[MMD4102 - Spring 2021, 2022, 2023]  I'm teaching Machine Learning at UOH for students of Mathematical Modeling of Data. The course covers theoretical aspects of ML, including PAC-learning,  VC dimension, unsupervised/supervised learning and neural networks. 

[IND3701 - Fall 2021, 2022, 2023]  I'm teaching the Optimization undergrad course at UOH for Engineering students, that covers linear and integer programming, polyhedral theory, convexity, and a bit of non-linear optimization. 

[MMD4001 - Fall 2021, 2022]  I'm teaching the Data Science Project at UOH for the students of Mathematical Modeling of Data. 

[IND3202 - Spring 2020, 2021, 2023] I'm teaching Simulation of Complex Systems at UOH, a course for the undergrad programs in Industrial Engineering and Mathematical Modeling of Data. This course covers technical aspects of stochastic processes, simulation, and stochastic optimization, together with applications in operations management. The students work on projects using R and Julia/Python.

[IN1009 - Spring 2020] I'm teaching Linear Algebra at UOH, a first-year course of the undergrad program in Engineering. This course covers the basics of vector spaces, matrices, spectral properties, and their applications in engineering and data processing. The computational side is performed in Octave.

[MA231 - Lent Term 2019, Lent Term 2020] I'm teaching Operational Research Methods at LSE,  together with Giacomo Zambelli, for undergrad students of the BSc programs of the Math Department. The course provides an introduction to modeling and optimization techniques such as linear/dynamic programming, and classic topics of operations such as flows, matchings, Markov chains, queueing theory and inventory management (~80 students). 

[MA424 - Lent Term 2019, Michelmas Term 2020] I'm teaching Modelling in Operations Research at LSE, for MSc students of Management, OR & Analytics and Data Science. The course consists of two parts: Simulation and Optimization. In the first are covered the classic techniques for MCMC, queueing networks and variance reduction; in the second part we focus on modeling and solving using linear/integer optimization (~30 students).

[MA2001 - Otoño 2018] I'm teaching the Multivariate Calculus undergrad course at the School of Engineering at UChile, for third-semester engineering students, that covers topology of euclidean spaces, differentiability and integration (~100 students).

[IN3701 - Otoño 2017] I'm teaching the Modeling and Optimization undergrad course at the Department of Industrial Engineering, UChile, that covers linear and integer programming, polyhedral theory, convexity, and a bit of non-linear optimization (~100 students). 

[Coursera MOOC - Fall 2015, Spring 2016] TA of the Coursera MOOC in Approximation Algorithms I & II (ENS). The course is divided into two parts, introducing classic techniques for designing approximation algorithms for many fundamental problems in combinatorial optimization. Data rounding, dynamic programming, linear programming, and randomization are tools exploited in the course.