SICSS-Singapore

July 13 to July 20, 2026 | Singapore

People


Faculty

Image of Subhayan Mukerjee
Subhayan Mukerjee
Subhayan Mukerjee is an Assistant Professor at the Department of Communications and New Media, and a principal investigator at the Centre for Trusted Internet and Community at the National University of Singapore. He researches online audiences using computational methods, and teaches courses in quantitative methods, programming, and data visualization.
Image of Zhicong Chen
Zhicong Chen
Zhicong Chen is a Postdoctoral Fellow at the Department of Communications and New Media at the National University of Singapore. His research bridges digital media, data science, and cultural analysis, leveraging text-as-data methods and large-scale datasets to investigate online safety, information dynamics, and social change.
Image of Cai Mengxuan
Cai Mengxuan
Mengxuan Cai (PhD) is a Research Fellow at the Centre for Trusted Internet Community, National University of Singapore. Her research spans political communication, gender, social media, misinformation and AI.
Image of Rongxin Ouyang
Rongxin Ouyang
Rongxin Ouyang is an PhD student at the Department of Communications and New Media at the National University of Singapore. He researches the societal and political implications of digital media using computational, causal, or quantitative methods; with a particular interest in the inequality and audience engagement of social media.
Image of Xu Dong
Xu Dong
Xu Dong is a PhD Candidate at the School of Journalism and Communication at the Renmin Univerisity of China and visiting student at the Department of Communications and New Media at the National University of Singapore. He researches human-computer interaction and public opinion on social media using computational methods.
Image of Cai Yang
Cai Yang
Cai Yang is a Master by Research student affiliated with the Department of Communications and New Media and the Centre for Trusted Internet and Community at the National University of Singapore. His research interests lie in computational social science, where he studies user behavior and user profiles on social media platforms using large-scale digital data and computational methods. He also develops auditing methods to evaluate platform transparency and compliance.

Speakers

Image of Prasanta Bhattacharya
Prasanta Bhattacharya
Prasanta Bhattacharya is an Innovation Lead and Senior Research Scientist at the Institute of High Performance Computing (IHPC), a flagship interdisciplinary research institute of A*STAR — Singapore’s lead public sector agency for science and technology. He previously also served as Adjunct Assistant Professor at NUS Business School (Department of Analytics and Operations), where he designed and delivered graduate and executive-level courses in AI, business analytics, and network science. His research integrates network science, behavioral analytics, and psychometric modeling to address complex behavioural challenges in emerging markets.
Image of Hannah Clapham
Hannah Clapham
Hannah Clapham is an Assistant Professor at NUS Saw Swee Hock School of Public Health in Singapore. Her research employs mathematical modelling and data analysis to understand transmission and control of infectious diseases. She has a particular interest in arboviruses and sero-epidemiology.
Image of Dilrukshi Gamage
Dilrukshi Gamage
Dr. Dilrukshi Gamage is a Senior Lecturer at the University of Colombo School of Computing, Sri Lanka and a Visiting Research Fellow at the Centre for Protecting Women Online at the Open University UK. Her interdisciplinary research lies at the intersection of Human-Computer Interaction (HCI), Trust & Safety, and Computational Social Science, focusing on how AI-generated content—such as deepfakes—impacts public trust, gendered safety, and digital literacy in the Global South. She was previously a Research Fellow at the Weizenbaum Institute for the Networked Society in Berlin and an Affiliate at the Berkman Klein Center for Internet & Society at Harvard University and a postdoctoral researcher at Institute of Science Tokyo (formally Tokyo Tech). She has led multi-country research and design interventions across South Asia and presented her work at leading venues such as CHI, ICWSM and Trust & Safety Conference. Her work can be found at www.dilrukshigamage.org
Image of D. Sunshine Hillygus
D. Sunshine Hillygus
D. Sunshine Hillygus is Professor of Political Science and Public Policy at Duke University, where she also directs the Social Science Research Institute and co-directs the Duke Polarization Lab. Professor Hillygus has published widely on the topics of public opinion, political communication, survey methodology, and information technology and politics. She is a 2024 Carnegie Fellow, 2025 Insight250 Global Insights Winner, and an Elected Fellow of the Society for Political Methodology. She serves as a PI of the American National Election Study and on AI taskforces for the American Association of Public Opinion Research and the American Political Science Association. She is co-author of Making Young Voters: Converting Civic Attitudes into Civic Action (Cambridge University Press, 2020), The Persuadable Voter: Wedge Issues in Political Campaigns (Princeton University Press, 2008), and The Hard Count: The Social and Political Challenges of the 2000 Census (Russell Sage Foundation, 2006). She holds a Ph.D. in political science from Stanford University and a B.A. and M.A. from the University of Arkansas. From 2003-2009, she taught at Harvard University, where she was the Frederick S. Danziger Associate Professor of Government and founding director of the Program on Survey Research.
Image of Yihong Huang
Yihong Huang
Dr. Yihong Huang is an Assistant Professor at Guanghua School of Management, Peking University, China. She received her PhD from Harvard University in 2024. Her research focuses on Behavioral Economics, Experimental Economics and Political Economy, employing both field and lab experiments. She uses insights from behavioral economics theory to understand real-world phenomena such as misperceived social norms, political discourse, media bias, and inefficient information flow.
Image of Hai Liang
Hai Liang
Dr. Hai Liang is an Associate Professor and the Director of the School of Journalism and Communication at The Chinese University of Hong Kong (CUHK). He also serves as the Co-Director of the Computational Social Science Laboratory at CUHK and is an affiliated member of the Web Mining Laboratory at City University of Hong Kong. His research interests include computational social science, political communication, and digital public health. He has published dozens of journal articles, many appearing in the foremost communication journals, such as Journal of Communication, Communication Research, Human Communication Research, Journal of Computer-Mediated Communication, and New Media & Society. He has also published in public health, information science, political science, sociology, and other interdisciplinary journals. He is currently working on several interdisciplinary projects related to human-AI communication using computational methods and field experiments, decentralized activism on social media, and the consequences of political incivility.
Image of Swapnil Mishra
Swapnil Mishra
Swapnil Mishra is an Assistant Professor at National University of Singapore (NUS), where he is primarily working at intersection of public health, machine learning and Bayesian modelling. He is part of Machine Learning & Global Health Network, which is a multi-country and multi-organisation network focused on doing fundamental research in machine learning and problems related to global health. His research focuses on applying and developing statistical machine learning techniques for the broader and messier world of science and public policy, especially global health. He develops flexible and scalable models for understanding various spatiotemporal data, for example, epidemics (COVID-19, Malaria, HIV) and crime. For his doctorate, he built models for understanding the evolution of popularity in social media. His work focused on algorithms to model point processes with classical machine learning techniques as well as using modern deep learning networks, mainly recurrent networks.

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Participants

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