The Vanderbilt Mathematical Programming and Intelligent Robotics (VAMPIR) Lab is dedicated to advancing the frontier of computational game theory, control systems, and trajectory optimization, with mathematical optimization serving as the core of our research. Our work centers on solving complex multilevel programming problems—including MPECs, EPECs, CVaR models, and MDPs—that underlie challenges in dynamic decision-making and planning. By leveraging rigorous tools from mathematical programming, we aim to tackle problems ranging from trajectory planning for autonomous systems and strategic decision making to applications in robotics and medicine.
Led by Forrest Laine, our team includes PhD students Pravesh Koirala, Mel Krusniak, Andrew Cinar, and Yue Zhao, along with a number of talented undergraduates. Together, we have produced impactful contributions in areas like bilevel programming for racing, nonsmooth polyhedral collision detection, algorithmic collusion, and cybersecurity applications of discrete strategy games. What sets our lab apart is a commitment to rigorous mathematical programming approaches, distinguishing our work from more conventional machine learning pipelines.
