Thomas Duignan
Machine Learning Engineer at University at Buffalo
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolThomas Duignan is a machine learning engineer with 11 years of experience applying ML and software engineering to scientific domains, particularly AI-accelerated drug discovery and materials chemistry. He has progressed from graduate research in theoretical chemistry to senior and principal engineering roles at Proxima, spearheading protein-first approaches for PROTAC and molecular glue design. Thomas blends deep scientific rigor from a PhD with practical production experience building ML pipelines and cloud-enabled research platforms. He’s comfortable moving models from prototype to operational systems and has worked across startups and larger firms to productionize research workflows. Based in New York, he consistently pursues hobby coding projects outside work, reflecting a continual drive to explore new tools and techniques beyond his day job.
11 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (PhD) Theoretical Chemistry, Doctor of Philosophy (PhD) Theoretical Chemistry at University at BuffaloBachelor of Applied Science (B.A.Sc.) Physical Chemistry, Bachelor of Applied Science (B.A.Sc.) Physical Chemistry at SUNY Geneseo
English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (53)
threejs10
open-science10
visualization10
reproducible-science10
atomic-design10
modeling-tool10
computational-chemistry10
materials-informatics10
tsne10
chemistry10
3d-models10
structural-biology9
molecular-simulation9
sequence-analysis9
redux9
Programming languages (6)
Github contributions (5)
tjduigna/exa
Apr 2016 - Apr 2020
Core exa functionality
Contributions:25 PRs, 125 pushes, 12 branches in 3 years 11 months
source-portexaxmake
plinder-org/plinder
Jul 2024 - Feb 2026
Protein Ligand INteraction Dataset and Evaluation Resource
Contributions:40 reviews, 47 PRs, 182 pushes in 1 year 7 months
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