His research interests lie broadly in Optimization. For discrete settings, his focus is on designing and implementing effective exact methods. His research helps to exactly solve vehicle routing problems faster and accelerate general mixed integer programming solvers such as Gurobi and CPLEX through novel branching strategies. For continuous optimization, he focuses on developing efficient algorithms with provable convergence rates. He has been working on zeroth and first-order algorithms for large-scale/high-dimensional non-convex optimization problems.  He is actively recruiting self-motivated Ph.D. students with a solid mathematical background or a strong coding skill in C++.  Inquiries about potential Ph.D. positions can be sent to yu.yang@ise.ufl.edu. Personal website; Google scholar.