Yevgeniy Vorobeychik

Vanderbilt University, Washington University in St. Louis

Papers

Total Citations

159

H-Index

About

Yevgeniy Vorobeychik is a leading researcher at the intersection of artificial intelligence, robotics, and optimization, with a particular focus on creating systems that are both intelligent and robust. His work spans submodular optimization, adversarial machine learning, and temporal logic planning, where he develops algorithms that can reason about complex, real-world constraints and security threats. One of his most influential contributions is in "Submodular Optimization with Routing Constraints" (2016, 149 citations), which addresses the critical gap between theoretical optimization and practical deployment by incorporating realistic travel costs into sensor placement and task allocation problems. This work has had a significant impact on fields ranging from environmental monitoring to robotics. More recently, Vorobeychik has pioneered the integration of large language models with formal methods, as seen in his work on "Conformal Temporal Logic Planning using Large Language Models" (2023), which enables robots to interpret natural language instructions and generate provably safe plans. He also explores adversarial perspectives on task assignment, ensuring that multi-agent systems remain resilient under attack. Through his research, Vorobeychik continues to bridge the gap between theoretical guarantees and practical, secure, and intelligent autonomous systems.