Maxim Raginsky

Maxim Raginsky is a Professor at the University of Illinois at Urbana-Champaign, holding appointments in the Department of Electrical and Computer Engineering, Coordinated Science Laboratory, and a courtesy appointment in Computer Science. His work bridges probability, stochastic processes, control theory, machine learning, optimization, and information theory, focusing on modeling, learning, and simulation of nonlinear dynamical systems with applications to advanced electronics, autonomy, and artificial intelligence.

Research Interests

• Nonlinear dynamical systems in machine learning and control
• Statistical machine learning theory
• Information-theoretic methods in learning
• Stochastic control and filtering

Scientific Contributions

• Co-author of foundational monographs on concentration inequalities and generalization bounds
• Recipient of the NSF CAREER Award (2013), IEEE Fellow (2025), and Roberto Tempo Best CDC Paper Award (2024)
• Editorial roles in Foundations and Trends in Machine Learning, Journal of Machine Learning Research, and SIAM Journal on Mathematics of Data Science

Academic Leadership

• Advising 15+ graduate students and postdocs including Joshua Hanson, Belinda Tzen, and Tanya Veeravalli
• Teaching core graduate courses: Control of Stochastic Systems, Statistical Learning Theory, Optimization by Vector Space Methods