معرفی
Siddharth Prasad is a Researcher at the Toyota Technological Institute at Chicago (TTIC), focusing on the intersection of mechanism design, market design, optimization, and machine learning. His work leverages integer programming and operations research to address complex problems in artificial intelligence and economic systems.
- Education: PhD in Computer Science from Carnegie Mellon University, advised by Nina Balcan and Tuomas Sandholm. B.S. in Mathematics and Computer Science from Caltech.
Prasad's research emphasizes revenue-optimal combinatorial auctions, algorithm learnability, and data-driven optimization. He applies techniques like Gomory cuts and branch-and-cut to improve market mechanisms and machine learning systems.
Recent work trends include AI-driven auction design, integer programming advancements, and applications of machine learning in market shrinkage and uncertainty scenarios. His publications span top venues like IJCAI, AAAI, NeurIPS, and CP.
- Scientific Awards: Best poster award (honorable mention) at MIP workshop, 2024.
