New Online Course: Data Science and Analytics
Teaching Interests and Activities
- Theory and methods for nonlinear optimization (masters’ and doctoral levels)
- Operations research/management science for MBA curricula (MBA level)
- Business analytics (MBA and masters’ level)
- Co-author of textbook Data, Models, and Decisions: the Fundamentals of Management Science.
Lecture Notes on Topics in Nonlinear Optimization
These lecture notes have been developed with Professor Jorge Vera at Pontificia Universidad Católica, Santiago, Chile.
- Introduction to Nonlinear Optimization and Optimality Conditions for Unconstrained Optimization Problems
- Newton’s Method for Unconstrained Optimization
- Steepest Descent Algorithm for Unconstrained Optimization
- Optimality Conditions for Constrained Optimization Problems
- First-Order Methods in Simple Settings (Euclidean norm, unconstrained optimization)
- First-Order Methods in the General Setting (non-Euclidean norm, Bregman distances, with constraints and composite functions)
- Interior-Point Methods for Linear Optimization
- Interior-Point Theory for Convex Optimization with Self-Concordant Barriers
- Duality Theory of Constrained Optimization
- Analysis of Convex Sets and Functions
- Convex Conic Optimization, and SDP (Semi-Definite Programming)
- Symmetric Matrices and Eigendecomposition