Blaž Stojanovič is an engineer blending eight years of physics-driven scientific computing with practical machine learning and founding-stage product work. He has led relational deep learning and agent efforts at Kumo.ai for fraud detection, personalization, and recommender systems, and now contributes to pre-training engineering at Poolside in Mountain View. His academic background (MPhil in Scientific Computing from Cambridge and a physics BSc) and research at Stanford and Jozef Stefan Institute inform work on graph neural networks, large-scale simulation emulation, and meshless PDE solvers. He pairs rigorous numerical methods experience—parallelization, domain decomposition, and uncertainty quantification—with applied ML for real-world systems. Notably, he moves comfortably between building production models and publishing research-grade software and papers, bringing a scientist’s curiosity to product-focused engineering.
9 years of coding experience
6 years of employment as a software developer
Master of Philosophy - MPhil, Scientific Computing, Master of Philosophy - MPhil, Scientific Computing at University of Cambridge
International Baccalaureate, International Baccalaureate at Gimnazija Kranj
Bachelor's degree, Physics, Bachelor's degree, Physics at University of Ljubljana, Faculty of Mathematics and Physics
Contributions:5 pushes, 1 branch in 3 years 7 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.