"Learn the rules as a pro, so you can break them as an artist." Pablo Picasso.
I believe that understanding problems and topics in a fundamental way, leads to novel solutions and original insights. Thus, my teaching strategy consists of a combination of understanding concepts and learning by doing approach.
Specific techniques applied in my courses are:
Use of minimal working examples for explaining fundamental concepts and from them move to more complicated cases.
Some assignments consist of reading, discussing or implementing research papers.
Extra point assigments consist in writting an essay about books, documentaries, films, or plenary talks given by top scientists. The material for the assignment is selected within the scope of the course.
For math courses, I have designed a set of board games like dominoes, bingo, and matching, in which students make extensive use of mathematical concepts and compute operations for wining the game.
For computer science courses, some assignments consist of implementing classic algorithms using any programming lenguage.
In most of my courses the students developed a project along the semester/quarter according to their interests and within the scope of the course. In courses such as automation, automatic control or programming, some exams consisted of developing a project with specific requirements and deadline. In both cases they made a 20 minutes presentation, with a Q&A session, and showed a working demo of their project.
I have lectured more than 25 different courses at undergraduate level in topics such as: computer programming, mathematics, artificial intelligence, among others.
As a computer vision scientist, my pedagogical commitment is to teach the geometric foundations of computer vision, from projective and multi-view geometry to the use of geometric principles to improve state-of-the-art algorithms. In addition, to exemplify how geometric algebra simplifies the modeling, computing and application of such principles.