Teaching

Northwestern University, Evanston, Illinois, USA

Fall and Winter 2020, 2021, and 2022


Analytics for social good is a university-wide course where students use analytic tools on a series of non-profit case studies. The course is a combination of weekly lectures and interactive team sessions. As a TA I led weekly lab sessions combining R/Tableau technical sessions, team case study work, and practice sessions for final presentations.


  • Instructor of the IEMS MSiA Bootcamp. Calculus, Algebra, Probability, and Statistics

Fall 2019,2020,2021, and 2022


The IEMS MSiA Bootcamp consists of four modules on calculus, algebra, probability, and statistics. The objective of the Bootcamp is to get students from multiple backgrounds at the same level before their courses start. As an instructor, I have to plan the course material including lectures, sample exercises, and notes.


  • Instructor of the IEMS Ph.D. Bootcamp. Introduction to Python and Matlab

Sept 2019


The IEMS Ph.D. Bootcamp objective is to get first-year Ph.D. students from multiple backgrounds on the same level. The Introduction to Python and Matlab Bootcamp consisted of hands-on exercises on well-known problems such as newsvendor and TSP.


  • Grader. IEMS 313 - Foundations of optimization

Fall 2019, 2020, and 2021


  • Grader. IEMS 481- Logistics

Fall 2022


Universidad de los Andes, Bogota, Colombia

  • Teaching assistant. Advanced Optimization (Graduate level)

January 2017 - June 2018


Advanced optimization is a graduate-level course in the Industrial Engineering master.'s The course covers a variety of topics including column generation, Dantzig-Wolfe decomposition, and DEA. As a TA I led the weekly lab sessions where I covered class topics and additional material. I also assisted with exam questions' design and grading as well as the design and grading of assignments.


  • Teaching assistant. Optimization principles (Undergraduate level)

January 2017 - June 2018


Optimization principles is one of the core courses in the operation research area of the program. The course covers topics graph method, simplex algorithm, sensibility analysis, duality, and formulation. As part of the TA group, I have to lead weekly lab sessions covering class topics and coding in Xpress Solver. I also assisted with assignments, projects, and exam questions design.


  • Undergraduate Teaching Assistant.

Optimization principles (August 2013 - December 2015)

Probabilistic and Stochastic Models (January 2014 - June 2015)


The undergraduate teaching assistant in the Industrial Engineering department is a position where undergraduates help with the course grading. In addition, some courses, such as optimization principles and probabilistic and stochastic models, required their undergraduate TAs to help the graduate teaching assistant during office hours to solve students' questions.