Rajiv Sambharya
I am an Assistant Professor in the Industrial and Systems Engineering Department at Texas A&M University. My research lies at the intersection of optimization, control, and machine learning. I focus on developing data-driven tools to enable fast and reliable optimization. My email is rajivsambharya@tamu.edu.
Upcoming Talks
University of Delaware, Robotics Graduate Student Organization
INFORMS Annual Meeting, San Francisco
News
I began teaching DAEN429: Data Analytics II at Texas A&M, a deep learning course in the Data Engineering program.
I have started as an Assistant Professor in the Industrial and Systems Engineering Department at Texas A&M University!
Our paper Learning Algorithm Hyperparameters for Fast Parametric Convex Optimization with Bartolomeo Stellato was accepted to the SIAM Journal on Mathematics of Data Science.
I gave a talk at the SIAM Conference on Optimization in Edinburgh on Learning Algorithm Hyperparameters for Fast Parametric Convex Optimization with Certified Robustness. Thank you Bartolomeo Stellato for the invitation!
I organized a session called Data-Driven Algorithm Design and Analysis for Parametric Optimization at the INFORMS Optimization Society Conference in Atlanta. Thank you Mathieu Dahan for the kind invitation. In the same session, I gave a talk on Verification of Sequential Convex Programming for Parametric Non-convex Optimization.
New preprint on Verification of Sequential Convex Programming for Parametric Non-convex Optimization with Nik Matni and George Pappas. We introduce a verification framework to exactly verify the worst-case performance of sequential convex programming (SCP) algorithms for parametric non-convex optimization. Our framework provides, for the first time, global worst-case guarantees for SCP algorithms in the parametric setting.