Jumana Dakka
Technical Lead at Schrödinger
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolJumana Dakka is a Technical Lead with 10 years of experience applying machine learning to simulation-driven drug discovery and computational chemistry. Based in New York, she has advanced Schrödinger’s hit discovery efforts—building ML models for protein design, virtual screening, and DNA-encoded libraries—while architecting scalable cloud-native screening pipelines on GCP, BigQuery and Argo. Her background blends high-performance computing and bioengineering, including development of the HTBAC library to run >10,000 concurrent binding free energy simulations on national supercomputers and publications/awards from that work. She pairs hands-on model and descriptor development with production-grade workflow engineering, enabling large-scale virtual screens and improved binding-affinity prediction. Notably, her earlier translational research produced assays and mechanistic insights published in PNAS, reflecting a rare mix of wet-lab experience and ML/HPC systems expertise.
10 years of coding experience
7 years of employment as a software developer
Master of Science Electrical and Computer Engi, Master of Science Electrical and Computer Engi at Rutgers University
Github Skills (25)
affinity10
binding8
calculator8
infiniband7
descriptor7
throughput6
hpc6
computation5
storage4
chemistry4
python4
machine-learning3
analytics3
simulations2
reference-implementation2
Programming languages (1)
Github contributions (5)
radical-collaboration/isc-htbac-paper
Nov 2017 - Sep 2018
Contributions:169 pushes, 1 branch, 3 comments in 10 months
jdakka/radical.htbac
Oct 2017 - Aug 2018
Contributions:161 pushes, 8 branches in 10 months
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