Teaching

Present 2015
Linear Programming, ISE 631 (Ph.D. level, 10 students)
University of Southern California, Industrial & Systems Engineering
Taught with rigor, this is the first doctoral course in the field of optimization that serves as the foundation for all subsequent courses in the broad area of mathematical programming. As such, the course is intended for firstyear Ph.D. students and advanced M.S. students who intend to pursue a doctoral degree.

2014
Optimization Methods, 15.093 (M.S. level, 80 students)
MIT Sloan School of Management, Operations Research & Statistics Group
Introduces the principal algorithms for linear, network, discrete, robust, nonlinear, dynamic optimization and optimal control. Emphasizes methodology and the underlying mathematical structures. Topics include the simplex method, network flow methods, branch and bound and cutting plane methods for discrete optimization, optimality conditions for nonlinear optimization, interior point methods for convex optimization, Newton's method, heuristic methods, and dynamic programming and optimal control methods.

2013
MixedInteger and NonConvex Optimization, 10.557 (Ph.D. level, 30 students)  Guest Lecturer
Massachusetts Institute of Technology, Department of Chemical Engineering
Taught the part of the course concerned with mixedinteger optimization. Introduced modelling with binary variables (binary choice, relations between events, forcing constraints, logical propositions, disjunctive constraints, etc.), strength of formulations, and the cutting planes algorithm.

2014
Robust Modeling, Optimization & Computation, 15.094 (Ph.D. level, 40 students)
MIT Sloan School of Management, Operations Research Center
2011 2009Operations Research, CO343 (M.Eng. level, 80 students)
Imperial College London, Department of Computing

2011
Computational Finance, CO422 (M.Eng. level, 130 students)
Imperial College London, Department of Computing