Summary
Jason Khadka is a research scientist and computational physicist with a PhD in computational and biological physics and nine years of experience applying AI/ML and optimization methods to complex scientific problems. Based in Berlin, he blends rigorous theoretical training from Göttingen and IFISC with practical algorithm development, focusing on translating physics-driven insight into robust machine learning models. His background in complex systems gives him a knack for framing high-dimensional, noisy problems in ways that make optimization tractable. Colleagues find he balances deep technical rigor with a curiosity for cross-disciplinary applications, from biological modeling to scalable AI workflows. He is as comfortable deriving equations as prototyping code, often uncovering simple principled approaches where others see only complexity.
9 years of coding experience
Master in Physics of Complex Systems, Physics of Complex Systems, Master in Physics of Complex Systems, Physics of Complex Systems at IFISC (Institute for Cross-Disciplinary Physics and Complex Systems)
Bachelor of Science (B.Sc.), Physics, Bachelor of Science (B.Sc.), Physics at Jacobs University Bremen
Doctor of Philosophy (Ph.D.), Computational and Biological physics, Doctor of Philosophy (Ph.D.), Computational and Biological physics at The University of Göttingen
Hindi, German, English, Nepali