Jonathan Fine
Senior Scientist at Merck
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolJonathan Fine is a Senior Scientist based in the New York City area with a decade of experience applying machine learning and data-driven approaches to chemical and molecular problems. With a PhD in Chemistry from Purdue and a near-perfect academic record from RPI, he blends rigorous academic training with hands-on industry research at Merck. He contributes to open-source computational chemistry tooling—adding MMTF support and enhanced atom coloring to the widely used Avogadro libraries—bridging file-format engineering and visualization. Comfortable working at the intersection of ML, chemistry, and software, he translates complex molecular data into practical, visualizable insights for drug discovery and materials science.
9 years of coding experience
Doctor of Philosophy - PhD, Chemistry, 4.0, Doctor of Philosophy - PhD, Chemistry, 4.0 at Purdue UniversityBachelor's degree, Chemistry, 3.97, Bachelor's degree, Chemistry, 3.97 at Rensselaer Polytechnic Institute
English
Github Skills (9)
chemistry10
c-language10
computational-chemistry10
cprogramming-language10
opengl9
visualization8
qt8
visualizations8
open-source7
Programming languages (10)
Github contributions (5)
OpenChemistry/avogadrolibs
Aug 2018 - Aug 2018
Avogadro libraries provide 3D rendering, visualization, analysis and data processing useful in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 commits, 4 PRs, 5 comments in 3 days
Contributions summary:Jonathan implemented initial support for the MMTF file format, enabling the reading of molecular structures from MMTF files. They introduced new functionality for reading and interpreting MMTF data within the Avogadro library. Furthermore, the user added support for atom coloring within the core molecule and rendering plugins, enhancing visualization capabilities. These changes integrate a new file format and expand visual rendering options.
compchempythonc-plus-plussimulationbioinformatics
chopralab/lemon
Jun 2018 - May 2020
A framework for rapidly mining structural information from the Protein Data Bank
Contributions:311 commits, 35 PRs, 244 pushes in 1 year 11 months
pythonminingpdb-filespdbbank-data
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