معرفی
Constantine Caramanis is a Professor and holder of the Chandra Family Endowed Distinguished Professorship in Electrical and Computer Engineering at the University of Texas at Austin. His research focuses on decision-making in large-scale complex systems, specializing in robust optimization, high-dimensional statistics, machine learning, and applications to networks including social, wireless, transportation, and energy systems. Caramanis directs a substantial research group and is affiliated with the NSF Institute for Foundations of Machine Learning and the UT Machine Learning Lab.
He has made significant contributions to optimization theory, developing efficient algorithms for matrix sensing, non-convex problems, and combinatorial optimization. His recent work bridges machine learning and control theory through latent MDPs, diffusion models for inverse problems, and bandit algorithms with fairness considerations. Caramanis has received prestigious recognition including the NSF CAREER award and IEEE Fellowship for his theoretical advances in optimization and learning.
