Jumana Dakka
Technical Lead at Schrödinger
New York, New York, United States
Summary
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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 Engineering, Master of Science , Electrical and Computer Engineering at Rutgers University
Github Skills (18)
affinity9
throughput8
binding8
infiniband8
calculator8
hpc6
recurrent-neural-networks5
convolutional-neural-networks4
bayesian4
classification3
machine-learning3
analytics2
simulations2
optimization2
python1
Programming languages (2)
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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