Simina Branzei

Simina Branzei is an Associate Professor of Computer Science at Purdue University, where she joined in Spring 2018. Her research spans multiple areas at the intersection of theoretical computer science, game theory, and economics, with a focus on developing rigorous theoretical frameworks for understanding complex systems.

Dr. Branzei's research interests include algorithmic game theory, theory of computation, artificial intelligence, algorithms, learning, computational complexity, and their interfaces with dynamical systems and optimization. Specific topics she has worked on include fair division, markets and auctions, games, learning dynamics, and local search processes. Her research is supported by an NSF CAREER Award, a prestigious grant recognizing early-career faculty who demonstrate exceptional potential for leadership in their field.

Analysis of her publication record reveals consistent contributions to understanding computational aspects of economic and social systems. Her work shows particular expertise in computational complexity of fixed point problems, fair allocation mechanisms, market dynamics, and game theoretic models. She has developed novel theoretical frameworks for analyzing cake cutting protocols, market equilibria, and strategic behavior in multi-agent systems.

• NSF CAREER Award
• IBM Ph.D. Fellowship
• Google Anita Borg Memorial Scholarship

Dr. Branzei actively mentors graduate students in theoretical computer science, with current Ph.D. student Reed C. Phillips. Her past mentees include Nicholas J. Recker (Ph.D.) and Nithish Kumar (Master's). She has been instrumental in organizing academic workshops including the ACM EC 2024 Mentoring Workshop, Mini-Symposium on Games and Learning at CanaDAM 2023, and Workshop on Fair Division at FOCS 2022, demonstrating leadership in building research communities.

She teaches graduate courses including Algorithm Design, Theory of Computation, and Algorithmic Game Theory, as well as undergraduate courses in algorithms and theory of computation, shaping the next generation of computer scientists with strong theoretical foundations.