Current AQM Students

Jiebiao Wang

Jiebiao Wang is a Ph.D. student at the Crown Family School of Social Work, Policy, and Practice. Previously, he worked in the School of Public Policy & Management at Tsinghua University as a research assistant. His research interests center on the well-being of people with intellectual and developmental disabilities (IDD), health policy, advanced quantitative methods, and machine learning. Besides, he is interested in computational text analysis using Twitter APIs to collect the corpus and analyze large-scale administrative datasets utilizing machine learning algorithms.

He is from Inner Mongolia, China. He received his MSW at Washington University in St. Louis and a Bachelor from the University of Science and Technology Beijing.

 

Hyunku Kwon

Hyunku Kwon is a PhD student in sociology. He specializes in political and historical sociology, with a focus on American political history, the state and the market, social networks, and political beliefs. He is particularly interested in the relationship between social structures and political beliefs (especially those pertaining to nativism, populism, and racism). His current work uses statistical, archival, and computational methods to study (1) the subjective representations of political polarization, (2) how ethnic networks both enabled and limited radicalism in Chicago in the late nineteenth century, and (3) deep learning approach to political ideology. He is also a member of two research groups at the University of Chicago: the Culture and Action Network and Knowledge Lab.

Ziwei Zhang

Ziwei Zhang joined the PhD program in Psychology in 2020 to study with Prof. Monica Rosenberg. Her interests include cognitive science, brain imaging, mechanisms of human learning, and mechanisms of human attention with main research interest focusing on the underlying mechanisms of human cognition. Ziwei deals with high-dimensional brain imaging data, and wants to combine computational modeling with brain imaging to better understand how the brain works to carry out different cognitive functions. She believes that she will benefit from theoretical understanding of statistics and more application beyond her own department/field and hopes to apply fundamentals learned from AQM courses to her research.

 

Andrew Frangos

Andrew is a Ph.D. student in the Crown Family School of Social Work, Policy, and Practice. Previously, they worked in the Los Angeles Unified School District as a high school math and engineering teacher, intervention coordinator, and instructional coach. Andrew is interested in critically assessing how racism and linguistic marginalization are operationalized and resisted in urban school systems and the communities they seek to serve, particularly through sociotechnical systems like school ratings, attendance boundaries, and school choice. When it comes to quantitative methods, Andrew is interested in system dynamics modeling, causal inference, and QuantCrit approaches. Andrew received a B.S. in Systems Science and Engineering at Washington University in St. Louis and an M.A. in Education from Claremont Graduate University with the support of Math for America Los Angeles.

 

Henry Jones

Henry Jones joined the PhD program in Psychology in 2022, working with Prof. Ed Awh. He is interested in the cognitive and neural mechanisms that underlie adaptive behavior. His current research focuses on how people can maintain attention in concert with other information to support flexible action. He is interested in the format and dynamics of these representations – how quickly they are formed, how much information is stored, and how robust to interference they are. The work relies on high-dimensional brain imaging data from multiple acquisition methods, like fMRI and EEG, with structure in space and time. He believes that the AQM courses will provide a general framework that can enable applying the most powerful statistical method for each data type and question in his research.

 

Jessica Li

Jessica is a Finance PhD student at the University of Chicago Booth School of Business. Her research interests lie broadly at the intersection of asset pricing and corporate finance, with a focus on financial intermediation, corporate debt and contracting, market structure, and implications of financial frictions. Currently, her work is focused on debt contracts and creditor governance, over-the-counter markets, and dynamic asset pricing.

 

 

Yiang Li

Yiang Li is a Ph.D. student in Sociology at the University of Chicago. His research broadly focuses on: Social Demography, Health, Family, Aging and the Life Course, and Statistical Methods. His primary research motivation is to use statistical and/or computational techniques to 1) improve the understanding of how social conditions affect health outcomes, 2) examine the early-life contextual drivers that shape and perpetuate health inequalities over the life course, especially the potential synergistic effects and interactions between family dynamics and neighborhood context and 3) uncover the underlying social mechanisms behind stratified life trajectories, such as gendered body shape standards, network homophiles, and assortative mating, that contribute to the intricate tapestry of health and social stratification 4) utilizing comparative approach to study variegated social processes along the life course led to diverging population health trajectories. Yiang received his MA in Computational Social Science from the University of Chicago in 2024 and First-Class BSc (Hons) in Social Sciences with Quantitative Methods from University College London (UCL) in 2022.

 

Aaron Stagoff-Belfort

Aaron Stagoff-Belfort is a sociology Ph.D. student at the University of Chicago. He is a Research Assistant for the UChicago Justice Project and an Urban Doctoral Fellow at the Mansueto Institute for Urban Innovation. His research interests lie at the intersection of policing and the criminal legal system, urban sociology, and race-class inequality. He uses mixed methods, including statistical tools and causal inference, as well as social network analysis, to advance two related research agendas. The first investigates how policing might effect socioeconomic wellbeing and health, particularly the role policing plays in producing inequality and stratification. The second explores approaches to building safer neighborhoods without relying on punitive social control mechanisms. Both bodies of work consider the role of community and state institutions in providing security and how institutions outside of the legal system can build social cohesion and enhance community safety. Prior to coming to the University of Chicago, he worked as a Program Associate in the Redefining Public Safety Program at the Vera Institute of Justice in New York City. He received a Bachelor of Arts in the College of Social Studies at Wesleyan University.

 

 

Jesse Zhou

Jesse is a PhD student in Sociology and a graduate fellow at the Stone Center for Research on Wealth Inequality and Mobility. His research interests lie in social inequality and mobility, economic sociology, and causal inference methods. Substantively, Jesse is fascinated by how globalization and technological changes are reshaping social inequality and the role of skills in this transformation. Methodologically, he is particularly interested in exploring causal mediation analysis and integrating machine learning frameworks into causal inference.