My research deals
with applications of optimization and matrix theory
to algorithmic development for both
continuous and discrete
My research interests include:
optimization in finite
abstract spaces; linear, nonlinear and semidefinite programming; matrix
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
on High Performance Optimization: Theory, Algorithm Design, and