Wanheng Hu is a Ph.D. candidate in Science and Technology Studies at Cornell University, where he is also doing a minor in Media Studies. He spent the 2022-23 academic year as a research fellow at the Program of Science, Technology and Society at Harvard Kennedy School. His research lies at the intersection of social studies of science, medicine, and technology; critical data/algorithm studies; and public engagement with science. His dissertation examines the cultivation of credible machine learning (ML) algorithms in expert practices, with an empirical focus on image-based diagnostics within the Chinese medical artificial intelligence (AI) industry. The project draws on ethnographic fieldwork at two Chinese medical AI startups and several hospitals, as well as extensive interviews with multiple stakeholders including medical image annotators, ML engineers, and clinicians. It traces how medical expertise is reimagined and re-enacted in various facets of the medical AI pipeline: from data annotation to algorithmic training, to clinical application, and to regulatory approvals. This work was supported by the National Science Foundation, the China Times Cultural Foundation, and a Hu Shih Fellowship, among others.

Wanheng’s research has been published or is forthcoming in venues such as the Oxford Handbook of the Sociology of Machine Learning and Public Understanding of Science. At Cornell, Wanheng is also a member of the Artificial Intelligence, Policy, and Practice (AIPP) initiative, housed within the Bowers College of Computing and Information Science. Prior to Cornell, Wanheng studied at Peking University, where he obtained an M.Phil. in Philosophy of Science and Technology, a B.L. in Sociology, and a B.Sc. in Biomedical English.