Thomas Schweizer

My mission is to empower people and improve their lives through intuitive and reliable software. I believe technology should adapt to their users and not the other way around. I'm particularly interested in leveraging Machine Learning and Data Science to build the next generation of powerful, reliable, ethical, and safe software systems and applications.

I’m a PhD student at the University of Washington Paul G. Allen School of Computer Science & Engineering working on improving program comprehension by extracting natural semantics from source code with Professors Michael Ernst and René Just.

Previously, I worked at Mila where I developed software tools and methodologies to drive cutting-edge research in the domain of machine learning and its implementation in production. In June 2020, I graduated from the University of Montreal with a Masters in Computer Science. My advisor, Professor Michalis Famelis, and I researched approaches to automatically identify design-related changes through the evolution of software metrics in projects. I've also been working since 2014 for the Digger Foundation, a humanitarian company, where I design, develop, and deploy software systems to detect and eliminate landmines.

Alongside Software Engineering, Machine Learning, and Data Science, I'm interested in UI/UX design, Emergent Behaviors, Art, Software Biomimicry, and Complex Systems. I'm also an avid book reader and hiker :).