Most of my teaching activities comprise undergraduate, graduate, and doctoral courses in the Electrical and Computer Engineering department of IST, mostly to the Electrical and Computer Engineering MSc and PhD degrees, Aerospace Engineering, and Information Systems and Computer Engineering, among others.

The updated list of courses I currently teach can be found here.

Miscellaneous pedagogical texts/code:

• Python problems, Sep 2019 — simple Python exercises for beginners.
• Simple Sudoku solver, 2019 — backtracking solver of Sudoku, that I used to write in real-time during introductory Python  classes to illustrate main features of Python. A good exercise is to reverse engineer and comment the code.
• Derivation of the discrete-time Kalman and Extended Kalman filters, May 2018 — this is a straightforward Bayesian derivation of this family of stochastic filters.
• 1D localization using Bayes filter, EKF, and MCL, version 1.3 (Python 2.x), 2009 — graphical illustration of several Bayesian localization methods in a bounded 1D space: discrete Bayes filter, Extended Kalman Filter (EKF) and Monte Carlo Localization (MCL).