Filipp Nikitin is a computational biology PhD candidate at Carnegie Mellon with a strong foundation in data science, mathematics, and cheminformatics, and a decade of hands-on experience across research and industry. He has built production-oriented ML systems—from OCR and passport recognition to accelerated image-to-image models—and contributed open-source tooling such as TopicNet for topic modeling. At NVIDIA he developed modular generative-model packages and co-designed a scalable foundation model for 3D molecule generation, and at Los Alamos he helped create an active learning framework and database for chemical discovery. His background blends rigorous academic training (MIPT master’s with top grades) with applied research roles at Samsung and national labs, making him adept at moving deep-learning ideas into usable systems. Notably, he pairs theoretical expertise with engineering pragmatism, often designing data infrastructure (e.g., zarray-backed ALF DB) alongside model advances. Based in Pittsburgh, he is actively seeking opportunities that bridge deep learning research and drug-discovery impact.
10 years of coding experience
5 years of employment as a software developer
Master's degree, Mathematical and Information Technology, 4.85, Master's degree, Mathematical and Information Technology, 4.85 at Moscow Institute of Physics and Technology (State University) (MIPT)
Doctor of Philosophy - PhD, Computational Biology, 4.0, Doctor of Philosophy - PhD, Computational Biology, 4.0 at Carnegie Mellon University
Universal Radio Hacker (urh) plugin to decode cc1101 messages, which uses the cc1101 FEC (forward error correction) feature
Contributions:2 pushes in 1 day
feccc1101decodecorrectionradio
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.