Penn State Penn State: College of the Liberal Arts

Hanna Wallach

Hanna Wallach

Hanna Wallach

Adjunct Associate Professor of Political Science
Hanna Wallach

Professional Bio

Hanna Wallach is a Senior Principal Researcher at Microsoft Research New York City. As a leader in computational social science, Hanna develops machine learning methods for studying the structure, content, and dynamics of social processes using digitized information. Her work is inherently interdisciplinary: she has collaborated with political scientists, sociologists, journalists, and lawyers to understand local government email networks, the US government security classification system, multilateral relations between countries, public policy diffusion networks, and other social processes. To complement this research agenda, Hanna also studies issues of fairness, accountability, transparency, and ethics as they relate to AI and machine learning. The impact of Hanna’s work has been widely recognized. In 2014, she was named one of Glamour magazine’s “35 Women Under 35 Who Are Changing the Tech Industry”; in 2015, she was elected to the International Machine Learning Society’s Board of Trustees; in 2016, she was named co-winner of the CRA-W Borg Early Career Award; in 2018, she served as the program chair for the Neural Information Processing Systems (NeurIPS) conference; and in 2019, she is serving as the general chair for NeurIPS. Hanna is committed to increasing diversity in computing and has worked for over a decade and a half to address the underrepresentation of women, in particular. To that end, she co-founded two projects—the first of their kind—to increase women’s involvement in free and open source software development: Debian Women and the GNOME Women’s Summer Outreach Program (now Outreachy). She also co-founded the annual Women in Machine Learning Workshop, which is now in its fourteenth year. Hanna holds a BA in computer science from the University of Cambridge, an MSc in cognitive science and machine learning from the University of Edinburgh, and a PhD in machine learning from the University of Cambridge.

Areas of Interest

  • Methodology
  • Gender and Politics
  • Public Policy
  • Race, Ethnicity, and Politics