Since the summer of 2016, I try to frequently make sketchnotes. Sketchnotes are the hipster way of taking notes. The idea is that you document meetings, presentations and the like using a combination of doodles, text and diagrams. That way you end up with a summary that is something a hybrid between a scheme and a comic book page.
Looking back, 2017 was an excellent but busy year, both professionally and personally. Luckily, I still found the time to digest some books.
Algorithms are awesome! While mathematics is mainly involved with proving theorems, which merely state some truth, computer science studies algorithms, which produce truths. A mathematician might be able to tell you that there is a way, a computer scientist will be able to find the way!
This summer I stumbled upon the optimal transportation problem, an optimization paradigm where the goal is to transform one probability distribution into another with a minimal cost. It is so simple to understand, yet it has a mind-boggling number of applications in probability, computer vision, machine learning, computational fluid dynamics and computational biology. I recently gave a seminar on this topic and this post is an overview on the topic. Slides can be found on my SlideShare and some implementations can are shown in a Jupyter notebook in my Github repo. Enjoy!
Do you remember the first time you felt like a scientist or an engineer? Yesterday, I had the pleasure of being one of the more than 300 volunteers of the WeGoSTEM project. Jacotte, Luc and myself showed the children Sint-Vincentius school how to build and program a simple drawing robot.
Whether you like it or not, a large part of a scientist job is about communicating. You have to pitch your ideas to collaborators, outline your plans to get grants, educate your students and report your findings to the scientific community. It is hence a good investment to spend a bit of your precious time honing your soft skills.