Maxim Bichuch

Maxim Bichuch is an Assistant Professor in the Department of Mathematics at the University at Buffalo (SUNY). He holds a PhD from Carnegie Mellon University and specializes in Financial Mathematics, Deep Learning, and Stochastic Processes. His research bridges theoretical advancements with practical applications in decentralized finance (DeFi), energy markets, and systemic risk analysis. Key areas include developing mathematical frameworks for automated market makers, optimizing investment strategies under stochastic volatility, and analyzing liquidity dynamics in financial systems.

His work frequently intersects machine learning and control theory, such as applying deep learning to solve high-dimensional partial differential equations (PDEs) and modeling regions of attraction for nonlinear systems. Bichuch collaborates internationally on projects addressing systemic risk in banking networks and regulatory frameworks for energy markets. His publications appear in journals like Mathematical Finance, SIAM Journal on Control and Optimization, and IEEE Conference on Decision and Control.

Notable contributions include frameworks for optimal regulatory charges in energy markets, models of fire sales in repo markets, and game-theoretic approaches to capacity expansion under risk aversion. His research often emphasizes real-world applications in finance, energy systems, and decentralized technologies.