Sunhwan Jo is a computational chemistry leader with 15+ years of experience applying molecular simulation, machine learning, and software engineering to drug discovery and biophysics. Currently Senior Director of Computational Chemistry at Beren Therapeutics, he has led teams building end-to-end CADD workflows, active-learning pipelines using graph-convolutional networks, and production-grade cloud deployments. A developer at heart, he has contributed core modules to CHARMM, NAMD and OpenMM (including extensions to OpenMM’s Gromacs topology handling) and has a track record of parallel-performance optimizations on national supercomputers. He founded widely used scientific web interfaces (CHARMM-GUI components) and has shipped user-friendly GUIs that are adopted broadly by the simulation community. His work blends deep theoretical methods (free energy, replica exchange, MD with NMR restraints) with practical software delivery, enabling AI-driven hit triage and structural modeling at scale. Based in Los Angeles, he pairs a PhD in biophysics with hands-on open-source contributions and product-focused leadership.
OpenMM is a toolkit for molecular simulation using high performance GPU code.
Role in this project:
Back-end Developer
Contributions:7 commits, 3 comments in 3 months
Contributions summary:Sunhwan primarily focused on extending the functionality of the GromacsTopFile class within the OpenMM library. They implemented support for NBFIX and VSTIE2 handling, adding new processing functions and data structures to parse and manage these features within the topology file. These changes involved modifications to handle non-bonded interactions and virtual sites, including the addition of exceptions and modifications to the non-bonded force calculations. The user's contributions included adding test cases to validate the implemented features.
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Sunhwan Jo - Senior Director Of Computational Chemistry