Hello! I am Tomas Knapen, computational neuroscientist. I use my broad experience in data analysis, programming, communication, and reproducible science to guide data science projects.

Philosophy

My conviction: understanding "why" is infinitely more valuable than knowing "how", especially when dealing with predictive data science outcomes.

That is, true long-term progress in any data science project depends on understanding the mechanisms at work. Quick-and-dirty, black-box methods may deliver fast results, but without deeper understanding the expiration date of these results comes very soon.

Linking Neuroscience and AI My scientific career focuses on explaining those human brain mechanisms that have strong links to dominant AI paradigms, such as reinforcement learning and convolutional neural network architectures. In this way, I am able to use cutting-edge neuroscientific insights to guide AI/data science projects.

Teaching I also teach full graduate-level courses on these topics in the Artificial Intelligence/Computer Science and Behavioral Sciences departments of the Vrije Universiteit Amsterdam. Need to know more about specific topics in this realm? I can teach you.

Ethical, Explainable AI If we cannot explain the inferences our actions and policies are based on, how can we defend them? How can we ensure that the ethics of our policies are just?

A Long-Term View on Data Science My core explainable-AI philosophy goes hand in hand with a strong focus on reproducibility and open practices, that can benefit a broad range of data science applications.