Past Events

Apr 25, 2020
A half-day research conference for Emory undergraduates (particularly QTM majors and minors) who engaged in capstone research projects, independent research, and honors research. Cancelled due to COVID-19

March 20 - March 22
DataFest Emory is a three-day data analysis challenge being hosted for the sixth year by Emory College’s newest department, Quantitative Theory and Methods (QTM). Forty teams each comprised of four to five undergraduate level students from Emory, guest colleges (and some high schools) work together to attack a complex, surprise dataset. The intense competition encourages collaboration and competition while testing the team members’ computational skills and capacity to generate insights on real data. The selection of winners is based not only on the demonstration of computational and analytical skills, but also on how well results are communicated to a panel of judges. The event was cancelled due to COVID-19, but you can see more about DataFest on ASA DataFest here.

Apr 1, 2020
Andrew Barclay has worked in computing for over thirty years, both in the for-profit and the public sectors. He has expertise in hardware and software engineering, high-performance computing, digital signal processing, database design, data analysis, statistics, and public health. Two years after winning the Java Cup International software developers contest for his medical imaging software work, Andy retired from for-profit work in information technology. He now spends nearly all of his time doing training, research, statistics, software, and policy work in the child welfare field with his wife, Michelle Barclay. Andy and Michelle founded and endowed the Barton Child Law and Policy Center at Emory University School of Law to advocate for research-based policy and to encourage students from all disciplines into public-interest career paths. Andy holds Master's degrees in Mechanical and Electrical engineering from Stanford University and the Georgia Institute of Technology.

Feb 6, 2020
Onur Altindag is an Assistant Professor of Economics who studies health and population economics. He received his doctoral degree in Economics from the Graduate Center, City University of New York, was a David E. Bell Postdoctoral Fellow at Harvard University (2016-2018) and is currently a research fellow at the Economic Research Forum in Cairo and a visiting scientist at the Harvard Center for Population and Development Studies. In addition to developing poverty targeting models for multilateral international organizations, he recently won a $1.5 million grant from The Novo Nordisk Foundation to study the long-term effects of MMR (measles, mumps and rubella) vaccination using population registries in Denmark that track different aspects of people’s lives, including their immunization status, education, income and adult health.

Oct 7, 2019
Blake Fleischer, Ph.D is the senior data scientist Georgia-Pacific developing predictive models and computational cloud architecture. His background includes a PhD in physical chemistry from Georgia Tech (GT) and experience as a research scientist at the GT Partnership for an Advanced Computing Environment (PACE), where he provided GT and Emory University researchers with high performance computing research solution.  Blake was also the director of Anidata, an Atlanta-based 501c3 nonprofit applying active, practical, and data-related technical expertise to produce software to affect positive change, giving preference to endeavors that improve the lives of those in the margins of society.

Value at Risk, Cross-Sectional Returns and the Role of Investor Sentiment
Dec 6, 2019
Talk Abstract.In this paper, we find that the relationship between the value-at-risk (VaR) and expected returns is negative and this negative relationship between the VaR and expected returns can be explained by volatility in the U.S. market. However, for different levels of investor sentiment, this relationship changes. For a high sentiment period, VaR is negatively related with the expected return and cannot be explained by momentum, short-term reversal, volatility, and financial distress. In comparison, the relation between the VaR and expected returns during a low sentiment period is mixed.

Who Watches the Watchmen? Local News and Police Behavior in the United States
Apr 15, 2020
Talk Abstract. How do the media influence local institutions? We explore the question by looking at how acquisitions of local TV stations by a large broadcast group, which are likely to decrease local coverage in favor of national news, affect U.S. municipal police departments. To capture variation in local media, we implement a triple differences-in-differences design which exploits the staggered acquisition of local TV stations by the Sinclair Broadcast Group 2010-2017, together with cross-sectional variation in whether municipalities tend to be covered by local news at baseline. First, using a newly collected dataset of transcripts of local newscasts, we document that when a station is acquired by Sinclair, covered municipality experience a decline in the probability of appearing in the news with a crime story relative to non-covered municipalities. Second, we find that after Sinclair enters a media market, covered municipalities have lower violent crime clearance rates with respect to non-covered municipalities. Instead, we find no differential effect of Sinclair acquisitions on property crime clearance rates, which are minimally covered in local news. Increases in crime rates or resources allocated to police departments do not explain the result, reinforcing the interpretation that police effort allocation across different activities is changing as a result of changes in local news content.

The Political Economy of Discrimination
Dec 2, 2019
Talk Abstract. From burqa ban to minaret ban, from right to detain suspected illegal immigrants to restricting the help to migrants, the number of social laws specifically targeting a tiny proportion of citizens has raised in recent years across Western democracies. These symbolic policies, we show, are far from being innocuous: they can have far reaching consequences for large parts of the population. By raising the salience of certain social traits (e.g., Muslim identity) these laws can create a labour market loaded in favor of the majority (e.g., the non-Muslims), yielding higher unemployment rates and spells for minority citizens. These deleterious effects arise even absent any form of bias against, or uncertainty about, minority workers. Instead they are fully driven by social expectations about behavior and are best understood as a form of social discrimination. Importantly, we establish conditions under which a plurality of the citizenry demands the implementation of symbolic policies anticipating their labor market consequences. We further highlight that the implementation of symbolic policies is always associated with less redistribution and can be coupled with lower tax rates. We discuss several policy recommendations to limit the possibility of social discrimination arising.

Regression Inside Out
Sept 24, 2019
Talk Abstract. Linear regression methods are a workhorse in the social sciences. Such methods pay particular attention to the columns in a data matrix (i.e., the variables), without requisite attention to the cases or rows of the data matrix. We show how the cases co-constitute the effects of variables by decomposing regression coefficients by cases or subsets of them. We couple our decomposition with a visualization strategy that enables researchers to see the results of a regression model, including the role that particular cases have in the model. The visualization is, in effect, correspondence analysis with a dependent variable. Through two examples, we illustrate the value-added of our approach.

Targeting humanitarian aid to refugee households using administrative data: model design and validation
Sept 18, 2019
Talk Abstract.We develop and assess the performance of an econometric targeting model for unconditional cash and food assistance to Syrian refugees in Lebanon. We use a regularized linear regression method to derive a prediction model for household expenditure based on demographic and background characteristics from routinely collected administrative data. This approach compares favorably to the common, costlier “scorecard” Proxy Means Test (PMT) that requires a short household survey of the entire target population. We then validate the model with a contemporaneous out-of-sample test. Finally, we show that some behaviors indicative of high levels of vulnerability are positively associated with expenditure per capita – lending support for additional structures to allow potential beneficiaries the opportunity to access aid.

June 24, 2020
A party to celebrate the graduating class of 2020! Originally scheduled for May 1, but rescheduled as an online event on June 24 due to COVID-19.

Nov 11, 2019
QTM and the Barkley forum invite you to attend and participate in an evening of dinner and dialogue over a seated, three-course dinner in the New Student Center. The evening's conversation will center on the topic of "Do Data Privacy Violations Justify Throwing the Book at Facebook?" Business attire is required.

Nov 18, 2019 & Nov 20, 2019
This course, offered in collaboration with ECDS serves as an introduction to Python and will be presented by Dr. Robert Thornstad. It will cover the basics of loading packages, importing data, re-coding variables, and basic plotting. No Python experience necessary. This course is also recommended for those wishing to attend the Social Media Scraping in Python workshop who would like to refresh their Python skills before the workshop.

Nov 04, 2019 & Nov 06,2019
This two-part workshop, led by Sara Palmer and Joanna Mundy with Emory Center for Digital Scholarship ( ECDS), will provide an introduction to using the version control system Git from the command line. Attendees will learn the basics of creating a new Git repository, committing changes and pushing their work to GitHub, a free website for hosting code. Attendees are strongly encouraged to bring their own computers but laptops will be on hand for those who need them.

Oct 28, 2019
One of the greatest needs in today's workforce is effective communicators, particularly those with the ability to present data findings compellingly and often to non-technical audiences. This is the first of three workshops that will aid students in creating more impactful and effective presentations. It will focus on the initial planning phase of the presentation preparation process. Through the exploration of four different presentations, students will develop strategies for organizing their thoughts, assessing audience expectations, and creating a research agenda. This workshop was lead by Ed Lee (Director of Emory's Barkley Forum) and Mai Nguyen (QTM Visiting Instructor).

Oct 21, 2019 & Oct 23, 2019
Joanna Mundy PhD & Sara Palmer, digital specialists with ECDS will present a two-part workshop course covering data visualization in R. This is the first of the two sessions. Attendees should be familiar with basic R syntax. The workshop will use built-in datasets to create and modify many different graph types (scatter, histogram, boxplot, etc) and will also cover options for interactive visualizations and web-interfacing. Attendees are encouraged to bring their own computers with the most recent version of R and R Studio installed.

Oct 10, 2019
If your QTM background may lead to a life with more campus life, research and or academia in the foreground you may want to attend QTM's evening of Appetizers and Academic-Data Opportunities. The blending of good food and exposure to data-oriented academic experiences. Learn from university units and practitioners.

Sep 30, 2019 & Oct 10, 2019
This course serves as an introduction to R. QTM prep is partnering with Emory Center for Digital Scholarship (ECDS) to provide workshops for coding, publishing, and data visualizations this fall. Presenters Joanna Mundy & Elizabeth Sajewski will cover the basics of loading packages, importing data, recoding variables, and basic plotting. No R experience necessary. Attendees are encouraged to bring their own computers with the most recent version of R and R Studio installed.

Sep 25, 2019
This session with attorney Aaron Blumberg- 04'C, immigration legal expert from Miami, Florida, will contain essential employment information for visa holding juniors and seniors. Aaron Blumberg is an Immigration Attorney at Fragomen's Florida office, where he advises a diverse client base, including investors and entrepreneurs, colleges and universities, and multinational companies, on U.S. immigration law. Aaron has deep experience advising on the distinctive immigration requirements of colleges and universities. Aaron also advises international students on their visa options upon graduation and provides presentations and webinars all over the country on options for international students and recent graduates. As an Emory Alum, Aaron is always excited to return to campus and share his expertise with students. QTM is privileged to be able to host Mr. Blumberg, who will be meeting separately with international students in the law and business schools as well. Come prepared to take notes and ask questions!

Sep 18, 2019
Megan McRaney, Associate Director of Media Relations for Emory University, handles communications and media relations for Emory's social sciences, sciences, and research, as well as the Center for Community Partnerships. She will be available and on hand to assist with questions from QTM majors and minors about their LinkedIn profiles during this lab session. This is a time to learn tips and tricks for creating an engaging, informative, and useful LinkedIn profile from a pro who does it on a daily basis.

Sep 12, 2019
Dr. Mai Nguyen, PhD, is both a successful data journalist and one of Emory's College's new hires that will be working in the writing center and with QTM. Dr. Nguyen developed the resume template for QTM prep students that is available for supporting their efforts to get connected with QTM. She will be overseeing the review and feedback of QTM prep resume submissions and has graciously agreed to meet informally with QTM majors wanting to have another set of eyes help them with the final polishing of their resumes prior to the Fall Career Fair. Spaces are limited! Register for one of the three 30 minute sessions that will be offered by signing up for within the QTM prep calendar. (Each session has room for six students).

Sep 9, 2019
QTM SENIORS: Now is the time to begin seriously setting your sights on the path to your post-undergraduate opportunities. Kendra Owens, the Career Centers' QTM advisor is hosting a meeting you will want to make a priority to attend to help you organize planning for a successful transition year. Plan to be there!

Sep 4, 2019
It's a new academic year, QTM is a new department, we have 17 new ambassadors, a brand new professionalization program on Canvas, QTMprep, and KING POPS to give to the first 100 QTM majors coming by to take their free LinkedIn profile shots.

Apr 5 - Apr 7, 2019
DataFest @ Emory is a weekend-long data analysis competition for undergraduate students.  The competition originated at UCLA in 2011 and now takes place all over the country.  It is a true celebration for the data science community! More on ASA DataFest here. View details of the 2019 QTM event here.

Nov 19, 2018
The objective of this mini-hackathon is for participants to apply critical thinking skills along with statistical and analytical skills to find insights using publicly available socio-economic, demographic and geographic data collected from GA neighborhoods. Participants are encouraged to use out-of-the-box thinking to present innovative insights, pose intellectually sound questions, and posit possible solutions that can potentially be used by GA communities. View details of the Minihack here.

Climate change in the American mind
Apr 9, 2019
Talk Abstract. Climate change is one of the most daunting challenges of our time. Americans have diverse and sometime opposing views about global warming, fundamentally shaping the political climate of climate change. Dr. Leiserowitz will explain recent trends in Americans' climate change knowledge, attitudes, policy support, and behavior and discuss strategies to build public and political will for climate action.

Supercooled water clouds at polar latitudes
Mar 25, 2019
Talk Abstract. Among the many cloud types important to climate, supercooled water clouds over polar regions have been identified as a relevant challenge for climate models, owing in part to a paucity of observations adequate to study the dominant processes. Detailed remote sensing observations of persistent drizzle at cloud temperatures below –25°C over McMurdo Station, Antarctica, motivated a recent modeling study using large-eddy simulation and a climate model run in single-column model mode. The case study includes development of a stratiform water cloud in a relatively stable pre-cloud environment substantially above the surface layer, its transition to a continuously turbulent decoupled layer via rapid cloud-top cooling, and sustained drizzle and ice formation and precipitation. Representing this sequence of coupled dynamical and microphysical processes under highly supercooled conditions provides a strong test for climate model physics. We place this case study and this sequence of processes into the context of the most common types of supercooled water-bearing clouds found over polar regions, with an emphasis on the basic coupling of dynamical and microphysical processes.

Climate and Health
Feb 7, 2019
Talk Abstract. No Abstract.

The role of chemistry on volcanic climate forcing
Jan 17, 2019
Talk Abstract. Dr. Tsigaridis is currently working on a variety of topics related to aerosol research and their sources, sinks, and interactions with climate at various levels of complexity. His studies range from detailed aerosol processes such as the formation of secondary organic aerosols (SOA), to centennial time scale climate variability related to natural variability and external forcings. While his main expertise is organic aerosols, he is also experienced in working with all other aerosol types as well as tropospheric gas-phase and heterogeneous chemistry. Tsigaridis extensively used both box models that he developed, and 3-dimensional global models: the TM3 chemistry/transport model, the IPSL general circulation model LMDz-INCA, and the GISS modelE Earth System Model (ESM), for which he had contributed to the IPCC AR5 model development.

The Role of Atmospheric Aerosols in Climate Change
Thurs Nov 8, 2018
Talk Abstract. Dr. Min Zhong is an Assistant Professor in the Department of Environmental Engineering at Texas A&M University-Kingsville. Her research has focused on atmospheric aerosols and their impact on air quality, climate, and human exposure. Prior to working at TAMUK, she was a postdoc fellow at Emory University from 2013-2017. She earned her doctorate degree in environmental engineering from the University of Florida. She received her master’s degree of environmental engineering from Pohang University of Science and Technology, South Korea, and her bachelor’s degree of environmental engineering at Harbin Institute of Technology, China.

Climate Change 2018: Finding the Accelerator Pedal
Tues Nov 6, 2018
Talk Abstract. Dr. Field is the Perry L. McCarty Director of the Stanford Woods Institute for the Environment and the Melvin and Joan Lane Professor for Interdisciplinary Environmental Studies at Stanford University. Prior to his 2016 appointment at the Stanford Woods Institute, Field was a staff member at the Carnegie Institution for Science (1984-2002) and founding director of the Carnegie’s Department of Global Ecology (2002-2016). His research focuses on climate change, ranging from work on improving climate models to prospects for renewable energy systems and community organizations that can minimize the risk of a tragedy of the commons. He is involved in national and international-efforts to advance understanding of global ecology and climate change. Field was co-chair of Working Group II of the Intergovernmental Panel on Climate Change (IPCC) (2008-2015), where he led the effort on “Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation” (2012), and “Climate Change 2014: Impacts, Adaptation, and Vulnerability (2014). He has received much recognition for his work, including election to the US National Academy of Sciences, the Max Planck Research Award, and the Roger Revelle Medal.

Tidewater glaciers: Harbingers of climate change?
Thurs Oct 25, 2018
Talk Abstract. Tidewater glaciers (i.e., glaciers that terminate in the ocean) are perhaps the most iconic images of the cryosphere, attracting hundreds of thousands of tourists each year. Although all glaciers are a product of climate, the situation is more complex for tidewater glaciers which can undergo cycles of rapid retreat and slow advance independent of any climate forcing. In this talk I will discuss how processes that occur at the ends of these glaciers drive their advance and retreat cycles, how this relates to current climate warming, and why increasing our understanding of tidewater glaciers is critical to improving sea level rise projections.

Sufficient statistics for unobserved hetereogenity in structural dynamic logit models
Tues Apr 23, 2019
Talk Abstract. Victor Aguirregabiria is Professor of Economics at the University of Toronto. He has previously held appointments at the University of Western Ontario, University of Chicago, and Boston University. He is a graduate from CEMFI. He has served as Editor of the Journal of the Spanish Economic Association, and as Associate Editor of the Journal of Economic Literature, Quantitative Economics, Journal of Applied Econometrics, Journal of Business and Economic Statistics, International Journal of Industrial Organization, and Quantitative Marketing and Economics. He is Research Fellow of the Centre for Economic Policy Research, Honorary Fellow of the Spanish Economic Association, and Visiting Scholar at the Bank of Canada. His research has been published in leading international journals, including Econometrica, Review of Economic Studies, American Economic Review, and RAND Journal of Economics.  Professor Aguirregabiria’s research focuses on models, methods, and applications in Empirical Industrial Organization, with particular emphasis on dynamic structural models of oligopoly competition. His current methodological projects deal with biased beliefs and learning in dynamic games, identification and estimation with multiple equilibria, the characterization of dynamic discrete choice models using Euler equations, and fixed-effects estimation of dynamic discrete choice models. Professor Aguirregabiria is also currently working on empirical applications that deal with: geographic diffusion of banks’ credit; a micro-founded dynamic equilibrium model of the copper mining industry; and deregulation and spatial competition in the Ontario retail alcohol industry.

Theory and Causal Identification
Tues Oct 16, 2018
Talk Abstract. Since the mid-1980s there has been a marked increase in inequality across most democratic countries around the world. The super-rich now earn a much greater proportion of income and hold a much greater proportion of wealth than they did in the 1970s. The well-known Gini coefficient has steadily increased. The wages of rich individuals have increased much more quickly than those of poorer individuals, and the middle class has been hit hard, with the relative wage of the median earner steadily declining. Measured in any of a number of ways, the distribution of income across societies has become increasingly skewed toward the rich.

Discrimination, Market Information, and Social Information: Field Experiments on AirBNB and Alibaba
Wed Sept 12, 2018
Talk Abstract. The first paper studies the root cause of discrimination and how to eliminate discrimination on Airbnb. We conduct randomized field experiments among 1,256 hosts on Airbnb by creating fictitious guest accounts and sending accommodation requests to them. We find that requests from guests with distinctively African American names are 19 percentage points less likely to be accepted than those with distinctively White names. However, a public review posted on a guest page mitigates discrimination: when guest accounts receive a positive review, the acceptance rates of guest accounts with distinctively White and African American names are statistically indistinguishable. Past research has found discrimination in Business-to-Customer online marketplaces. There has been limited study on suppliers' discrimination behavior on B2B platforms in the context of global sourcing. In the second piece of research, we investigate whether price and racial discrimination of suppliers against retailers exists in B2B marketplaces across countries. We conducted field experiments on Alibaba.com, one of the largest global procurement platforms in the world. Further, we investigate the mechanism behind and use market and social information to mitigate discrimination.

Apr 15, 2019
Everyone tells you that experiential learning (like internships, volunteer opportunities, lab research, etc.) are vital for your future success. But it is not enough to simply do experiential learning. You need to understand how to talk about what you've done and come up with a compelling story for how and why your skills translate to your future career. Learn more about your career options with Kendra Owens of the Emory Career Center.

Apr 4, 2019
Learn how to effectively present your data with Edward Whillies Lee III. Edward Lee III is the senior director of the Alben W. Barkley Forum for Debate, Deliberation, and Dialogue, which houses Emory’s nationally acclaimed debate team.

Apr 1, 2019
A pre-datafest workshop geared towards helping participants develop strategies for cleaning, sampling and reshaping data.

Mar 29, 2019
Sometimes, the best way to understand and communicating data is to visualize it! This workshop, lead by our own Dr. Zhiyun Gong, walked participants through ways to choose the right type of visualization and then visualize data in R.

Mar 28, 2019
Intermediate/advanced tableau with special topics including mapping. Lead by Paul R. Lisborg of OldCastle Architectural.

Mar 27, 2019
A pre-datafest workshop that went through the fundamentals of Python for data cleaning, reshaping, and basic analysis.

Mar 26, 2019 and Feb 20, 2019
One of the most important and challenging skills for young professionals to master is the art of salary negotiation. This workshop walked participants through strategies for requesting the right compensation for their skills and experience.

Mar 20, 2019
Co-sponsored by the Emory Center for Digital Scholarship, the Advanced Tableau workshop covered skills to enhance tableau dashboards and stories.

Mar 19, 2019
Led by Dr. Jeremy Jacobson, this practical workshop session taught the fundamentals of working with database systems in the SQL coding family.

Mar 6, 2019
A co-sponsored workshop with ECDS, this event covered topics related to data cleaning, such as removing duplicates, fixing structural errors, deciding how to fill in missing data, and other quality control concerns.

Feb 27, 2019
Version control is paramount for reproducible science and for data collaboration in the workplace. Git and Github are tools that streamline version control and enable sharing across communities of data scientists. This workshop introduced participants to data science in Git and GitHub

Feb 26, 2019
To get you from college to career, it is vital to have an understanding of the interview process for data-enabled career roles. Almost all of these roles require a technical interview. What does that look like? This workshop covered the components and expectations for the technical interview.

Feb 25, 2019
Hear from data analyst Steven Howard while eating a hearty lunch provided by QTM. Steven is the Digital and Applied Analytics Leader at Accenture and is a hands-on leader, skilled at applied intelligence service development and delivery. Now concentrating on the intersection of data, technology, and healthcare, he has developed actionable operations and behavioral insights, predictive analytics, direct & digital marketing, and data monetization teams. He's known for focusing everyone on growing and improving their clients' business, aligning on goals, and developing businesses.

Feb 20, 2019
Introduction to network analysis and applications. Co-sponsored with ECDS.

Feb 13, 2019
Introduction to using R text analysis tools and Twitter's (free-level) developer API to conduct topic analysis and answer questions about behavior. Co-sponsored with ECDS.

Jan 30, 2019
After mastering the basics of R, it is advisable to delve deeper into R's data analysis capabilities. This workshop covered ggplot2 and other graphing package tips and tricks. Co-sponsored with ECDS.

Jan 23, 2019
A primer on programming in R. Co-sponsored with ECDS.

Nov 13, 2018
Amelia Schaffner is the irector of Entrepreneurship at Emory University's Goizueta Business School. She is responsible for developing the school's entrepreneurial culture, thinking, and initiatives, partnering with students, faculty, alumni, and the local ecosystem of investors, VCs, and organizations. She is involved in a number of initiatives, including the RAISE Forum for startups and investors in the southeast, the pitch-the-professors program to support new student concepts working with the Atlanta Tech Village incubator, the AHIA (Advancing Healthcare Innovation in Africa) Initiative, and more.

Nov 12, 2018
Get your resume noticed! Co-sponsored with Emory Career Center.

Nov 7, 2018
Python is a powerful, highly sought-after skill for budding data scientists in both academia and industry. Join us for a python workshop lead by Marissa Adams, QTM Alumna and Lead Developer of Data Science at ANNUITAS. Learn how to: row/column bind, mutate columns, make data frames/data tables, and much more!

Nov 7, 2018
Explore career paths at the intersection of data science and finance. Learn about what's happening at the forefront of several areas in the finance industry. Hear from distinguished Emory alumni about the impact of data in the areas of asset management, portfolio management, and real estate. And so much more. Panel guests include Michel Kessel (Principal of Lighthouse Realty Advisors of NY/NJ), Michael Kainsky (Managing Director of Neuberger Berman of NY), and Kunal Soni (Managing Director of the Carlyle Group of LA)

Oct 30, 2018
Come hear from QTM almuni about ways to "math-up" skillsets learned in your classes.

Oct 18, 2018
Ernest Brown, Business Analyst, Business Development & Strategic Relations at Kaiser Permanente will discuss the ways in which data informs decision making in healthcare, government, and business. Lunch provided by QTM.

Sep 24, 2018
Hear panelists working in non-profit and government fields discuss the role of data science in their jobs. Learn about potential career paths!

Sep 24, 2018
Join us for a networking evening to explore career pathways and to learn from industry experts, academics, graduate program leaders, & alumni. Over 20 guests will be available to take questions and chat with current students at this networking session.

Sep 12, 2018
Engage with Career Center expert Kendra Owens as she walks QTM seniors through the job search.

The Woodruff Library will host the Emory Digital Humanities Symposium: DH for the Study and Teaching of South Asia on April 6^th and 7^th. This is an interdisciplinary and international symposium on newly formed approaches to digital humanities in the field of South Asian Studies, and it brings together scholars and library professionals actively engaged in DH projects related to South Asia.

The two-day symposium of panels, demos, and a roundtable discussion will replicate the cycle of scholarly production – one in which individuals access archives or create their own, analyze data, teach about their research, craft scholarship, and publish in some format for public consumption. Please see the attached flyer for detailed information about the featured projects and presentations.

Measurement Error without Exclusion: The Returns to College Selectivity and Characteristics
Wednesday Feb 21, 2018 12:00pm-1:30pm || Modern Languages 201
Talk Abstract. This paper studies the identification of the coefficients in a linear equation when data on the outcome, covariates, and an error-laden proxy for a latent variable are available. We maintain the classical error-in-variables assumptions and relax the assumption that the proxy is excluded from the outcome equation. This enables the proxy to directly impact the outcome and allows for differential measurement error. Without the exclusion restriction, we first show that the coefficients on the latent variable, the proxy, and the covariates are not identified. Then, we derive the sharp identification regions for these coefficients under either or both of two auxiliary restrictions. The first restriction weakens the assumption of “no measurement error” by imposing an upper bound on the net of the covariates “noise to signal” ratio, i.e. the ratio of the variance of the measurement error to the variance of the latent variable given the covariates. The second restriction weakens the proxy exclusion restriction by specifying whether the latent variable and its proxy affect the outcome in the same or the opposite direction, if at all. Using the College Scorecard data, we employ this framework to study the financial returns to college selectivity and characteristics. Here, college selectivity, defined as the average SAT score of a student cohort, serves as a proxy for the latent average scholastic ability and is included in the average earnings equation. We obtain an informative upper bound on the return to college selectivity which becomes smaller upon conditioning on the instructional expenditures per student and the completion rate. Further, we obtain tight bounds on the returns to the college characteristics and find that conditioning on the composition of majors reduces the magnitude of the bounds on the effect of some of these characteristics, such as the gender composition. 

Partisan Tribalism or Policy Voting?
Monday Dec 11, 2017 3:00pm-4:00pm || White Hall 102

Understanding the Great Gatsby Curve
Thursday Feb 1, 2018, 12:00pm-1:30pm || MLB 201
Talk Abstract. The Great Gatsby Curve, the observation that for OECD (Organisation for Economic Co-operation and Development) countries, greater cross-sectional income inequality is associated with lower mobility, has become a prominent part of scholarly and policy discussions because of its implications for the relationship between inequality of outcomes and inequality of opportunities. We explore this relationship by focusing on evidence and interpretation of an intertemporal Gatsby Curve for the United States. We consider inequality/mobility relationships that are derived from nonlinearities in the transmission process of income from parents to children and the relationship that is derived from the effects of inequality of socioeconomic segregation, which then affects children. Empirical evidence for the mechanisms we identify is strong. We find modest reduced form evidence and structural evidence of an intertemporal Gatsby Curve for the US as mediated by social influences.

Design for Humanistic Inquiry
Thursday Feb 1, 2018, 5:30pm-7:00pm || Woodruff Library Jones Room
Talk Abstract. In the last decade, the use of software tools for data analysis and data visualization has proliferated in the humanities. The availability of digitized material, increasing computational power, and analytical techniques adopted from network science, geospatial analysis, and natural language processing have inspired new ways to interrogate cultural heritage data. But those tools, reliant on statistical modeling, also limit the questions we can ask and the meaning we discover. In order to uncover significance in materials that have passed through many hands, and stories that have been telegraphed by different voices inflected with opinion, argument, and perspective, we need tools that support human-scale exploration of complex systems. The research process requires "thinking through data," which is how we describe the reflective, slow collecting and editing of information, as distinct from the quick, mechanistic, algorithmic approach to data processing. This talk will demonstrate how the requirements of humanistic inquiry are encoded in tools developed at Humanities + Design and why, in this age of artificial intelligence, it is so important to capture the intellectual work of data modeling.

See https://scholarblogs.emory.edu/dmh/about/ for more information.

This workshop will provide an overview of Tableau, software for data visualization and analysis. In this workshop, you will learn how to connect to data, create views, perform simple calculations, and bring your views together in a unified way. Please bring a laptop with Tableau Desktop 10.0+ installed. Click here for installation instructions. Visualizations made in past workshops have been tremendously successful, attracting attention from Tableau Labs and Delta. Led by Paul Lisborg, Manager of Business Intelligence & Analytics at Oldcastle Architectural.

Friday May 12, 2017
This mini-conference brought together Emory faculty and distinguished scholars from around the country to share and exchange thought leadership in the area of political economy.

June 27 - 28, 2016
Event Program. The theme of 2016’s Southeast Educational Data Symposium (SEEDS) was “Closing the Loop.” By considering data, intervention, and evaluation together as part of a common conversation with the goal of enhancing student success, analytics can become more actionable for educators and more beneficial for students.

Mar 31 - Apr 2, 2017
DataFest @ Emory is a weekend-long data analysis competition for undergraduate students.  The competition originated at UCLA in 2011 and now takes place all over the country.  It is a true celebration for the data science community! Details of the QTM DataFest can be found here. Informarion about ASA DataFest more generally is here. 

How Do Right-To-Carry Laws Affect Crime Rates? Coping with Ambiguity Using Bounded-Variation Assumptions
Wednesday Apr 12, 2017
Talk Abstract. No abstract.

Does Representation Induce Polarization? A Theory of Choosing Representatives
Wednesday Mar 29, 2017
Talk Abstract. No abstract.

Recent Advances in the Theory of Experimentation
Wednesday Feb 1, 2017
Talk Abstract. The social sciences have seen great advances in the use of field experiments. These advances have been largely based on pragmatic concerns. In this talk, I will apply the mathematical tools of behavioral decision making to try to understand why we run experiments the way we do, and how we can use this understanding to create new experimental techniques. Some of these techniques are being applied in the field, and I will summarize how well they do (or don’t) work.

Before Computer Scientists Make Us Obsolete… Let’s Take Advantage of Them
Thursday, Dec 8 2016
Talk Abstract. The talk illustrates some of the cutting-edge tools that data miners and computational linguists have been perfecting over the last decade or so. We will start by showing how basic principles of machine learning built in PC-ACE (Program for Computer-Assisted Coding of Events) make manual approaches to text such as Content Analysis or Quantitative Narrative Analysis (QNA) more efficient and more reliable than in CAQDAS programs (Computer-Assisted Qualitative Data Analysis Software, such as Atlas.ti, NVivo, MaxQda). We will show how narrative data in PC-ACE can be visualized in dynamic network graphs and dynamic GIS maps. For illustrative purposes we will rely on a corpus of a thousand newspaper articles on lynching events that occurred in Georgia between 1875 and 1935. The main focus of the talk will be on Natural Language Processing (NLP) tools and what they can do for us: Part-of-Speech (POS) tagging, Named Entity Recognition (NER), Dependency Parsing, and Sentiment analysis in Stanford CoreNLP, topic modelling in Mallet, sentence complexity in Computerized Linguistic Analysis System (CLAS), Key-Word in Context searches (KWIC). We will use these computational tools to compare the short story Dry September, a fictional story of lynching by Nobel laureate William Faulkner, to the thousand newspaper articles on real Georgia lynchings.

Can Math Help Save Democracy? Partisan Gerrymandering and the Supreme Court
Tuesday Mar 21, 2017
Talk Abstract. In partisan gerrymandering, boundaries are drawn to encircle as many voters as possible of the opposing party, thereby packing them into a small minority of districts. The Supreme Court identifies partisan asymmetry is a hallmark of this offense against democracy, but has not settled upon a manageable standard. I will describe three tests (68 Stan. L. Rev. 1263) that meet existing legal criteria. Two tests are based on classical statistical testing, and one is based on simulation of a partisan- neutral process. Crucially, none of the tests depends on geography. If adopted by courts or through citizen initiatives, these tests may help repair a bug in American democracy.

Heterogeneous Production Functions, Panel Data, and Productivity Dispersion
Tuesday Nov 1, 2016
Talk Abstract. In this lecture we explore identification in linear panel data models with time varying random coefficients that can be correlated with explanatory variables. We also identify the moments of the distribution of random coefficients conditional on the explanatory variables. We conclude with a discussion of applications of our results to production functions.

Feb 15 - 17, 2017
An awareness event for the Quantitative Social Sciences Major. This event encouraged students to network with QTM on Facebook, drop by the QTM offices and learn more about data science, and raffled prizes to students.

Thursday Oct 20, 2016
We hold an annual netowrking night to help put QSS majors in touch with each other, with academia, and with industry, to see how they can use their major. 2016 representatives came from diverse academic fields (Political Science, Biology, Sociology, Psychology/Linguistics, Math) and from industry partners (Ernst & Young, Turner, etc.).

May 30, 2017 - June 2, 2017
This interdisciplinary workshop brought researchers working across the fields of computational text analysis and Japanese Studies together. The sessions focused on the unique challenges of digital analyses of Japanese texts, including challenges of OCR (Optical Character Recognition) for Japanese texts, specialized tools for classical, early modern, and modern Japanese grammar, and more. The workshop was sponsored in part by QTM.

Friday Feb 24, 2017
The goal of this workshop was to introduce individuals to ArcGIS software and demonstrate the functionality and potential of GIS for visualizing directional trends over time, density of events, and more. Led by Megan Slemmons, GIS Librarian at the Emory Center for Digital Scholarship.

Friday Feb 17, 2017
R is a popular program for statistics, but it is also capable of producing high-quality data visualizations. This workshop focused on exploring ggplot2 and plotly for data visualization. Led by John Bernau, Digital Scholarship Specialist at Emory Center for Digital Scholarship.

Feb 8 - 9, 2017
This two-day workshop covered data processing and visualization from the start to the finish of a project using Tableau software. Led by Paul Lisborg, Manager of Business Intelligence & Analytics at Oldcastle Architectural.

Friday Jan 20, 2017
Text analysis is a valuable tool for social scientists. This workshop covered computational techniques for studying the content of text, using Twitter as a test case. Led by Joshua Fjelstul, Graduate Student in the Emory Political Science department.

Nov 2-3, 2016
This Workshop was intended for Python and programming novices. The goal of the workshop was to acquaint novices with python command line essentials and related tools (Github and Jupyter) for data science applications. This event was held twice; once in Fall 2016 and again in Spring 2017. Led by Jeremy Jacobson, Visiting Professor at the Institute for Quantitative Theory and Methods.

Wednesday May 20, 2015
This interdisciplinary symposium brought together Emory faculty and internationally-recognized scholars from around the country, spanning fields as diverse as psychology, neuroscience, physics, and medicine, to share how they are using computational and quantitative methods to study the production and perception of vocal communication signals. The event was sponsored by Emory Conference Subvention Fund, the Institute for Quantitative Theory and Methods, the Center for Mind, Brain and Culture. Additional event details.

Title: Topography of Human Vocal Development

Speaker: Dr. Eugene Buder (University of Memphis)

Title: Sequence learning and the cultural evolution of language

Speaker: Dr. Morten Christiansen (Cornell University)

Title: Evaluating the communicative value of mouse vocalizations

Speaker: Dr. Katrin Schenk (Randolph College)

Title: Statistical constraints on vocal learning in songbirds

Speaker: Dr. Samuel Sober (Emory University)

Title: How a song is learned: mechanisms of template matching

Speaker: Dr. Ofer Tchernichovski (Hunter College, CUNY)

Title: Emotional Content in Acoustic Communication: Messages Sent, Messages Received

Speaker: Dr. Jeffrey J. Wenstrup (Northeast Ohio Medical University)

Darwin’s Phylogenetic Reasoning
Tuesday March 22, 2016

Does Ockham's Razor Solve the Mind/Body Problem?
Thursday March 17, 2016

Drew Linzer, Chief Data Scientist, Daily Kos
Thursday Dec 3, 2015

Thursday Oct 8, 2015
QTM & the Career Services office put on a great event in the Fall for students to hear directly from the experts how quantitative training is changing their field. Students had an opportunity to chat with guests from academia, business, the non-profit sector and government during our 2015 Networking Night.

Introductory Remarks

Clifford Carrubba (Professor, Department of Political Science and Institute for Quantitative Theory & Methods, Emory University)

Speaker: Nicole Miller (Manager, Quantitative Economics & Statistics (QUEST), Ernst & Young)

L-3 Data Tactics

Speaker: Nathan Danneman (Data Scientist, L-3 Data Tactics, Federal Contractor)

Excellence in Education

Speaker: Dana Rickman (Policy & Research Director, GA Partnership for Excellence in Education, Non-profit)

Biostatistics & Bioinformatics

Speaker: Howard Chang (Assistant Professor, Department of Biostatistics & Bioinformatics, Emory University)

Q & A Session

Panelists: Nicole Miller, Nathan Danneman, Howard Chang, Dana Rickman

Thursday Feb 12, 2016
This workshop is designed to provide attendees with a basic introduction to text analysis — computational techniques for studying the content of text — for social science applications. It will feature applications to social media analysis (Twitter). No prior experience working with text data is needed. Basic knowledge of R is helpful but not required. The workshop will include three mini-units: (1) collecting and structuring raw text for analysis; (2) cleaning and manipulating text to prepare it for analysis; and (3) describing and analyzing text for social science applications. The workshop was sponsored by QTM.  Led by Joshua Fjelstul

Friday Dec 4, 2015
As computing grows ever more embedded into daily life, computational techniques can now be applied to shed insight on basic social science questions. At the same time, the increasingly social aspect of computing means that technologists must wrestle with and understand social science principles. The emerging cross-disciplinary field of computational social science addresses these challenges and opportunities, combining computational methods with social science theory and research. Georgia State University hosted the third annual workshop for exchanging research ideas in this growing research area. The workshop was sponsored in part by QTM. Additional event details.

Friday Feb 20, 2015

Apr 10 - 12, 2015
A weekend-long data analysis competition hosted by the Institute of Quantitative Theory and Methods and developed by the American Statistical Association. We give you the data set; you draw the interesting insights. More on QTM's DataFest event can be found here.

Do counts of digital traces count for learning?
Friday Apr 17, 2015
Talk Abstract. The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach for advancing our understanding of the learning process. This promise motivated the emergence of the new field learning analytics and mobilized the education sector to embrace the use of data for decision-making. This talk will first introduce the field of learning analytics and touch on lessons learned from some well-known case studies. The talk will then identify critical challenges that require immediate attention in order for learning analytics to make a sustainable impact on research and practice of learning and teaching. The talk will conclude in discussing a set of milestones selected as critical for the maturation of the field of learning analytics. The most important take away from the talk will be that learning analytics are about learning and that computational aspects of learning analytics need to be integrated deeply with educational research and practice.

Hail to the Data: What We're Learning from Learning Analytics
Wednesday Apr 8, 2015
Talk Abstract. At the University of Michigan today, many interactions among teachers and students are mediated by technology. Students use clickers in class, do homework online, write and revise papers and project in the cloud, and produce video of presentations. This 'digital exhaust' gives us unprecedented opportunities to understand teaching and learning and improve student success. A new field of Learning Analytics is emerging to take advantage of this opportunity. Professor Timothy McKay’s presentation will introduce this topic using examples from a variety of local projects.

Towards Long-Term and Actionable Prediction of Student: Outcomes Using Automated Detectors of Engagement and Affect
Friday Feb 9, 2015
Talk Abstract. In recent years, researchers have been able to model an increasing range of aspects of student interaction with online learning environments, including affect, meta-cognition, robust learning, and engagement. In this talk, I discuss how automated detectors of engagement and learning can be used in prediction of long-term student outcomes, illustrating this with examples of how affect, engagement, and learning during middle school use of educational software can support prediction of student long-term success, including end-of-year learning, decisions about whether to attend college, and even what major a student chooses. These predictive models can in turn support inference about what factors make a specific student at- risk for poorer learning or lower long-term engagement in learning.

Advancing University Teaching and Learning Analytics: Linking Pedagogical Intent and Student Activity through Data-Based Reflection
Monday Nov 17, 2014
Talk Abstract. Learning analytics are data traces of student activity that can be used to better understand and support learning processes and outcomes. Over the last few years there have been remarkable advances in our ability to calculate and display useful information about what students are doing. Now, we face the challenge of how to mobilize this intelligence to have a meaningful impact on university teaching and learning. We need to consider and design for the ways in which learning analytics can become a part of (and change) the activity patterns of instructors and students. Working within the scope of the university course, I describe ways to integrate learning analytics into teaching and learning processes by using data-informed reflection to probe the connections (and disconnects) between instructors’ and designers’ pedagogical intents and students’ actual activity patterns. Particular attention will be paid to roles for students in the process, and the use of different reference frames for data interpretation. To ground the discussion, work from the E-Listening Project at Simon Fraser University will be presented as an initial example of a learning analytics application developed and implemented in a university course using such an integrated approach.

Teaching and Learning in an Evolving Educational Environment
Wednesday Oct 15, 2014
Talk Abstract. Charles Dziuban, educational researcher and internationally recognized expert on blended learning environments, will present outcomes from twenty years of research on the concept of learning analytics through an effective teaching and learning perspective. He compares student success rates in varying course modalities in addition to preference for instructional formats. He showed the characteristics of excellent instructors from the student point of view using concepts such as the Anna Karenina Phenomenon. Finally, he presented examples of how individual faculty members at the University of Central Florida are undertaking an analytic approach to improving their courses with the scholarship of teaching and learning.

Exploratory Thematic Analysis for Historical Newspaper Archives
Wednesday Apr 15, 2015
Talk Abstract. How do humanities scholars make sense of new or otherwise unfamiliar archives? Is there a role for computational text analysis in the process of sensemaking? In this talk, I propose that topic modeling, when conceived as a process of thematic exploration, can provide a new entry-point into the sensemaking process. I will present new research from the Georgia Tech Digital Humanities Lab on a software tool called TOME: Interactive TOpic Model and MEtadata Visualization, designed to support the exploratory thematic analysis of digitized archival collections. TOME is centered around a set of visualizations intended to facilitate the interpretation of the topic model and its incorporation into extant humanities research practices. In contrast to other topic model browsers, which present the model on its own terms, ours is informed by the process of conducting early-stage humanities research. This talk will thus also demonstrate the conceptual conversions--in terms of both design and process-- that interdisciplinary collaboration necessarily entails. In making these conversions explicit, and exploring the implications of their successes and failures, my collaborators and I take up the call, as voiced by Johanna Drucker (2011), to resist the “intellectual Trojan horse” of visualization. We seek to model a new mode of interdisciplinary inquiry, one that brings the methodological emphasis of the digital humanities to bear on the practices of humanities research and computer science alike.

Quantitative Models for Ancient Historians
Tuesday Oct 7, 2014
Talk Abstract. Realistic simulation of historical processes is a final frontier for the study of the past. The ultimate purpose of simulation is to test causal hypotheses regarding the nature of the determinants of observed outcomes. This approach rests on the ability to assess the impact of different variables in an interactive model, an ability that requires concurrent consideration of factors such as geography, ecology (climate, land cover), natural endowments (such as mineral resources), the distribution of population, and the real cost of connectivity in terms of time and price, which is itself a function of geographical, infrastructural and technological conditions as well as institutional constraints. Recent years have witnessed considerable progress in discrete areas of simulations. The most notable examples include increasingly sophisticated raster-based simulation of state formation (PNAS 110, 2013, 16384-9) and geospatial modeling of the patterning of connectivity created by real transfer costs (Orbis 2.0, June 2014). We now also have access to spatial models for population and land use (e.g. HYDE), as well as to a growing number of geo-referenced datasets for various features such as settlements and certain types of deposits. What is still missing is proper integration of all these diverse elements, which is a vital precondition for meaningful multivariate simulation and hypothesis testing. Cooperation among different project teams was established in 2013/14 in order to pursue this goal, both specifically for Roman history and more globally. This paper, which draws on an international collective effort, seeks to illustrate the potential and challenge inherent in this ongoing endeavor by means of case studies (currently in progress) that focus on the properties of economic and political connectivity in the Roman world.

Neural Computations Underlying Acoustic Communication in Drosophila
Wednesday April 1, 2015
Talk Abstract. This talk addresses the goal of our research: to discover fundamental principles about sensory perception, sensorimotor integration, and the generation of behavior. To make these discoveries, we focus primarily on the acoustic communication system of Drosophila. Similar to other animals, flies produce and process patterned sounds during their mating ritual: males generate songs via wing vibration, while females arbitrate mating decisions. I will discuss how our studies, using quantitative behavior, in vivo electrophysiology, computational modeling, and genetic tools, address the neural mechanisms underlying both the production and perception of dynamic courtship songs in Drosophila.

Decision Making in Animal Groups
Wednesday Feb 18, 2015
Talk Abstract. I talk about a theoretical approach to collective decisions that works well across species. I also take the opportunity to present idTracker (www.idtracker.es), software that analyses video to identify each individual in a group. This identification is used for tracking without propagation of mistakes, thus obtaining large amounts of high quality data. I end my talk with applications of our models to understand aggregation in adverse conditions, how humans make estimations in groups, and how we can improve them.

Maximally Informative Behaviors Implemented by Simple Neural Circuits
Wednesday Jan 14, 2015
Talk Abstract. In this talk, I show that the foraging patterns of a small nematode, C. elegans, can be accurately described by theories of maximally informative search strategies. Further it is possible to design environmental conditions for C. elegans where worm foraging patterns follow maximally informative search strategies that are in direct contrast to chemotaxis predictions. in order to perform a maximally informative search, animals technically need to maintain a full mental map for the likelihood distribution of food throughout the environment. However, my colleagues and I find that this search can be approximated well (under conditions of our experiments) with a simple drift-diffusion model. The corresponding neural implementation within the C. elegans neural circuits will be discussed.

Statistical Inference on Networks of Spiking Neurons
Tuesday Dec 2, 2014
Talk Abstract. Coupling large numbers of relatively simple elements often results in networks with complex computational abilities. Examples abound in biological systems - from genetic to neural networks, from metabolic networks to immune systems, from networks of proteins to networks of economic and social agents. Recent and continuing increases in the experimental ability to simultaneously track the dynamics of many constituent elements within these networks present a challenge to theorists: to provide conceptual frameworks and develop mathematical and numerical tools for the analysis of such vast data. The subject poses great challenges, as the systems of interest are noisy and the available information is incomplete.

For the specific case of neural activity, Generalized Linear Models provide a useful framework for a systematic description. The formulation of these models is based on the exponential family of probability distributions; the Bernoulli and Poisson distributions are relevant to the case of stochastic spiking. In this approach, the time-dependent activity of each individual neuron is modeled in terms of experimentally accessible correlates: preceding patterns of activity of this neuron and other monitored neurons in the network, inputs provided through various sensory modalities or by other brain areas, and outputs such as muscle activity or motor responses. Model parameters are fit to maximize the likelihood of the observed firing statistics; smoothness and sparseness constraints can be incorporated via regularization techniques. When applied to neural data, this modeling approach provides a powerful tool for mapping the spatiotemporal receptive fields of individual neurons, characterizing network connectivity through pairwise interactions, and monitoring synaptic plasticity.

Life’s Information Hierarchy
Wednesday Nov 19, 2014
Talk Abstract. We have proposed that biological systems are information hierarchies organized into multiple functional space and time scales. This multi-scale structure results from the collective effects of components estimating regularities in their environments by coarse-graining or compressing time series data and using these perceived regularities to tune strategies.  As coarse-grained (slow) variables become for components better predictors than microscopic behavior (which fluctuates), and component estimates of these variables converge, new levels of organization consolidate, giving the appearance of downward causation. This intrinsic subjectivity suggests that the fundamental macroscopic properties in biology will be informational in character. If this view is correct, a natural approach is to treat the micro to macro mapping as a collective computation performed by system components in their search for configurations that reduce environmental uncertainty.  I discuss how we can move towards a thermodynamics of biology by studying this process inductively. This includes strategy extraction from data, construction of stochastic circuits that map micro to macro, dimension reduction techniques to simplify the circuits and move towards an algorithmic theory for the macroscopic output, and macroscopic tuning and control.

Is ‘Big Data’ a Cause or an Effect? Filtering Signals from Noise
Wednesday Apr 8, 2015
Talk Abstract. The speed and complexity of business problems are accelerating like never before. We believe the companies that will succeed in a world of increasing change are the ones who are able to benefit from this change. Decision Sciences and Big Data Analytics provide a powerful opportunity for companies to turn the complexity of their business environments to their advantage. This lecture will discuss how companies are adopting a new ‘Art of Problem Solving’ – and what you can expect from this vastly growing arena. This event was co-sponsored by QTM and the Emory Data Analytics Club

Quantifying the Social Logic of Buildings and Cities
Wednesday Nov 12, 2014
Talk Abstract. The built environment is the largest and most complex physical human artifact. Relational patterns of connections and separations in the built space underlie important aspects of human behavior and illuminate the spatial logic of society. Buildings and cities are described according to topological properties in contrast to geometrical representations that have traditionally informed architectural and urban theories. This research is aimed at unfolding important aspects of the social logic of built space by means of quantitative analysis of buildings and cities based on graph-theoretic methods. Spatial complexes are studied as networks of connections among elementary units of rooms, circulation spaces and streets, which support structured conditions of encounter, co-presence, co-awareness, and movement. Several themes of inquiry are discussed supported by the morphological analysis of various scales of built space including: the evolution of Adriatic and Ionian coastal cities, complex dynamics of arterial roads during city growth, shape description based on human perception of space, interaction between boundary shape and circulation structure in buildings and cities, and Balkan vernacular houses. The research spans cross-disciplinary links from architecture and urbanism to complexity science, graph theory, morphology, morphometry, physiography, historical cartography, urban history, organizational management, and environmental studies.

Monday Apr 13, 2015
This workshop was designed to provide an introduction to web scraping for non-programmers. Scraping is the method by which researchers collect large online data quickly and efficiently. We used a free point-and-click software program called OutWit Hub to explore this method. We began by explaining what scraping is and how it works. Along the way, we learned how to navigate around a website’s structure, identify the information we need, and extract and output it as data. We also explored some of the common misconceptions and legal implications of scraping copyrighted content. Finally, we got hands-on experience with this powerful tool. By the end of this workshop, participants were able to use this method on their own. Led by Trent Ryan.

Monday Jan 12, 2015
Instructors from the Inter-University Consortium for Political and Social Research (ICPSR) Data Archives partnered with the Emory Center for Digital Scholarship (ECDS) and the Institute for Quantitative Theory and Methods (QTM) to host a Data Curation Workshop in the Spring of 2015. The workshop aimed to give researchers hands-on experience curating quantitative datasets for long-term access and preservation in accordance with federal funding agency mandates and requirements from journals and publishers.

The workshop introduced the study of space in the built environment from a social viewpoint. The continuous built space is represented in discrete components according to basic aspects of human behavior and activities including movement, co-awareness and co-presence. Case studies of various scales, including houses, complex buildings, settlements, and archaeological records, were examined according to three main representational techniques of convex partitions, axial maps and visibility fields. Relational patterns of connections and separations among spatial components were analyzed as networks according to graph-theoretic methods to reveal the underlying social function (interfaces and program). The workshop covered the drawing of maps and isovists; justified graphs; UCL Depthmap software; data export and import; space syntax configuration, topological measures; and interpretation of graphical and numerical results. Led by Dr. Ermal Shpuza.

Apr 4 - 6, 2014
A weekend-long data analysis competition hosted by the Institute of Quantitative Theory and Methods and developed by the American Statistical Association. We give you the data set; you draw the interesting insights. 2014 was the inaugural year for ASA DataFest at Emory.

Using Analogy to Discover the Meaning of Images
Wednesday Apr 9, 2014
Talk Abstract. Enabling computers to understand images remains one of the hardest open problems in artificial intelligence. No machine vision system comes close to matching human ability at identifying the contents of images or visual scenes or at recognizing similarity between different scenes, even though such abilities pervade human cognition. In this talk I will describe research--currently in early stages--on bridging the gap between low-level perception and higher-level image understanding by integrating a cognitive model of pattern recognition and analogy-making with a neural model of the visual cortex. This event was co-hosted by QTM, the Center for Mind, Brain, and Culture (CMBC), and the Department of Biology.

Help or Hindrance? The Role of Humanitarian Military Interventions in Human Security NGO Operations
Wednesday Mar 5, 2014
Talk Abstract. How do humanitarian military interventions influence the work of NGOs?  Previous work has found that the joint presence of military and NGO actors is essential for the fulfillment of the most complex human security tasks after humanitarian disasters, like improvements in government human rights performance and  economic development.  NGOs were better able to fulfill their human security objectives when humanitarian military interventions were present, arguably because military interveners provide logistical support that aids in collaboration between various humanitarian actors, including NGOs, and because military interveners provide security. In this piece, we use both network analysis methods to examine the process through which military interventions improve the ability of NGOs to connect to each other and econometric methods to examine the ways in which interventions influence the violence NGOs face from domestic actors.  Using a dataset of over 2,500 human security organizations involved in states with a history of humanitarian disasters, we find that human security NGOs involved in countries where there is a humanitarian military intervention benefit in terms of their network ties to other NGOs. This event was co-hosted by QTM and the Department of Political Science.

Communities in Networks
Friday Feb 7, 2014
Talk Abstract. Network science is an interdisciplinary endeavor with methods and applications drawn from across the natural, social, and information sciences. A prominent problem in network science is the algorithmic detection of tightly connected groups of nodes known as communities. Community detection has been used successfully in a number of applications, some of which we highlight in this talk. We also discuss the extension of community detection to multilayer networks, a general framework that allows studies of community structures in networks that change over time and/or have multiple types of links. No prior knowledge about community detection in networks will be assumed for this presentation. This event was co-sponsored by QTM and the Department of Mathematics and Computer Science.

Neural Constraints on Learning
Friday Jan 24, 2014
Talk Abstract. Why are some behaviors easier to learn than others? New behaviors must require new patterns of neural activity. Some new neural activity patterns must be easier to generate than others, but what makes the difference? We use the paradigm of a closed-loop brain-computer interface to encourage animals to exhibit new patterns of neural activity. We find that the extent to which a novel brain-to-behavior mapping can be learned is a function of the current state of the network of neurons controlling behavior. This means that the ease or difficulty with which we can learn new behaviors might be determined by interactions among networks of neurons. This event was co-sponsored by QTM and the Graduate Neuroscience Program in the Graduate Division of Biological and Biomedical Sciences.

Generation of Sequences Through Reconfiguration of Ongoing Activity in Neural Networks: A Model of Choice-Specific Cortical Dynamics in Virtual Navigation
Wednesday Nov 20, 2013
Talk Abstract. Complex timing tasks are the basis for experiments identifying the neural correlates of behaviors like memory-based decision making in brain areas like the posterior parietal cortex (PPC). Recently, cellular-resolution imaging of neural activity in PPC during a virtual memory-guided 2-alternative forced choice task [Harvey, Coen & Tank, 2012] showed that individual neurons had transient activation staggered relative to one another in time, forming a sequence spanning the entire duration of the task. Motivated by these results, our goal here is to develop a computational framework that reconciles the emergence of biologically realistic assemblies or trajectories of activity states, with the ability of the same neural population to translate sensory information into long time-scale behaviors. To this end, we build an echo state network to test our hypothesis that during memory- based decision making, sensory cues set up an initial network state that follows the intrinsic dynamics of the brain area to generate activity underlying a behavioral response. This event was co-hosted by QTM, Emory-Georgia Tech Training Program in Computational Neuroscience (CNTG), and the Department of Physics.

Strategic Interaction and Networks
Tuesday Nov 5, 2013
Talk Abstract. A presentation was about the following paper: this paper brings a general network analysis to a wide class of games, including strategic innovation, public goods, investment, and social interactions. The major interest, and challenge, is seeing how network structure shapes outcomes. We have a striking result. Equilibrium conditions depend on a single number: the lowest eigenvalue of a network matrix. When the graph is sufficiently tight (as measured by this eigenvalue), there is a unique equilibrium. When it is loose, stable equilibria always involve extreme play where some agents take no actions at all. We combine tools from potential games, optimization, and spectral graph theory to solve for all Nash and stable equilibria. This paper is the first to uncover the importance of the lowest eigenvalue to social and economic outcomes, and we relate this measure to different network link patterns. This event was co-sponsored by QTM and the Department of Economics.

Modeling and Forecast of Socio-Technical Systems in the Data-Science Age
Wednesday Oct 16, 2013
Talk Abstract. In recent years the increasing availability of computer power and informatics tools has enabled the gathering of reliable data quantifying the complexity of socio-technical systems. Data-driven computational models have emerged as appropriate tools to tackle the study of contagion and diffusion processes as diverse as epidemic outbreaks, information spreading and Internet packet routing. These models aim at providing a rationale for understanding the emerging tipping points and nonlinear properties that often underpin the most interesting characteristics of socio-technical systems. Here, I review some of the recent progress in modeling contagion and epidemic processes that integrates the complex features of heterogeneities of real-world systems. This event was co-hosted by QTM and the Department of Biostatistics & Bioinformatics.

Challenges in Modeling Malaria Parasite Infection Dynamics and Evolution for Elimination Planning
NO DATE
This event was co-sponsored by QTM and the Department of Biology.

Computing the Shape of Stories: A Macroanalysis
Monday Apr 14, 2014
Talk Abstract. Jockers opened his lecture with an argument about the applicability of quantitative methods to literary studies. He offered his answer to the "so what" question that is frequently asked by humanists who are unaccustomed to thinking about literature as data on the one hand and quantitative evidence on the other. After sketching the broad outlines of how quantitative data might and should be employed in literary studies, Jockers moved to a "proof of concept" derived from his own recent work charting plot structure in 40,000 narratives. In this section, Jockers discussed how he employed tools and techniques from natural language processing, sentiment analysis, signal processing, and machine learning in order to extract and compare the plot structures of novels in a corpus of texts spanning the two hundred year period from 1800-2011. He explored the six core plot archetypes revealed by the technique and how these shapes change from the 19th to the 20th century. He then compared the plot structures of 1,800 contemporary best sellers to the larger corpus in order to suggest that at least one element of market success is related to plot shape. This event was co-sponsored by QTM, the Emory Center for Digital Scholarship (ECDS), and the Department of History.

Beyond Tools: The Shared Questions about Interpretation that Link Computer Science to the Humanities
Wednesday Mar 26, 2014
Talk Abstract. The phrase "digital humanities" suggests an encounter with digital technology itself -- which might involve departments of computer science only indirectly, as creators of tools. But as collaborations between humanists and computer scientists grow more common, it's becoming clear that these disciplines are working in parallel on shared, surprisingly fundamental questions. For instance, computer scientists want to understand how we learn to generalize about latent categories from limited evidence, which is a good part of what humanists do when we "interpret an archive" or "develop a theory." Instead of treating CS as a source of tools, some humanists are starting to approach the discipline as a theoretical interlocutor, analogous to linguistics or anthropology. What might that conversation look like concretely? I'll flesh out some possibilities, briefly describing collaborative research on literary character with David Bamman (CS, Carnegie Mellon), and reflecting more generally on the humanistic value of model-building. I'll also acknowledge some of the social divisions that make this conversation risky. Cohosted by QTM, the Emory Center for Digital Scholarship (ECDS), and the Department of History.

Computational Methods for Chinese History and Humanities
Wednesday Nov 6, 2013
Talk Abstract. The China Historical GIS (covering 221 BCE-1911CE) and the China Biographical Database (300,000 figures mainly from the 7th-early 20th century) provide data for new approaches to China's history. Yet, the methodologies for compiling, organizing, and analyzing this data requires historians to make conceptual leaps from the time-worn and familiar to the profoundly different. This event was co-sponsored by QTM, the Emory Center for Digital Scholarship (ECDS), and the Department of History.

Understanding Heterogeneous Effects of Health Policies Using a Gene-Environment Interaction Framework
Tuesday Jun 4, 2013
Talk Abstract. This talk outlines a research agenda that combines genetic and social science concepts, methodologies, and data to pursue new insights in understanding the impacts of environments and policies on human behavior.  The primary example of this agenda will focus on new results suggesting a gene-environment interaction in responses to tobacco control policies.  Based on variation in a nicotinic receptor gene, I find that some individuals have no behavioral response to tobacco taxation, suggesting a novel gene-policy interaction.  This finding has implications for how we understand the mechanisms of specific health policies and how we might consider introducing new policies to further reduce tobacco consumption.  I also show preliminary evidence of additional gene-environment (policy) interactions with alcohol policies and experiences of economic downturns. The event was co-hosted by QTM and the Department of Economics.

Wednesday Sept 25, 2013
The QTM Institute invited undergraduate students to discover precisely what the new QSS major will offer. Students heard short presentations from people in academia, business, the non-profit sector, and government. Speakers included representatives from Adobe, IBM, the Defense Department, Ernst &emp; Young, Government, the Emory Law School, the Goizueta Business School, and from the departments of Anthropology, Biostatistics, Economics, Political Science, Psychology, and Sociology.

Joe Walker (Senior Consultant, Marketing Analytics, Adobe Software Systems)

Speaker: Felecia Kornegay (Client Manager, IBM)

Speaker: Nicole Miller (Manager, Quantitative Economics & Statistics (QUEST), Ernst & Young)

Speaker: Sue Payne (Professor & Executive Director, Center for Transactional Law and Practice, Emory University)

Speaker: James Rilling (James Rilling, Department of Anthropology, Emory University)

Speaker:Christopher Curran (Associate Professor, Department of Economics, Emory University)

Speaker: Jennifer Gandhi (Associate Professor, Department of Political Science, Emory University)

Speaker: Dana Rickman (Director of Policy & Research, GA Partnership for Excellence in Education)

Thursday Apr 10, 2014
Over the last ten years, we have seen the creation of massive digital text collections, from Twitter feeds to million-book libraries. At the same time, researchers have developed text-mining methods that go beyond simple word frequency analysis to uncover thematic patterns. This workshop introduced participants to topic modeling through hands-on tutorials using the Mallet package and the R statistical language. After a theoretical presentation of the method, we discussed inference and model training, data preparation techniques such as stoplist curation and text segmentation, model analysis techniques in the presence of metadata, and finally, model diagnostics. Led by Dr. David Mimno.

Monday Feb 3, 2014
Qualtrics (emory.qualtrics.com) is an application to collect and analyze survey data. Qualtrics has many advanced features, which make it a more useful and efficient tool than SurveyMonkey and other competitors. This workshop introduced participants to these features. Participants also learned how to integrate Qualtrics with Amazon Mechanical Turk. Led by Chris Martin.

Dec 2-3, 2013
Participants had the opportunity to work with real-world networks from different scenarios and make calculations of the parameters studies, as well as visualize these networks. Led by Dr. Ernesto Estrada.

Wednesday Oct 9, 2013
As computing grows ever more embedded into daily life, computational techniques can now be applied to shed insight on basic social science questions. At the same time, the increasingly social aspect of computing means that technologists must wrestle with and understand social science principles. The emerging cross-disciplinary field of computational social science addresses these challenges and opportunities, combining computational methods applications with social science theory and research.
On November 8, 2013, Emory University and the Georgia Institute of Technology convened an all-day workshop for exchanging research ideas in this exciting new area. The program included distinguished visiting speakers, oral presentations from local researchers, and an interactive poster session. Co-sponsored by QTM, Georgia Tech's GVU Center, and Emory's Mathematics and Computer Science Department.

Wednesday Oct 9, 2013
Mechanical Turk, or MTurk, is a low-cost service provided by Amazon that allows researchers to collect survey data from people around the world. Social, psychological, and health researchers have used MTurk extensively in the past five years to gather survey data or implement simple experiments. In this workshop, participants learned how to efficiently use MTurk in combination with Qualtrics to implement a study. Participants also learned the advantages and drawbacks of Mechanical Turk and what online resources can keep your MTurk knowledge up to date. The workshop included a hands-on implementation of a survey. Led by Chris Martin.

Sept 25-27, 2013
This workshop was about writing effective research proposals. We began with the basics of research design, including units of analysis, measurement, independent and dependent variables, validity, reliability, and cause and effect. We covered sampling (probability and nonprobability sampling) and methods for collecting and analyzing data. Throughout, the focus was on research design - that is: formulating a research question, tying the question to existing knowledge or theory, developing hypotheses, and laying out the methods for testing the hypotheses. The objective was to produce intellectually convincing, fundable research proposals at the Ph.D.-level of study. Led by Dr. Russell Bernard.

Nov 9-10, 2012
This conference was designed to examine the relationship between elections and force from the perspectives of both Comparative Politics and International Relations. It brought together participants working on interrelated questions such as: When political actors can resort to force in pressing their claims, when and why do they participate in elections? When do elections constrain behavior, such that they lead to political order (in the form of peace or self-enforcing democracy)? Do the answers to these questions vary for different political actors: incumbents, the military, political parties, insurgencies, citizens? The event made possible through the generous support of the Halle Institute, the Institute for Quantitative Theory and Methods, and the Institute for Developing Nations.

Paper: Elections under the Shadow of Force

Speaker: Dr. Adam Przeworski (New York University)

Discussant: Dr. James Fearon (Stanford University)

Paper: Circumstances and Reputational Incentives in International Crisis Bargaining

Speaker: Dr. Alexandre Debs (Yale University)

Discussant: Dr. Dan Reiter (Emory University)

Paper: Information and Self-Enforcing Democracy: The Role of International Election Observation

Speaker: Dr. Susan Hyde (Yale University)

Discussant: Dr. John Reuter (University of Rochester)

Paper: Third-Party Institutions and the Success of Democracy

Speaker: Dr. Milan Svolik (University of Illinois Urbana-Champaign)

Discussant: Dr. Jeff Staton (Emory University)

Paper: Defective Democratization: Prior Regimes and Civil Conflict

Speaker: Dr. Burcu Savun (University of Pittsburgh)

Discussant: Dr. Kyle Beardsley (Emory University)

Paper: Autonomous Decisions: Why Do Militant Groups Conduct Simultaneous Electoral and Armed Campaigns, and Why Does the Government Allow It?

Speaker: Dr. Aila Matanock (University of California-Berkeley)

Discussant: Dr. Laia Balcells (Duke University)

Paper: Pocketbook Protests: Explaining the Worldwide Emergence of Pro-democracy Protests

Speaker: Dr. Dawn Brancati (Washington University)

Discussant: Dr. Tom Remington (Emory University)

Fall 2012
The Interdisciplinary Forum on Complex Networks (IFCN) had the mission to generate a platform where scientists from different disciplines and units at Emory University and beyond could join together to discuss and share methodological, theoretical, and practical ideas that concern complex networks. Biological, physical, and social networks represent a point of interdisciplinary convergence because 1) their architectures tend to have similar properties, 2) they face similar challenges, such as questions about diffusion and robustness, and 3) they require the same methodological tools. Convened by: Monica Capra and Edmund Waller.

How to Read a Million Letters
Wednesday Apr 24, 2013
Talk Abstract. The Humanities have entered the age of Big Data. Does this also mean that quantification will make a comeback? Already some scholars are announcing the return of ¿cliometrics.¿ In this talk, I examine the place that quantification can play in humanistic projects, particularly those that rely on messy datasets. While I readily grant that quantification is a useful and even necessary tool in digital humanities, I argue that it must still be supplemented by the qualitative, hermeneutic skills that humanists have honed over time. This event was co-sponsored by QTM and the Department of History.

The Dynamics of Vaccination Sentiments on a Large Online Social Network
Wednesday Apr 10, 2013
Talk Abstract. Modifiable health behaviors, a leading cause of illness and death in many countries, are often driven by individual beliefs and sentiments about health and disease. Individual behaviors affecting health outcomes are increasingly modulated by social networks, for example through the associations of like-minded individuals - homophily - or through peer influence effects. Using a statistical approach to measure the individual temporal effects of a large number of variables pertaining to social network statistics, we investigate the spread of a health sentiment towards a new vaccine on Twitter, a large online social network. We find that the effects of neighborhood size and exposure intensity are qualitatively very different depending on the type of sentiment. Generally, we find that larger numbers of opinionated neighbors inhibit the expression of sentiments. We also find that exposure to negative sentiment is contagious - by which we merely mean predictive of future negative sentiment expression - while exposure to positive sentiments is generally not. In fact, exposure to positive sentiments can even predict increased negative sentiment expression. Our results suggest that the effects of peer influence and social contagion on the dynamics of behavioral spread on social networks are strongly content-dependent. This event was co-sponsored by QTM and the Department of Biology.

Entering the Era of Genomic Medicine: Opportunities and Challenges
Tuesday Mar 19, 2013
Talk Abstract. The Human Genome Project's generation of a reference human genome sequence was a landmark scientific achievement of historic significance. It also signified a critical transition for the field of genomics, as the new foundation of genomic knowledge started to be used in powerful ways by researchers and clinicians to tackle increasingly complex problems in biomedicine. To exploit the opportunities provided by the human genome sequence and to ensure the productive growth of genomics as one of the most vital biomedical disciplines of the 21st century, the National Human Genome Research Institute (NHGRI) is pursuing a broad vision for genomics research beyond the Human Genome Project. This vision includes using genomic data, technologies, and insights to acquire a deeper understanding of genome function and biology as well as to uncover the genetic basis of human disease. Some of the most profound advances are being catalyzed by revolutionary new DNA sequencing technologies; these methods are producing prodigious amounts of DNA sequence data as part of studies aiming to elucidate the complexities of genome function and to unravel the genetic basis of rare and complex diseases. Together, these developments are ushering in the era of genomic medicine. This event was co-sponsored by QTM and the Cherry L. Emerson Center for Scientific Computation.

Wanna Get Away? RD Identification Away From the Cutoff
Friday Mar 8, 2013
Talk Abstract. In the canonical regression discontinuity (RD) design for applicants who face an award or admissions cutoff, causal effects are nonparametrically identified for those near the cutoff. The impact of treatment on inframarginal applicants is also of interest, but identification of such effects requires stronger assumptions than are required for identification at the cutoff. This talk explores RD identification away from the cutoff. Our identification strategy exploits the availability of dependent variable predictors other than the running variable. Conditional on these predictors, the running variable is assumed to be ignorable. This identification strategy is illustrated with data on applicants to Boston exam schools. Functional-form-based extrapolation generates unsatisfying results in this context, either noisy or not very robust. By contrast, identification based on RD-specific conditional independence assumptions produces reasonably precise and surprisingly robust estimates of the effects of exam school attendance on inframarginal applicants. These estimates suggest that the causal effects of exam school attendance for 9th grade applicants with running variable values well away from admissions cutoffs differ little from those for applicants with values that put them on the margin of acceptance. An extension to fuzzy designs is shown to identify causal effects for compliers away from the cutoff. This event was co-sponsored by QTM and the Department of Economics.

Finding Meaning in Big Genomic Data
Wednesday Feb 20, 2013
Talk Abstract. This presentation considered how adding constraints from other levels of analysis can help identify islands of biological meaning within ultra-high-dimensional spaces created by genomic big data. Focusing on “DNA in action”—how genes respond to and influence their molecular ecology—provides a set of common fate and mass action models that focus the analytic search space. Additional constraints imposed by social and ecological systems provide a meta-genomic framework for understanding genomes as a joint product of both their own internal regulatory logic and the constraints and affordances of their environment. Hybridizing abstract models of inter-level constraint with supervised machine learning provides a new approach to “informed search” through big data. This event was co-sponsored by QTM and the Department of Biology.

How Censorship in China Allows Government Criticism but Silences Collective Expression
Friday Feb 1, 2013
Talk Abstract. We offer the first large scale, multiple source analysis of the outcome of what may be the most extensive effort to selectively censor human expression ever implemented. To do this, we have devised a system to locate, download, and analyze the content of millions of social media posts originating from nearly 1,400 different social media services all over China before the Chinese government is able to find, evaluate, and censor (i.e., remove from the Internet) the large subset they deem objectionable. Using modern computer-assisted text analytic methods that we adapt to and validate in the Chinese language, we compare the substantive content of posts censored to those not censored over time in each of 85 topic areas. Contrary to previous understandings, posts with negative, even vitriolic, criticism of the state, its leaders, and its policies are not more likely to be censored. Instead, we show that the censorship program is aimed at curtailing collective action by silencing comments that represent, reinforce, or spur social mobilization, regardless of content. Censorship is oriented toward attempting to forestall collective activities that are occurring now or may occur in the future¿and, as such, seem to clearly expose government intent. This event was co-sponsored by QTM and the Department of Political Science

Public Health in Twitter: What's in there?
Wednesday Nov 14, 2012
Talk Abstract. Twitter and other social media websites contain a wealth of information about populations, and have been used to track sentiment towards products, measure political attitudes, and study social linguistics. In this talk, we investigated the potential for Twitter and social media to impact public health research. Broadly, we explored a range of applications for which social media may hold relevant data, including disease surveillance, public safety, and drug usage patterns. To uncover these trends, we developed new statistical models that can process vast quantities of data and reveal trends and patterns of interest to public health. Our results suggest that social media has broad applicability for public health research. This event was co-sponsored by QTM and the Department of Mathematics & Computer Science.

The Effect of Poor Neonatal Health on Cognitive Development: Evidence from a Large New Population of Twins
Thursday Oct 24, 2012
Talk Abstract. Several recent studies show that poor neonatal health (proxied by low birth weight) has persistent effects into adulthood by reducing both an individual's level of educational attainment as well as adult earnings, but little is known about effects before age 18. This paper makes use of a large new population of twins from Florida to study this question. We find that the effects of poor neonatal health on student outcomes are remarkably invariant. The estimates are virtually identical from third grade through tenth grade. They are the same regardless of whether a student attended a "better" school versus a "worse" school, across racial and ethnic groups, and across maternal education levels. However, the effects grow in magnitude between the start of kindergarten and the end of third grade. These results suggest an important potential role for early childhood and early elementary investments in remediating this persistent condition. This event was co-sponsored by QTM and the Department of Economics.

Language as Influence(d): Power and Memorability
Wednesday Sept 26, 2012
Talk Abstract. We discussed two projects exploring the interplay between language and influence as revealed by computational analysis of large data sets. (1) We show that power differentials among group participants are subtly revealed by how much one individual immediately echoes the linguistic style of the person they are responding to. We considered multiple types of power: status differences (which are relatively static), and dependence (a more "situational" relationship). Using a precise probabilistic formulation of the notion of linguistic coordination, we look at two very different settings: discussions among Wikipedians and arguments before the U.S. Supreme Court. (2) What information achieved widespread public awareness? We consider whether, and how, the way in which the information is phrased¿the choice of words and sentence structure¿can affect information's memorability. We introduce an experimental paradigm that seeks to separate contextual from language effects, using movie quotes as our test case. We find that there are significant differences between memorable and non-memorable quotes in several key dimensions, even after controlling for situational and contextual factors. This event was co-sponsored by QTM, the Department of Mathematics & Computer Science, and the Department of Political Science.

Singing in the Fast Lane: the Neuromechanics of Sound Production in Vocal Vertebrates
Friday Mar 22, 2013
Talk Abstract.Sound is the fastest, most accurate, and information-rich modality for communication in all vertebrates, with human language at the pinnacle of complexity. Just like human infants, songbirds learn their song through imitation learning, mimicking their parents. Songbirds have therefore become an important model system to understand the neural processes and pathologies underlying human speech production and language acquisition. My research aims at unraveling the question How are neural signals translated into sound, operating at the border of neuroscience and biomechanics. As such, neuromechanics integrates both experimental and computational approaches from physics, molecular biology, physiology and neuroscience. We find that sound production systems are pushed to the extremes: tissues violently collide at 100,000 times/sec and extreme performing superfast muscles contract up to 250 times/sec. While focused on songbirds, I use a comparative approach to find unifying principles of motor control and discover new model systems across the vocal vertebrates, from birds to fish, from mice to whales. This event was co-hosted by the Department of Biology.

Apr 18 & 23, 2013
Data visualization is an essential tool for discovery and communication of quantitative information, especially as datasets have grown in size and complexity.  This workshop, offered twice in April 2013, provided a set of ideas, techniques, and best practices for creating effective graphical data presentations using R software (www.r-project.org). Led by Robi Ragan.

Mar 1, 4, & 6, 2013
This was the second series of non-parametric primer workshops offered by QTM in Spring 2013. In this workshop, we studied a unified framework for nonparametric and semiparametric kernel-based analysis with an emphasis on applied modeling. We focused on kernel-based methods capable of handling the mix of categorical (nominal and ordinal) and continuous datatypes one typically encounters in the course of applied data analysis. Applications were emphasized throughout, and we used R for data analysis (www.r-project.org). Led by Jeffrey Racine.

Feb 25 & 27, 2013
In these workshops, we studied a unified framework for nonparametric and semiparametric kernel-based analysis with an emphasis on applied modeling. We focused on kernel-based methods capable of handling the mix of categorical (nominal and ordinal) and continuous datatypes one typically encounters in the course of applied data analysis. Applications were emphasized throughout, and we used R for data analysis (www.r-project.org). Led by Jeffrey Racine.

Friday Nov 16, 2012
In this workshop, we will talk about how to crawl web pages and PDF files from the web, as well as how to extract target information from the crawled raw data using R, Python, and Java. Several examples were given, e.g. data scraping from Twitter and Wikipedia. The workshop began by introducing two crawling methods: crawling based on HTTP request and crawling via web API. After the pages are crawled, we showed several methods of data extraction from the web pages, including table data extraction, regular expression based data extraction, and Xpath based data extraction. Several data scraping examples were demonstrated, including the entire pipeline of scraping data¿from crawling to analysis¿using Twitter and Wikipedia. How to automatically crawl a batch of PDF files from the web and extract the text was also demonstrated. The workshop was sponsored by QTM.  Led by Qiaoling Liu and Yu Wang.