Maria Korshunova
Senior Deep Learning Scientist at NVIDIA
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolMaria Korshunova is a Senior Deep Learning Scientist with 11 years of industry and research experience, currently applying advanced ML at NVIDIA after completing a PhD-focused trajectory at Carnegie Mellon in computational chemistry and drug design. She blends deep theoretical training from MIPT and Skolkovo with hands-on engineering—contributing core back-end and ML components to OpenChem, including molecular data layers and multitask loss functions. Her background spans internships and roles at Pfizer, Terray Therapeutics, Yandex, and multiple positions at NVIDIA, reflecting a rare mix of academia-to-production expertise. Based in Sunnyvale, she specializes in turning molecular representations (SMILES and graph structures) into scalable deep-learning pipelines that accelerate drug discovery. Notably, she pairs rigorous publications-focused research with practical toolkit development that other labs and teams can adopt.
11 years of coding experience
1 year of employment as a software developer
Master's degree, Mathematics and Computer Science, 5.0, Master's degree, Mathematics and Computer Science, 5.0 at Skolkovo Institute of Science and TechnologyBachelor's degree, Applied Mathematics and Physics, 4.92, Bachelor's degree, Applied Mathematics and Physics, 4.92 at Moscow Institute of Physics and Technology (State University) (MIPT)Doctor of Philosophy - PhD, Bioinformatics, Computational Biology, Computational Chemistry, Doctor of Philosophy - PhD, Bioinformatics, Computational Biology, Computational Chemistry at Carnegie Mellon University
Github Skills (13)
smile10
data-structures10
smil10
pytorch10
machine-learning10
computational-chemistry10
graph-convolutional-networks10
python10
data-structure10
data-processing10
predictive-modeling9
deep-learning9
data-science8
Programming languages (3)
Github contributions (5)
Mariewelt/OpenChem
Jul 2018 - Apr 2022
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:444 commits, 11 PRs, 101 pushes in 3 years 10 months
Contributions summary:Maria contributed significantly to the development of the OpenChem toolkit, focusing on implementing new functionalities for handling and processing data relevant to computational chemistry and drug design. Their work included the creation of data layers for handling SMILES strings and molecular graphs, reflecting an understanding of molecular data structures. Furthermore, they implemented a multitask loss function, demonstrating their involvement in developing the model training process using deep learning libraries.
chemistrydesign-researchdrug-designdeep-learningdrug
isayev/ReLeaSE
May 2017 - Mar 2019
Deep Reinforcement Learning for de-novo Drug Design
Contributions:139 commits, 15 PRs, 41 pushes in 1 year 10 months
drug-designdeep-learningreinforcement-learningdeep-reinforcement-learningdrug
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.