People
Faculty
Cantay Caliskan
Cantay Caliskan is an assistant professor of instruction at the Goergen Institute for Data Science, University of Rochester. He studied political science, computer science, and statistics during his PhD, and received his degree from Boston University in 2018. Cantay received his BA in Economics, Mathematics, and Intl. and Global Studies from Brandeis University and his MA in International Relations from Koç University. His research interests include computational social science, specifically computer vision, social media analysis, and generative AI.
Ezgi Siir Kibris
Ezgi Siir Kibris is a Ph.D. candidate in Political Science and an alumna of the MS program in Data Science at the University of Rochester. She has MA degrees in Political Science and European Studies and BA in Economics from Sabanci University. Her dissertation research revolves around judicial politics, international courts, democratic backsliding, and gender. She is interested in quantitative methods, specifically causal inference, machine learning, and natural language processing.Speakers
Agnes Horvat
Agnes Horvat is an Associate Professor of Communication and Computer Science (by courtesy) at Northwestern University. Her research lies at the intersection of human-centered computing, computational social science, and communication. Using interdisciplinary approaches, her research group, the Lab on Innovation, Networks, and Knowledge (LINK), investigates how networks induce biased information production, sharing, and processing on digital platforms. For example, they study the impact of networks and diversity on scholarly communication, identify expressions of collective intelligence and opportunities for innovation in crowdsourcing communities, and develop tools to support creativity and predict success in culture industries. Agnes developed courses on networks, media, and AI to train students for careers at the intersection of creative occupations and data science. Her research and teaching have been recognized with an NSF CAREER and CRII Award. She received her PhD in Physics from the University of Heidelberg, Germany. Prior to becoming a faculty member at Northwestern, she was a postdoctoral fellow at the Northwestern Institute on Complex Systems (NICO).
Dino P. Christenson
Dino Pinterpe Christenson is Professor (Ph.D., Ohio State University; B.A., University of Michigan) in the Department of Political Science at Washington University, a Faculty Affiliate in the Division of Computational and Data Science, and a Research Fellow at the Weidenbaum Center on the Economy, Government, and Public Policy. Christenson studies American political behavior and quantitative methods, with recent work exploring presidential voting behavior, campaign dynamics in presidential primaries and caucuses, the coalition behavior of interest groups, and public opinion and the media environment of institutional outcomes. More generally, his research in American politics concerns electoral behavior, public opinion, political psychology, political communication, interest groups and judicial politics. He has broad methodological interests as well, including survey research, experimental design, longitudinal and nested data models, Bayesian analysis, social network analysis and causal inference.
Bruce Desmarais
Bruce Desmarais is Professor in the Department of Political Science and Faculty Co-Hire of the Institute for Computational and Data Sciences at Penn State University. Professor Desmarais' research focuses on the development and application of statistical methods in the study of Social and Political systems that are characterized by interdependence and structural complexity. Network analysis is the primary methodological approach in his research. Areas of application include international conflict and cooperation among countries, campaign finance and co-sponsorship networks in the US Congress, digital communication networks in local government, diffusion of public policies across the US states, and the interconnectedness of scientific research and US regulatory policymaking. His current research agenda is generously supported by three grants from the US National Science foundation and one from the Russell Sage Foundation.
Bryce J. Dietrich
Bryce Dietrich is Associate Professor in the Department of Political Science at Purdue University and research scholar at the Center for C-SPAN Scholarship and Engagement (CCSE). His research uses novel quantitative, automated, and machine learning methods to analyze non-traditional data sources such as audio (or speech) data and video data. These methods are used to understand the causes and consequences of non-verbal cues, such as vocal inflections and walking trajectories, especially as they relate to elite political behavior.
Gourab Ghoshal
Gourab Ghoshal is Professor of Physics and Astronomy with joint appointments at the departments of Computer Science and Mathematics. He came to Rochester from Harvard University, where he was a Research Scientist at the Department of Earth and Planetary Sciences and a member of multidisciplinary Orgins of Life Initiative. Hailing from New Delhi, India, Professor Ghoshal got his BS and MS degrees at the University of London, UK (BS and MSc in theoretical Physics, 2004). He did his doctoral-thesis work at the University of Michigan, Ann Arbor (PhD in Physics, 2009) during which he attended the prestigious Complex Systems summer school at the Santa Fe Institute, NM and the Theoretical Physics school at Les Houches near Chamonix in France. Following his PhD, he was a postdoctoral scientist jointly at Northeastern University and Harvard Medical School as well as a visiting scientist at the Media Lab, MIT.
Jonathan Herington
Jonathan Herington is Assistant Professor of Philosophy, and Assistant Director of Graduate Education in the College of Arts, Sciences, and Engineering, at the University of Rochester. Between 2014 and 2019 Jonathan was an Assistant Professor in the Department of Philosophy at Kansas State University. Previously Jonathan was a Research Fellow in the Medicine, Ethics, Society and History unit of the University of Birmingham. Jonathan completed my PhD in the School of Philosophy, at the Australian National University. Jonathan is a native of Brisbane, Australia and recieved a BA (Hons I) in International Relations and Philosophy, and a BSc in Microbiology, from the University of Queensland. Prior to undertaking my PhD Jonathan was located at the Centre for International Security Studies, University of Sydney.
Yichen Li
Yichen Li is currently a rising senior at the University of Rochester, where he specializes in Data Science and Business. His research focuses on advanced applications in computer vision, specifically developing methods to analyze political polarization and to measure 3D distances within 2D images. He also has significant experience in leveraging Large Language Models for predicting financial metrics such as stock prices and sales volumes for various companies.
Muchen Zhong
Muchen Zhong is a graduating senior at the University of Rochester, majoring in Data Science and Economics. Soon, she will be joining Brown University for the MS program in Data Science. Her recent research involves developing innovative methodologies in computer vision to quantify political polarization and constructing methods to measure 3D distances in 2D frames. She also has research experience in applying natural language processing and network analysis to explore the impact of AI agents on team dynamics, processes, and outcomes. She is interested in computer vision and financial data science.Teaching Assistants
Participants
Adiba Proma
Adiba Proma is a Computer Science PhD student at the University of Rochester. Her research focuses on modeling human interactions within social networks, particularly exploring the impacts of these interactions in the contexts of climate change and elections. She is also keen on exploring how various technologies, such as Large Language Models (LLMs), recommendation algorithms, and user interface (UI) designs, influence social interactions on online platforms.
Amber Shen
Amber(Yiyang) Shen is a graduating MSW student at Columbia University. Amber's research interests encompass minority mental health, homelessness, poverty, aging, and stigma, with a keen focus on leveraging Artificial Intelligence in mental health interventions. She has gained hands-on research experience at Columbia Population Research Center and the Action Lab for Social Justice, where she spearheaded projects exploring topics ranging from longitudinal studies of community wellbeing to mental health in low-income neighborhoods.
Bibandhan Poudyal
Bibandhan Poudyal is a Physics PhD student at the University of Rochester specializing in complex network analysis, particularly its application to understanding how human mobility impacts urban well-being.
Dihan Shi
Dihan Shi is a PhD student in the Department of Political Science at Washington University in St. Louis. He uses survey experiments and computer vision to study comparative political economy and public opinion. He also studies causal inference problems in survey experimentation and remote sensing. He holds a B.S. degree summa cum laude in Mathematics (Honors) and Political Economy (Honors) from Georgetown University (2022).
Haofeng Ma
Haofeng Ma is a PhD Candidate in Political Science at The University of Iowa. As a comparativist, he is broadly interested in comparative public opinion, language and ethnicity, and political economy. His methodological approaches include spatio-temporal statistics, Bayesian statistics, causal inference, natural language processing, and deep learning. He also utilizes GIS techniques, such as geoprocessing and remote sensing, to enhance data availability, analytics, and visualization. He holds an MS in Informatics from The University of Iowa (2023), a master’s degree in Political Theory from Sun Yat-sen University (2019), and a bachelor’s degree in Politics and Public Administration from Xiangtan University (2017).
Homayra Tabassum
Homayra Tabassum is a graduate student at the University of Rochester, where she is pursuing a master's degree in Data Science. Prior to this, she completed her undergraduate studies in Computer Science and Engineering. Homayra's academic and research interests bridge the domains of Data Science and Social Sciences, with a particular focus on advancing diversity and gender equity within STEM fields.
Jefferson Leal
Jefferson Leal is a PhD student in Political Science at the University of Rochester. Originally from São Paulo, Brazil, he has an MA in Political Science and BA degrees in Economics and International Relations from the University of São Paulo. His research interests include Latin American Politics, populism, polarization, inequality, and democratic backsliding. His methodological interests concern causal inference, machine learning, and natural language processing.
Ke Xu
Ke Xu is pursuing a duel degree in Data Science and Business Analytics from the University of Rochester with interests in applied machine learning, neural networks, and image datas.
Neeley Pate
Neeley is a first year Ph. D. student in the Computer Science department at the University of Rochester. She previously graduated from The University of Texas at Austin with a Bachelors of Science in Electrical and Computer Engineering and a minor in Journalism. Currently, she works with the Rochester Human-Computer Interaction Lab (ROCHCI) with interests in online trust, misinformation and propaganda, and social network construction.
Nour Assili
Nour Assili is an undergraduate Data Science major at the University of Rochester, with a concentration in Economics. She has actively contributed to research projects at the university's Human Computer Interaction Lab. Nour was also a software engineer at early-stage startups, where she built applications at the intersection of tech and social sciences. Her academic and professional interests are centered around Artificial Intelligence, Machine Learning, and Blockchain technologies. Currently, she is exploring how Blockchain could ensure that profit-maximizing corporations do not totally control superintelligence.
Omer Antalyali
Omer Lutfi Antalyali currently holds a position at Suleyman Demirel University as a Professor of Management and Strategy. He is also a Visiting Professor at the University of Rochester's Psychology Department, focusing on a year-long engagement. His primary research project, employee meta-motivation, integrates his interests in leadership, motivation, and advanced statistical analysis. Recently, he has expanded his research scope into the realm of computational social science, embarking on a project aimed at predicting achievement goal orientation through vocal features. His work significantly enhances the intersection of management strategy and technology-driven psychological research, contributing valuable insights to both fields.
Pavithra Priyadarshini Selvakumar
Pavi Selvakumar, is a Ph.D. candidate from the Environmental Science Graduate Program at Oklahoma State University. After completing her Bachelor's in Information Technology at Anna University, India, she went on to earn her Master's in Environmental Assessment and Management at the University of East Anglia, United Kingdom. Her research interests include environmental stewardship, enhancing university campus sustainability, and promoting environmental sustainability through Corporate Social Responsibility (CSR). In the future, Pavi aspires to get into academia, pursuing path-breaking research in the field of environmental sustainability and being a part of an endearing teaching fraternity.
Sayli Shivalkar
Sayli Shivalkar is pursuing a Master's in Data Science at the University of Rochester. She focuses on creating data science systems that solve fundamental issues and generate measurable impacts. Having co-founded a data science startup in the agri-tech space to improve agricultural productivity, she aspires to use data to solve social issues. Her areas of interest are Responsible AI, knowledge graphs, signal processing, and AI Product Management. She has worked on applications of data science in NIR spectroscopy, LLMs, recommendation systems, CPG, knowledge graphs, and venture capital. Her motto is to learn and unlearn effectively with a passion for making data science accessible to everyone.
Suganya Schmura
Suganya Rajendran Schmura is a PhD student in the Department of Linguistics at the University of Rochester. Her research interests include sociolinguistics, Tamil heritage language maintenance and identity, language variation and change, linguistic anthropology, and arts-based ethnography. She is currently investigating a linguistic variable in Tamil that seems to be grammaticalizing, or shifting from a lexical word to a grammatical unit, by employing both quantitative and qualitative methods within a natural language corpus she created. Suganya holds an MS in Applied Linguistics from Texas A&M University-Commerce and a BS in Biological Sciences from Carnegie Mellon University.
Tianhui Wu
Tianhui Wu is a PhD student in the Department of Political Science at The University of Iowa, with a keen interest in comparative public opinion and political behaviors. Her current research focuses on perceived corruption, mass media, and contentious politics, employing both statistical and computational methods. She earned her BA in Political Science and Public Administration from Fudan University and her MA in Political Theory from Sun Yat-sen University.
Wei-Lun Lo
Wei-Lun Lo is a PhD student in Economics at the University of Rochester. His research interests span health, causal inference, and family economics. His research investigates impacts of children’s health on families' decision-making. He is also broadly interested in applying and integrating techniques from analyses of text corpora and geographic patterns to generate new insights into healthcare fraud and abuse. He holds an MA in Economics from the University of Wisconsin-Madison and a BBA in Finance from National Taiwan University.
Yitao Yu
Yitao Yu is a new graduate Data Science student at the University of Rochester. During his undergraduate program, he primarily focused on studying Machine Learning and its various fields of application. He also uses Kaggle in his leisure time, learning to solve different tasks such as recommendation systems, image description, visual localization, time series, and more.