People
Faculty
Matthew Salganik
Matthew Salganik is Professor of Sociology at Princeton University, and he is affiliated with several of Princeton's interdisciplinary research centers: the Office of Population Research, the Center for Information Technology Policy, the Center for Health and Wellbeing, and the Center for Statistics and Machine Learning. His research interests include social networks and computational social science. He is the author of the forthcoming book *Bit by Bit: Social Research in the Digital Age.*
Chris Bail
Chris Bail is the Douglas and Ellen Lowey Associate Professor of Sociology and Public Policy at Duke University and a member of the Interdisciplinary Program on Data Science, the Duke Network Analysis Center, and the Duke Population Research Institute. His research examines how non-profit organiations and other political actors shape social media discourse using large text-based datasets and apps for social science research. He is the author of *Terrified: How Anti-Muslim Fringe Organizations Became Mainstream*.Speakers
Deen Freelon
Deen Freelon is an Associate Professor in the School of Media and Journalism at the University of North Carolina at Chapel Hill, and directs the Computational Communication Research Lab.
Kieran Healy
Kieran Healy is Associate Professor of Sociology at Duke University. He's affiliated with the Kenan Institute for Ethics, the Markets and Management Studies program, and the Duke Network Analysis Center.
David Lazer
David Lazer is Professor of Political Science and Computer and Information Science, Northeastern University & Harvard University.
Monica Lee
Monica Lee is a Data Scientist at Facebook who works on Civic Engagement and Election Integrity. Her research leverages social network analysis and machine learning to combat election related social media abuse and to develop tools for civic empowerment.
Kristian Lum
Kristian Lum is the Lead Statistician at the Human Rights Data Analysis Group (HRDAG), where she leads the HRDAG project on criminal justice in the United States.
Sendhil Mullainathan
Sendhil Mullainathan is the Robert C. Waggoner Professor of Economics at Harvard University and the co-founder of the Abdul Latif Jameel Poverty Action Lab.
Duncan Watts
Duncan Watts is a Principal Researcher at Microsoft Research and a founding member of the MSR-NYC lab. He is also an AD White Professor at Large at Cornell University.Teaching Assistants
Taylor Brown
Taylor Brown is a doctoral student in the Duke Sociology department, and is associated with the Duke Network Analysis Center. She has broad interests in computational methods and social media studies. Her dissertation explores gender inequality in creative professions. Taylor holds an MA in sociology from UNC-Chapel Hill and an MSc in evidence-based social intervention from the University of Oxford. Prior to beginning her PhD, Taylor fulfilled an appointment at the National Science Foundation in the division of Social and Economic Sciences.
Haohan Chen
Haohan Chen is a doctoral student in the Duke Political Science Department. He studies the formation and expression of political preferences in authoritarian regimes in the social media era. His current research uses computational models to simulate how people in authoritarian regimes strategically falsify their political preferences with different parts of their social network and how authoritarian regimes respond. He applies a combination of machine learning and causal inference methods to text data from social media sites of China to test empirical implications of his computational models. Prior to graduate school, Haohan earned a BA from the University of Hong Kong.
Marcus Mann
Marcus Mann is a doctoral student in the Duke Sociology department. He uses computational methods to examine politically partisan news ecologies on social media and maintains a general interest in the cultural differentiation of epistemic authorities and their corresponding audiences, communities, and social movements.
Friedolin Merhout
Friedolin Merhout is a doctoral student in the Duke Sociology department. He enjoys exploring how computational methods provide a new lens to view longstanding social science debates, and pondering the potential inherent in the wealth of digital trace data. Before starting the doctoral program at Duke, he earned a BA from Freie Universitaet in his hometown Berlin.
Janet Xu
Janet Xu is a doctoral student in the Princeton Sociology department, where she is also affiliated with the Office of Population Research. Her current research examines perceptions and portrayals of demographic diversity using experimental and computational methods. She holds a B.A. from the University of Chicago. Prior to graduate school, Janet worked at the National Opinion Research Center (NORC) as a survey researcher.Participants
Emily Bello-Pardo
Emily D. Bello-Pardo is a doctoral student at American University. Her work examines the attitudinal impacts of online dis- and mis- information, online discursive incivility, and public policy shifts, and uses experimental and computational social science approaches to explore these topics in the US and Latin America. In 2017, Bello-Pardo was a Google NewsLab Fellow at Pew Research Center. Before her PhD, Bello-Pardo obtained a MA in Latin American and Caribbean Studies and dual Bachelor degrees in Political Science and International Relations from Florida International University.
Nicolò Cavalli
Nicolò is a DPhil candidate in Sociology at Nuffield College, University of Oxford. He holds a BA in Politics from University of Bologna and a MSc in Economics from Bocconi University, Milan. Before joining Nuffield College, Nicolò worked as journalist, reporting on social issues and political movements from Italy, Greece, Catalunya, California and Peru. His Doctoral Thesis focuses on how intergroup emotional stratification emerged in Europe in times of economic recession.
Lily Fesler
Lily Fesler is a doctoral student in economics of education at the Stanford Graduate School of Education and an Institute of Education Sciences (IES) fellow. Her research interests include student and teacher bias in higher education and barriers to college access. Methodologically, she is very interested in using text analysis to better understand student's college experiences (and started the Stanford student-led group Computational Text Analysis in the Social Sciences). Before coming to Stanford, Lily worked as an education analyst at Abt Associates and as an analyst at an economic consulting firm in Boston. She received her bachelor's degree from Wesleyan University.
Natalie Gallagher
Natalie Gallagher is currently pursuing a PhD in psychology at Northwestern University. Her work lies at the intersection of social and cognitive research, including network cognition, social categories, and a flexible sense of self. She draws on psychological, sociological, and computational methods to pursue her questions, and is interested in how research can inform social change. Natalie received her BA in psychology and theater from Georgetown University.
Ryan J. Gallagher
Ryan J. Gallagher is a PhD student at Northeastern University. At the Network Science Institute, he researches the dynamics of social networks using tools and theory from natural language processing and communications. He currently studies the affective phenomena of networked counterpublics. Ryan holds an MS in mathematics from the University of Vermont, where he worked with the Computational Story Lab at the Vermont Complex Systems Center, and a BA in math from the University of Connecticut.
Douglas Guilbeault
Douglas Guilbeault is a PhD candidate in the Network Dynamics Group at the University of Pennsylvania. His research uses formal models and online experiments to study political communication and cultural evolution. His recent work focuses on the effects of political polarization on collective intelligence. Doug is funded by a PhD scholarship from the Social Sciences and Humanities Research Council of Canada, as well as by a dissertation fellowship from the Institute for Research on Innovation and Science. He has a background in philosophy, linguistics, and cognitive science.
David Hagmann
David is a PhD candidate in Decision Sciences at Carnegie Mellon University and a visiting scholar at the Wharton School at the University of Pennsylvania. His interests include information avoidance, behavioral interventions (nudges), and decisions from experience. In his dissertation, David studies persuasion in the presence of motivated reasoning. While we might think that changing someone’s mind is all about exposing them to facts that support our views and challenge theirs, such an approach may be more likely to engender defensive information avoidance rather than receptive information processing.
Katherine Hoffmann Pham
Katherine Hoffmann Pham is a PhD candidate in Information Systems at the NYU Stern School of Business. Her research focuses on applications of big data to international development and policy problems; her current projects study transportation mode choice in New York City and migration patterns in the Central Mediterranean. She is also interested in how machine learning can be applied to causal inference. Previously, she worked on randomized controlled trials with Innovations for Poverty Action and completed a co-terminal degree in International Relations, Economics, and International Policy Studies at Stanford.
David Holtz
David Holtz is a PhD student in the Information Technology group at MIT Sloan. His research interests span online marketplace design, causal inference, applied machine learning, and network science. His work thus far has focused on ratings and reviews, as well as the viability of reputation systems that don’t depend on user generated feedback. He holds an MA in Physics & Astronomy from Johns Hopkins University and a BA in Physics from Princeton University. Prior to beginning his PhD, David was a data scientist (most recently at Airbnb).
Eaman Jahani
Eaman Jahani is a graduate research assistant pursuing a PhD degree in Social and Engineering Systems with a minor in Statistics at MIT IDSS. Prior to MIT, he was a software engineer at Google for 4 years. His main training is in statistics and computer science, but recently he has been appreciating econometrics and modeling in applied economics. His past research examined the extent of bubbles vs truth-seeking in cryptocurrency markets and socio-economic prediction in social networks. His current research focuses on structural factors such as networks or institutions that regenerate inequality at a micro scale. Eaman spends too much time reading political commentaries.
Carly Knight
Carly Knight is completing her PhD in Sociology at Harvard University. Her work applies quantitative and computational methods to questions of historical and cultural change. Her primary research interest concerns the evolution of attitudes towards the market and the development of organizational market actors. She is also broadly interested in political sociology, law and regulation, markets and moral classification, and computational analysis. In the Fall, she will begin as an Assistant Professor at New York University.
Elena Labzina
Elena is a graduating Ph.D. student in PolSci at WashU in St Louis. Soon, she is joining the Lab of Law&Economics at ETH Zurich as a postdoc in PolSci, Econ, and Data Analysis. Also, she holds MAs in PolSci, Econ, and Stats. Her BSc is in Applied Math and CompSci from Lomonosov State in Moscow, Russia. Elena’s research concerns the interdisciplinary studies that apply advanced data methods to questions related to information security, media freedom, development, and environmental issues.
Tina Law
Tina Law is a Ph.D. student in sociology at Yale. Her research explores how big data and computational social science can be used to advance the study of racial inequality in U.S. cities and neighborhoods. She is particularly interested in applying and integrating techniques from analyses of social networks, text corpora, and emotions in order to generate new insights into longstanding issues of urban racial inequality. Her ongoing work is supported by the National Science Foundation’s Graduate Research Fellowship Program. She will be continuing her studies at Northwestern in fall 2018.
Yan Leng
Yan is currently pursuing a Ph.D. at Human Dynamics group at MIT. She received dual masters in Computer Science and Transportation Engineering from MIT in 2016. Yan is interested in using a broad range of computational techniques to understand the network effect of social influence. In particular, she works on the inference, identification, and modeling of social influence and social learning with large-scale behavioral data in a networked environment. Besides, she also works on the combining network structure and personal attributes in maximizing cascading payoff.
Jeff Lockhart
Jeff Lockhart is a PhD candidate in sociology at the University of Michigan. Before coming to Michigan, he completed a masters in computer science at Fordham University and a masters in gender studies at the University of Cambridge. His research seeks to integrate computational tools with critical insight from feminist and queer theory.
Julien Migozzi
Julien Migozzi is a PhD Candidate in Urban & Economic Geography at the University of Grenoble Alpes and a Lecturer & Research Assistant at the Ecole Normale Supérieure de Paris. His research investigates how the real estate market reshapes patterns of social stratification and neighborhood change in emerging cities of the Global South, with a specific focus on Cape Town, South Africa. He is particularly interested in the intersection of housing market, financialization and inequalities. His methodology combines in-depth, qualitative fieldwork with spatial analysis, multivariate statistics & mapping. He received his B.A and his M.A in Geography from the Ecole Normale Supérieure de Lyon.
Sanaz Mobasseri
Sanaz Mobasseri is an Assistant Professor of Organizational Behavior at Boston University’s Questrom School of Business. She received her PhD from the Management of Organizations Department at UC Berkeley's Haas School of Business. Her research examines the role of emotion, cognition, and culture in shaping social networks and labor market outcomes. Much of her work is situated in organizational settings, where she examine the microfoundations of workplace inequality. Although grounded in sociology and organizational theory, her work integrates theoretical insights from social psychology and sociolinguistics. Her research methods are similarly diverse, ranging from experimental studies in the lab to audit studies in the field to computational approaches applied to large archival data sets.
Hussein Mohsen
Hussein is a PhD student in Computational Biology & Bioinformatics at Yale University supported by the Nicholas Jabr and Gruber Science Fellowships. His research interests are at the confluence of deep learning, cancer genomics, and computational social science. He received a BS in Computer Science from the Lebanese American University (LAU) and an MS in Bioinformatics at Indiana University.
Zanele Munyikwa
Zanele Munyikwa is a PhD student in Information Technologies at the MIT Sloan School of Management. She studies the role of networks, platforms, and people in the rapidly changing digital economy. Zanele's current research focuses on the future of work and the economics of social networks. She holds a Bachelors degree in Computer Science from Duke University, and spent two years as a Research Fellow at Stanford Graduate School of Business.
Trang (Mae) Nguyen
Trang (Mae) Nguyen (Nguyễn Thu Trang) is the John N. Hazard Fellow in Comparative Law at New York University School of Law, U.S.-Asia Law Institute, and visiting scholar at University of California Berkeley School of Law. Her research uses mixed methods analysis to study authoritarian legality. Mae earned a J.D. degree from NYU School of Law, where she was a Mitchell Jacobson Law & Leadership Fellow and executive editor of the New York University Law Review.
Stan Oklobdzija
Stan Oklobdzija is a PhD Candidate in the Department of Political Science at UC San Diego. His dissertation project focuses on how changes to US election law allowed networks of interest groups to take over roles previously held by political parties. His research interests revolve around campaign finance, election law and state politics. Prior to graduate school, he worked as a reporter at the Sacramento Bee.
Anne Helby Petersen
Anne Petersen is a research assistant at the Section of Biostatistics, Copenhagen University, Denmark. She has a MSc in statistics, a BSc in mathematics and a keen interest in sociology. She is the primary developer of two R-packages on CRAN, dataMaid and PCADSC. Her research interests are focused on the methodological challenges related to modeling observational data and in particular how this type of information can be used to understand the interplay between social inequality and health.
Iacopo Pozzana
Iacopo holds a masters in physics from the University of Pisa and is currently pursuing a PhD in computer science at Birkbeck, University of London. In his research, he uses tools from network science, machine learning and natural language processing to study human behaviour on social media, currently focusing on platforms granting an high degree of anonymity to their users. Previously, he has worked on social bot detection and on temporal network modelling.
Francesco Rampazzo
Francesco is pursuing a PhD in Social Statistics and Demography at the University of Southampton, while being a Doctoral Fellow at the Max Planck Institute of Demographic Research. He holds a Master’s degree in Demography from Stockholm University, and a Bachelor’s degree in Statistics from the University of Padova. Having moved around Europe for his university education, he understands how important it is to complement traditional data sources on migrants, with digital data sources for capturing the actual movements of individuals. His PhD focuses on the use of digital data for describing demographic events, such as European migration, male fertility, and patterns of transition to adulthood.
Leah Rosenzweig
Leah just completed her PhD in political science at MIT, where she was a member of MIT GOV/LAB and the Political Methodology Lab. Her research focuses on citizens’ political behavior in developing countries. Her current book project investigates the puzzle of why citizens vote in elections with foregone conclusions. Using survey and experimental methods, she analyzes the role that social norms play in motivating turnout among citizens in semi-authoritarian states. Leah will be joining the Institute for Advanced Study in Toulouse, France as a postdoctoral research fellow in the fall.
Martijn Schoonvelde
Martijn Schoonvelde is a postdoctoral fellow in Political Science at the Vrije Universiteit in Amsterdam where he uses automated text analysis to study on leader communication in the European Union during times of crisis. Before this, he was a Max Weber Fellow at the European University Institute in Florence, and a research fellow at the University of Exeter in the UK. He received his PhD from Stony Brook University. His interests include comparative political behavior, EU politics and research methods. He tweets under @hjms.
Carsten Schwemmer
Carsten Schwemmer is currently pursuing a PhD in Sociology at Bamberg University, Germany. His research focuses on computational methods for the study of ethnic minorities and social media communication. Carsten is particularly interested in natural language processing, data mining and software development. He also teaches computational social science at Bamberg University and Humboldt University of Berlin.