My research deals with applications of optimization and matrix theory to algorithmic development for both
continuous and discrete optimization problems.
My research interests include: optimization in finite dimensional and abstract spaces; linear, nonlinear and semidefinite programming; matrix eigenvalue problems; and numerical analysis of algorithms.  

My  combinatorial optimization work applies convex relaxations to hard combinatorial optimization problems. The relaxations are based on Lagrangian duality, and in many cases they result in Semidefinite Programming relaxations.

I am a team member for the MITACS Project
on High Performance Optimization: Theory, Algorithm Design, and Engineering Applications

Selected Publications; Publications: Full List with Abstracts ; Presentations

Directory of PS/PDF publication files;  HTML Publications List