Shazeda Ahmed is a DataX Postdoctoral Scholar at UCLA. She has been a researcher at Upturn, the Mercator Institute for China Studies, the Citizen Lab, Stanford University’s Institute for Human-Centered Artificial Intelligence (HAI), and Princeton University’s Center for Information Technology Policy. Her research has investigated how tech firms and the Chinese government are collaborating on the country’s social credit system, the political economy of emotion-recognition and courtroom AI technologies in China, and the epistemic culture of the emerging field of AI safety. Her work has been featured in media outlets including the Financial Times, WIRED, The New York Times, and the BBC.
Noopur Raval is an Assistant Professor in the Department of Information Studies at UCLA. She studies technology-use in global contexts. Prior to academia, she has worked at the Wikimedia Foundation and at Microsoft Research. Her website is www.noopur.cc.
Homa Hosseinmardi is an Assistant Professor of Data Science (DataX) and Computational Communication at UCLA, where she directs the OASIS Lab (Online and AI Systems’ Integrity & Safety). Her research takes a holistic, large-scale approach to understanding sociotechnical systems and information ecosystems, with a focus on safety and trustworthiness.
Angela Fentiman, Ph.D., is the Director of Communications and Creative Services at the UCLA Teaching and Learning Center, where she oversees marketing and communications activities and drives internal and external outreach strategies. With nearly two decades of experience in public relations, executive communications, media relations, crisis communication, community outreach, and governmental relations. Her research focuses on the experiences of women in executive leadership roles. Angela has been an instructor at UCLA Extension for 14 years and has held adjunct professor positions at California Lutheran University and Woodbury University.
Amir Ghasemian is a visiting scholar at UCLA, where his research lies at the intersection of complex systems and computational social science, with a focus on modeling networks and their dynamic behaviors. Drawing on tools from statistical inference, causal inference, and machine learning, he develops principled methods to address challenges of heterogeneity, interdependence, and bias in large-scale data. His work advances tasks such as community detection, link prediction, and the study of social influence dynamics, as well as applications to digital ecosystems. His website is https://aghasemian.github.io/.
Christopher Wegemer is a postdoctoral researcher at UCLA’s Luskin School of Public Affairs and an AI Policy Fellow at the Mila Institute. His current research investigates the effects of adaptive learning technologies on political polarization. He has published more than 30 studies, and his work has informed policy and practice through partnerships with educational and activist organizations. He holds a Ph.D. in education, along with degrees in electrical engineering, applied physics, and global studies. At UCLA, he teaches courses on data science, social networks, and global movements.