David Koes
Associate Professor
Pittsburgh, Pennsylvania, United States
Summary
🤩
Rockstar🎓
Top SchoolDavid Koes is an associate professor and computational drug discovery expert with 13 years in academia and a PhD in computer science from Carnegie Mellon. He designs novel algorithms and end-to-end systems that accelerate inexpensive therapeutic discovery, coupling machine learning with practical software engineering. A staunch advocate for open science, he contributes to prominent open-source chemistry and protein tools like Open Babel and ProDy, improving core algorithms for conformer search, bond order analysis, and interactive 3D protein visualization. Based in Pittsburgh, he combines deep domain knowledge in molecular computation with hands-on systems work, and recently stepped into leadership as co-director of the CMU-Pitt Computational Biology PhD program.
13 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at Carnegie Mellon University
Github Skills (11)
chemistry10
visualization10
c-language10
visualizations10
cprogramming-language10
python10
numpy9
dynamics9
algorithms9
api8
apidoc8
Programming languages (9)
Github contributions (5)
openbabel/openbabel
Jun 2014 - Jul 2021
Open Babel is a chemical toolbox designed to speak the many languages of chemical data.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:213 commits, 41 PRs, 103 comments in 7 years 1 month
Contributions summary:David's commits focused on enhancing the functionality of Open Babel. They implemented a fix to avoid creating a new random vector instance, and refactored the code for improved performance. The user also worked on core components, including conformer search algorithms and bond order analysis, indicating a strong understanding of the library's internal workings related to chemical data and molecular structures.
chemical-datacheminformaticsbabelchemistrytoolbox
prody/ProDy
Oct 2016 - Jun 2022
A Python Package for Protein Dynamics Analysis
Role in this project:Back-end Developer
Back-end DeveloperContributions:7 reviews, 27 commits, 9 PRs in 5 years 9 months
Contributions summary:David implemented and refined functionalities for protein dynamics analysis within the ProDy package. They added support for interactive 3D protein visualization using py3Dmol, including features for coloring and animating GNM/ANM calculations. Furthermore, they addressed issues related to multiple models and improved the API to allow for direct manipulation of the viewer object. Python 3 formatting was also incorporated.
python-packageproteinpythondynamics
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