Researching explainable AI, robust vision models, and physics-informed ML.
Hi, I’m Patrick, a PhD student in Electrical and Computer Engineering at Northwestern University.
I work in the AI in Multimedia – Image and Video Processing Lab (AIM-IVPL) under the guidance of Aggelos K. Katsaggelos.
My research focuses on making machine learning models more explainable, adaptable, and robust, bridging the gap between what AI can do and how well we can understand and trust it.
My passion for signal processing and explainable AI began during my master’s in data science at the Eastern Switzerland University of Applied Sciences, where I was supervised by Guido M. Schuster.
With more than ten years of experience in algorithm and software development, machine learning, and project management, I aim to connect research with real-world impact.
Explainable AI (XAI) · Robust Computer Vision · Deep Learning
Physics-Informed Neural Networks (PINNs / PINOs) · Signal Processing · Trustworthy and Interpretable AI
I am a Swiss native now calling the Chicago area my home-away-from-the-mountains during my PhD.
Outside research, I enjoy time with friends and family, exploring Chicago’s blues scene, and playing guitar.
When I’m not immersed in AI or music, I’m usually running, cycling, or practicing martial arts to stay balanced.
- Personal website: patch0816.github.io
- Google Scholar: scholar.google.com/citations?user=w1QXiQkAAAAJ
- ORCID: orcid.org/0009-0003-1268-5529
- LinkedIn: linkedin.com/in/patrick-koller
Email: [email protected]
Always open to collaboration, new ideas, and meaningful discussions across AI, science, and engineering.
“Any sufficiently advanced technology is indistinguishable from magic.” – Arthur C. Clarke