• Professor of Statistics and Computer Science
• Faculty Director of AI at the Data Science Institute
• Courtesy appointment at the Toyota Technological Institute at Chicago
• Recipient of the inaugural SIAM Activity Group on Data Science Career Prize in 2024
• Deputy Director for Research at the NSF-Simons Foundation National Institute for Theory and Mathematics in Biology
• Deputy Director for Research at the NSF-Simons AI Institute for the Sky (SkAI Institute)
• Faculty Director of the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship
• Member of the Executive Committee for the NSF Institute for the Foundations of Data Science.
• Fellow of the Society of Industrial and Applied Mathematics
• Fellow of the IEEE
• Member of the National Academies of Sciences, Engineering, and Medicine Committee on Applied and Theoretical Statistics (CATS)

 

Becca’s research is focused on machine learning foundations, scientific machine learning, and signal processing. Her work in machine learning and signal processing reflects broad and interdisciplinary expertise and perspectives. She is known internationally for her contributions to the mathematical foundations of machine learning, large-scale data science, and computational imaging. Her research focuses on developing the mathematical and statistical foundations of machine learning and scientific machine learning methodology. In addition to her technical contributions, Prof. Willett is a strong advocate for diversity in STEM and AI.

She received the National Science Foundation CAREER Award in 2007, was a DARPA Computer Science Study Group member, and received an Air Force Office of Scientific Research Young Investigator Program award in 2010. She completed her PhD in Electrical and Computer Engineering at Rice University in 2005. She was an Assistant and then tenured Associate Professor of Electrical and Computer Engineering at Duke University from 2005 to 2013. She was an Associate Professor of Electrical and Computer Engineering, Harvey D. Spangler Faculty Scholar, and Fellow of the Wisconsin Institutes for Discovery at the University of Wisconsin-Madison from 2013 to 2018.

Advisory boards and committees:

• National Science Foundation’s Institute for Mathematical and Statistical Innovation, Scientific Advisory Board
• National Science Foundation’s Institute for the Foundations of Machine Learning, External Advisory Board Member
• National Academies of Sciences, Engineering, and Medicine Committee on Testing, Evaluating, and Assessing Artificial Intelligence-Enabled Systems under Operational Conditions for the Department of the Air Force (no longer active)
• National Academies of Sciences, Engineering, and Medicine Committee on Foundational Research Gaps and Future Directions for Digital Twins (no longer active)
• US Department of Energy Office of Science Advanced Scientific Computing Advisory Committee (ASCAC) Sub-committee on “AI for Science” (no longer active)
• Sandia National Laboratories Computing and Information Sciences Laboratory, External Advisory Board (no longer active)
• University of Tokyo Institute for AI and Beyond, International Advisory Board (no longer active)
• Chan Zuckerberg Initiative, Scientific Advisory Board on Imaging (no longer active)

Scientific community leadership roles:

• Inaugural role in SIAM Journal of Mathematics of Data Science
• Inaugural role in Harvard Data Science Review
• Broad experience with leading conferences and workshops for the AI community
• Extensive experience in broadening participation in AI across diverse communities, including through Graduate Research Opportunities for Women (GROW)
• Conference chair or conference technical program chair for multiple large-scale conferences and workshops