معرفی
Itai Feigenbaum is an Associate Professor in the Department of Computer Science at Lehman College and the Computer Science Program at the Graduate Center, both part of the City University of New York (CUNY) system. His academic career focuses on bridging theoretical computer science with practical applications in economic and social systems.
Dr. Feigenbaum's educational background includes:
- Ph.D. in Operations Research from Columbia University (2016)
- M.Sc. in Operations Research from Columbia University (2012)
- B.Sc. in Mathematics from Rutgers University-New Brunswick (2011), with minors in Computer Science and Operations Research
His research spans multiple interconnected domains at the intersection of computer science, economics, and operations research. Dr. Feigenbaum specializes in algorithmic game theory and mechanism design, developing theoretically sound yet practically applicable solutions to complex allocation problems. His work in causal inference has produced significant contributions to understanding the theoretical foundations of causal discovery algorithms. In combinatorial optimization, he has tackled challenging problems in kidney exchange and school choice systems, creating algorithms that balance efficiency, fairness, and strategic considerations. His recent work increasingly integrates machine learning techniques with traditional optimization approaches, particularly in the causal inference space.
Analysis of Dr. Feigenbaum's publication record reveals a consistent focus on strategic decision-making in constrained environments. His work demonstrates a progression from theoretical foundations in mechanism design to increasingly complex real-world applications, particularly in healthcare (kidney exchange) and education (school choice). The recent emphasis on causal inference represents a natural extension of his expertise in algorithmic decision-making under uncertainty. His publications appear in top venues across computer science, operations research, and economics, reflecting the interdisciplinary nature of his contributions.
Dr. Feigenbaum has established productive collaborations with researchers across multiple institutions, particularly with colleagues at Columbia University (where he completed his PhD under Jay Sethuraman) and various AI research labs. His work on causal inference has involved collaborations with researchers from major tech companies, as evidenced by publications like the Salesforce CausalAI Library framework.
