The QMSS program gives students access to some of the most accomplished scholars at Columbia University. Working with a broad range of faculty members on theses and other research projects provides our students with the intellectual and material resources they need to accomplish their educational goals. Listed below are the faculty currently teaching in the QMSS program, but students also work with a wide range of faculty across the university.
Dr. Gelman is the founder of the QMSS program. He still maintains close ties with QMSS faculty, projects and students. He is currently a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. He has received the Outstanding Statistical Application award from the American Statistical Association, the award for best article published in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40. His books include Bayesian Data Analysis (with John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin), Teaching Statistics: A Bag of Tricks (with Deb Nolan), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Jennifer Hill), Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (with David Park, Boris Shor, and Jeronimo Cortina), and A Quantitative Tour of the Social Sciences (co-edited with Jeronimo Cortina).
Dr. Connelly , works in international and global history. He received his B.A. from Columbia (1990) and his Ph.D. from Yale ( 1997). His publications include A Diplomatic Revolution: Algeria's Fight for Independence and the Origins of the Post-Cold War Era (2002), and Fatal Misconception: The Struggle to Control World Population (2008). He has written research articles in Comparative Studies in Society and History, The International Journal of Middle East Studies, The American Historical Review, The Review francaise d'histoire d'Outre-mer, and Past & Present. He has also published commentary on international affairs in The Atlantic Monthly and The National Interest.
Program Directors and Staff
Gregory M. Eirich
Dr. Eirich is the Director of the Quantitative Methods in the Social Sciences (QMSS) MA Program and is appointed Lecturer-in-Discipline within the Department of Sociology. His course offerings include Data Analysis, Advanced Analytic Techniques, Research Seminar, Time Series, and Social Network Analysis with QMSS. He researches the causes and consequences of socioeconomic inequality, with a particular focus on family processes. He has studied “rich-get-richer” dynamics in the CEO labor market and the cumulative academic consequences of reading ability groups in the early education. His dissertation examined the relationship between parental religiosity and children's educational attainment in the United States. He has many on-going projects in collaboration with MA and Ph.D. students. His work has appeared in the American Journal of Sociology (with Thomas Diprete and Matthew Pittinsky), Annual Review of Sociology (with Thomas DiPrete), International Journal of the Sociology of the Family, Research in the Sociology of Work, in Adolescence in the 21st Century: Constants and Challenges (eds, Frances R. Spielhagen, Paul D. Schwartz; Information Age Publishing), and most recently, in the Journal of Family Issues. He has a BA in Classical Languages and Philosophy from Fordham University and his Ph.D. is from Columbia in Sociology. Prior to teaching, Greg was a senior consultant conducting health care research at The Advisory Board Company in Washington, DC. He can be reached via email.
Elena Krumova is the Assistant Director of the QMSS Program. She holds a PhD in Sociology from Columbia University and has several years of experience teaching at the undergraduate and graduate levels. Previously, she has been a Visiting Assistant Professor at the School of Public Policy at Central European University, Budapest and a Post-doctoral fellow at the Harriman Institute at Columbia University. Elena has a lot of experience advising students and over the last decade, she has helped scores of students conceive of and complete complex research projects.
Meghan is the Program Coordinator for QMSS. She studied Theatre and Environmental Policy at Northwestern University where she subsequently worked as a Research Coordinator for the Science of Networks in Communities Research Group. She has been with the QMSS program since 2016 and is responsible for coordinating all academic operations and enrichment activities. Beyond QMSS, she is involved with a number education outreach organizations within New York City. She is the primary contact for the program and can be reached by phone at (212) 851-7531 or email at firstname.lastname@example.org.
Dr. Parrott is appointed Lecturer-in-Discipline with QMSS and the Political Science Department. He is the founding director of Columbia’s AI Model Share initiative. He teaches Machine Learning, Data Mining, GIS and Spatial Analysis, and Data Visualization with QMSS. Prior to joining the QMSS faculty, he was a 2016-2017 American Political Science Association Congressional Fellow. As an APSA fellow he designed web-applications to organize, centralize, and automate data collection and everyday tasks for committee and personal office staff. Before that he was a senior research analyst with a focus on GIS and spatial statistical analysis for the Campaign Finance Institute, a nonpartisan NPO in Washington, DC. He holds a PhD in Political Science with a focus on American politics and research methodology from the University of Maryland, an MA in Political Science from Fordham University, and a BA in Philosophy, Psychology, and Political Science from the University of Texas. His research interests include American governing institutions (especially Congress), interest groups, money and politics, and quantitative methodology. His current research examines how the design of political institutions shapes who wins and who loses in the policymaking process.
Dr. Morales has taught Applied Data Science for Social Scientists and Theory and Methodology at QMSS since 2016. He is currently in residence as Visiting Faculty during the Academic Year 2021-2022. During this time, he will continue his work on identifying the conditions that ensure success and adoption of Data Science in corporate environments. Dr. Morales brings an incredible wealth of behavioral science knowledge and executive experience leading Data Science organizations in the media and entertainment industry, most recently at Warner Music Group and NBCUniversal. Throughout his career in Data Science, he has led teams of data scientists and data engineers to build automated platforms and data products tailored to the media space. He received his PhD in Political Science from New York University His current research interests include applications of Machine Learning for Inference, Experimentation and Causal Inference, and the formalization of the differences between inference and prediction.
Dr. Goodrich is a core instructor of QMSS and teaches Missing Data, Bayesian Statistics, Data Mining, Data Analysis, and Theory and Methodology at QMSS. Previously, he was a Post-doctoral Researcher working with Andrew Gelman at the Applied Statistics Center at Columbia University (primarily on the mi R package for missing Data). He received his PhD in Government and Social Policy from Harvard University in 2010 where his dissertation, It’s Not All About the Benjamins: Political Economy and Social-Psychology Theories of Welfare State Preferences, derived two new estimators and applies them to cross-country survey data to test competing theories of preferences for redistribution and other welfare state programs. He previously served as a research assistant at the Peterson Institute for international Economics. His research interests include methodology, comparative politics and political economy.
Born and raised in the Bronx in New York City, Aracelis Torres understood early on that all health care is not created equal. This realization fueled her desire to pursue a path to address the issue of health disparities. After completing her undergraduate studies at Yale University, Torres' work in a New York City community health center solidified her decision to apply her skills toward a career in public health. She obtained her MPH from the Yale School of Public Health with a concentration in Chronic Disease Epidemiology. Torres' work there focused primarily on the disparities in utilization of mammography screening within the Hispanic-Latino community. Torres was a doctoral student at the Bloomberg School within the Cancer Epidemiology concentration. There, she has analyzed the effectiveness of patient navigation on improving breast cancer screening among black Medicare beneficiaries from Baltimore City. She has worked toward integrating this information with geographic data to determine whether the success of the patient navigation program varies by how far individuals reside from health services. She also spent time working closely with the Chief of Epidemiologic Services at the Baltimore City Health Department to create a youth violence report for the city's Violent Crime Reduction Enhancement Initiative.
Dr. Yang is an Adjunct Assistant Professor within the Department of Political Science and she teaches the Quantitative Theory and Methods course on behalf of the QMSS program. She is a Senior Manager at Pfizer Inc., where she and her team develop global strategic plans and projects, using health economic and outcome research (HEOR) methodology and real-world evidence (RWE), that support the value proposition, marketing, and market access for Pfizer oncology portfolio. She works with cross-functional teams to diagnose, strategize, and illuminate a product’s benefit-risk and economic profile tailored to a myriad of market stakeholders to promote healthcare system performance in an increasingly value-based environment. She has extensive experience in conducting complex study design, performing advanced data analysis using big data such as health claims datasets, to understand patients’ health seeking behaviors and barriers to care. Dr. Yang has authored over 80 abstracts and original research articles on high-impact journals in a variety of therapeutic areas. Dr. Yang received a Master of Health Science degree in epidemiology from the Johns Hopkins Bloomberg School of Public Health and a Doctor of Public Health degree in Epidemiology from the Mailman School of Public Health at Columbia University.
Dr. Houlihan is Senior Vice President of Decisioning for Publicis Groupe where he is responsible for building out complex machine learning frameworks and managing a team of the worlds best Data Scientists. Previously, he founded, architect-ed and deployed a financial data analytics company, SentiQuant, and spent fifteen years in high technology roles, where he designed semiconductors into a variety of complex systems. Houlihan earned his doctorate in Financial Engineering from Stevens Institute of Technology where his research focus was sentiment analysis through natural language processing and machine learning techniques. He also holds both a BSEE and MBA from Drexel University. His work has appeared in Quantitative Finance, Computational Economics, and the Journal of Investing.
Dr. Riemann is the Analytics Manager in the Elections Unit at NBC News. In this role, he supports the development of applications used for election-night projections and helps produce election-related content and polling data in support of the NBC News family and digital properties. Prior to NBC, Charlie was a Vice President in the Innovation practice at the Nielsen Company and Research Director at the Harris Poll, one of the longest running surveys in the U.S. tracking public opinion, motivations and social sentiment. He earned his Ph.D. in Political Science from Columbia University and has served as an Adjunct Professor at the University of Connecticut, Columbia University’s School of International and Public Affairs, and at Fordham University’s Graduate Program in Elections and Campaign Management.