Summary
Attila Kertesz-farkas is a professor and machine learning researcher with over 20 years of experience developing ML and data analysis products for biotech and related domains, and more than a decade in academic research and product-focused development. He leads an international, multidisciplinary laboratory at HSE Moscow, where he secured competitive funding to build a team combining medicine, chemistry, economics and data science and promotes meritocratic, Western-style research practices. His work spans neuro-symbolic AI, foundational models for spectrometry, robust production monitoring for ML, and SOTA advances in sequence classification, image segmentation, and statistical error control. Previously at the University of Washington and ICGEB he produced open-source tools and statistical methods that materially improved classifier power and were adopted broadly by researchers. He codes across Python, PyTorch/TensorFlow, C++ and GPU environments and has a track record of turning cutting-edge research into practical toolkits and reproducible benchmarks. He combines deep theoretical contributions with hands-on engineering and an unusual talent for building cross-disciplinary teams that translate complex models into deployable biotech solutions.
11 years of coding experience
15 years of employment as a software developer
PhD, Computer Science, PhD, Computer Science at University of Szeged
Erasmus scholarship, Erasmus scholarship at Technische Universität Dresden