Recipient of the IEEE Information Theory Society James L. Massey Research and Teaching Award for Young Scholars (2023); IEEE Communications Society & Information Theory Society Joint Paper Award (2023); 2023 IEEE North-American School of Information Theory; Distinguished Lecturer of the IEEE Information Theory Society (2022-2023); Intel’s 2020 Rising Star Faculty Awardee; multiple papers presented at top conferences such as ICML, NEURIPS, COLT, AISTATS; NSF CAREER Award (2019); AFOSR Young Investigator Award (2019).
Research Experience
Post-doctoral researcher and lecturer at the Institute for Machine Learning at ETH Zürich; research fellow at the Simons Institute, UC Berkeley; currently holds multiple appointments at the University of Pennsylvania and collaborates with Google Research.
Education
Ph.D. in Computer and Communication Sciences from EPFL. Post-doctoral scholar and lecturer at the Institute for Machine Learning at ETH Zürich. Research fellow at the Simons Institute, UC Berkeley, program: Foundations of Machine Learning.
Background
Research interests include machine learning, optimization, and data science. He is an associate professor in the Department of Electrical and Systems Engineering at the University of Pennsylvania, with additional appointments in the Department of Computer and Information Science and the Department of Statistics and Data Science at the Wharton School. He is also affiliated with Google Research (NYC) and serves as the Penn site-lead for EnCORE: Institute for Emerging CORE Methods of Data Science, and co-lead of foundations at the AI Institute for Learning-enabled Optimization at Scale (NSF-TILOS).
Miscellany
Invited to give talks at various prestigious universities and workshops, including UT Austin, Chalmers University, MIT, Rutgers University, University of Wisconsin-Madison, and University of Washington Seattle.