People
Faculty
Zixi Chen
Zixi Chen (陳梓曦) is an Assistant Professor of Practice in Computational Social Science at NYU Shanghai, affiliated with the Center for Applied Social and Economic Research (CASER). She is passionate about fostering interdisciplinary collaboration to address societal challenges through computational methods. Trained as a methodologist, her research integrates text-as-data approaches, social network analysis, and quantitative methods to examine human behavior in technology-mediated education and social contexts. She is also dedicated to developing big-and-rich data frameworks that combines the advantages of digital big data and design-based survey data to advance equity in data-driven social science research. Her work has been published in leading journals such as the American Journal of Education and the Journal of Research on Technology in Education.
Jia Miao
Jia Miao is an Assistant Professor of Sociology at NYU Shanghai. Her research examines the impact of urbanization, urban redevelopment, and neighborhoods on social cohesion, health inequality, and subjective well-being in Asia. She also explores the social consequences of homeownership in major Chinese cities using experimental designs. Additionally, she studies the interplay between family and neighborhood dynamics in shaping the well-being of older adults amid rapid population aging in Chinese societies. Her work has been published in Social Forces, Chinese Sociological Review, Social Science & Medicine, Health & Places, Cities, and other journals.
Yongjun Zhang
Dr. Yongjun Zhang is an Assistant Professor of Sociology and the Institute for Advanced Computational Science at Stony Brook University. He is also affiliated with the Department of Asian and Asian American Studies, the AI Innovation Institute, and the Center for Changing Systems of Power.As a computational social scientist, Dr. Zhang leverages large-scale data, natural language processing, and computer vision to investigate social, political, and organizational behavior, focusing on topics such as racial segregation, political polarization, and organizational inequality.His research has been published in leading journals, including American Journal of Sociology, Demography, Scientific Reports, and Humanities and Social Sciences Communications. He is also the co-editor of Computational Social Science: Applications in China Studies and serves on the editorial boards of several journals, including Nature Scientific Data, Journal of Mathematical Sociology, Socius, Social Science Computer Review, and The Sociological Quarterly.Speakers
Yang Chen
Yang Chen is a Professor within the College of Computer Science and Artificial Intelligence at Fudan University, and leads the Big Data and Networking (DataNET) group at Fudan. From April 2011 to September 2014, he was a postdoctoral associate at the Department of Computer Science, Duke University, USA, where he served as Senior Personnel in the NSF Mobility First project. From September 2009 to April 2011, he has been a research associate and the deputy head of Computer Networks Group, Institute of Computer Science, University of Goettingen, Germany. He received his B.S. and Ph.D. degrees from Department of Electronic Engineering, Tsinghua University in 2004 and 2009, respectively. He visited Stanford University (in 2007) and Microsoft Research Asia (2006-2008) as a visiting student. He was a Nokia Visiting Professor at Aalto University in 2019. His research interests include online social networks, Internet architecture and urban computing. He serves as a Senior Associate Editor of the ACM Transactions on Social Computing, an Associate Editor-in-Chief of the Journal of Social Computing, and an Editorial Board Member of Elsevier Computer Communications. He served as a OC / SPC / PC Member for many international conferences, including SOSP, SIGCOMM, WWW, IMC, IJCAI, AAAI, ECAI, DASFAA, IWQoS, ICCCN, GLOBECOM and ICC. He is a senior member of ACM/IEEE, and a Fellow of the Royal Geographical Society.
Chuncheng Liu
Chuncheng Liu is an Assistant Professor of Communication Studies, jointly appointed in Sociology and Anthropology (CSSH) at Northeastern University. He is a sociologist of knowledge and technology whose research examines the politics of data and classification. He received his Ph.D. in Sociology and Science Studies from the University of California, San Diego, and previously served as a Postdoctoral Researcher at Microsoft Research New England. Liu's current research investigates the politics of sociotechnical systems that surveil, evaluate, and classify citizens. As a leading scholar of China's social credit system, his ongoing book project, under contract with the University of California Press, presents the first ethnographic study of a municipal social credit system that scores citizens based on behavioral indicators. Beyond this book, his broader research explores the organizational politics and public perceptions of contact tracing technologies, generative AI tools, and other data-driven systems of governance. Earlier in his career, Liu studied how public health institutions classify sexual minorities and COVID-19 cases, an interest rooted in his prior work on HIV/AIDS research and intervention. His research has appeared in leading journals including Big Data & Society, Information, Communication & Society, Journal of Contemporary China, Social Science & Medicine, Sociological Forum, and Science, Technology & Human Values. His work has been recognized with awards and grants from the American Sociological Association, the Association for Asian Studies, and the Horowitz Foundation for Social Policy, among others. Liu's insights have also been featured in media outlets such as The Guardian, Bloomberg, and Rest of World.
Guoer Liu
Guoer Liu is an Assistant Professor of Political Science at the University of California San Diego. She is affiliated with UCSD's 21st Century China Center and the Lieberthal-Rogel Center for Chinese Studies at the University of Michigan. She received her Ph.D. in Political Science and Scientific Computing from the University of Michigan in 2024. Her research sits at the intersection of political institutions, technology, and environmental politics, with a primary empirical focus on China. Her book project asks why governments turn to automation when it constrains the very discretion that makes political power useful. She also conducts research in political methodology, with a focus on causal inference and survey experiments.
Hua Shen
Hua Shen is an Assistant Professor of Computer Science at NYU Shanghai, jointly affiliated with New York University. Her research lies at the intersection of Human-Computer Interaction and multiple AI fields, including Natural Language Processing, Speech Processing, and Machine Learning. Particularly, she led a team to initiate research on Bidirectional Human-AI Alignment, aiming to empower humans to interactively explain, evaluate, and collaborate with AI, while incorporating human feedback and values to improve AI systems. She has been selected for the 2026 Google Gemini Academic Program Award, four Shanghai Talent Award programs, and the 2023 Rising Stars of Data Science. Her papers have received multiple honors, including the CHI 2026 Best Paper Honorable Mention Award, EMNLP 2025 Outstanding Paper Award, Best Paper Award at AIED 2024, Best Demo Award at CSCW 2023, Best Paper Honorable Mention at IUI 2023, and a Google Research Science Conference Scholarship (2023). She received her Ph.D. from The Pennsylvania State University and was previously a postdoctoral scholar at the University of Washington and the University of Michigan.
Celine Yunya Song
Prof. Celine Yunya Song is a Full Professor in the Academy of Interdisciplinary Studies and Director of the Media Intelligence Research Center at the Hong Kong University of Science and Technology (HKUST). Her research cuts across global communication, digital media, social media analytics, cyber-psychology and behavior. With an extensive track record in pursuing interdisciplinary research, her scholarship has straddled English, French and Chinese cultures and media. She is a two-time recipient of the prestigious Fulbright award. Her research has been awarded a series of internal and external grants, including from the Humanities and Social Sciences Prestigious Fellowship Scheme, General Research Fund, Quality Education Fund, and Public Policy Research Fund, as well as external grants from Ryerson University, Canada, L'Universite Paris Nanterre, France, FMSH, France and the CONVERGE COVID-19 Working Group Award, USA. She received the HKBU President's Award for Outstanding Young Researchers in 2017 and the HKBU President's Award for Outstanding Performance in Scholarly Work in 2023. She was a visiting associate professor at Cornell University from 2019 to 2020.
Xi Song
Xi Song is a Professor of Sociology and a faculty member of the Asian American Initiative at Columbia University. Prior to joining Columbia, she was the Schiffman Family Presidential Professor of Sociology and a faculty member of the Graduate Group in Demography at the University of Pennsylvania. Her research interests include social mobility, occupations and work, Asian Americans, population studies, and quantitative methodology. Song received the 2021 William Julius Wilson Early Career Award from the American Sociological Association. Her publications received multiple awards from the American Sociological Association (ASA), the International Sociological Association Research Committee on Social Stratification and Mobility (ISA-RC28), the Integrated Public Use Microdata Series (IPUMS), and Demographic Research. She received the Mentor of the Year Award from the Department of Sociology at the University of Pennsylvania in 2022. She has served on the editorial boards of the American Journal of Sociology, Demography, Sociological Methodology, Social Science Research, and Research in Social Stratification and Mobility.
