Charlie Harris
Technical Lead, UK Sovereign AI Unit at Department for Science, Innovation and Technology
Cambridge, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolCharlie Harris is a Technical Lead in the UK Sovereign AI Unit and a Cambridge PhD candidate who applies generative and geometric deep learning to real-world biotech challenges. With six years’ experience spanning government, venture and industry, he led an £8M government seed investment into OpenBind and helped scale the UK’s Encode AI for Science programme, bridging technical strategy and policy at No.10. He previously developed GNN-based protein structure tools at BenevolentAI and contributed backend and feature engineering to the widely used Graphein protein graph library, adding DSSP integration and AAIndex node features. Trained in bioinformatics and biochemistry at Imperial and Cambridge, he combines hands-on model and software development with stakeholder-facing leadership, uniquely positioning him to operationalise large biomolecular datasets for drug discovery.
6 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of CambridgeMaster of Science - MS, Bioinformatics, Distinction, Master of Science - MS, Bioinformatics, Distinction at Imperial College London
Github Skills (7)
bioinformatics10
networkx10
python10
data-science10
graph-neural-network9
pdb9
computational-biology9
Programming languages (4)
Github contributions (5)
a-r-j/graphein
Nov 2020 - Sep 2021
Protein Graph Library
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:35 commits, 1 PR, 29 pushes in 9 months
Contributions summary:Charlie primarily contributed to the graphein library by implementing and integrating features related to protein structure analysis. Their work included adding functionality to compute peptide bonds, incorporate chain IDs, and generate node and edge features within protein graphs. The user also expanded the library's capabilities by integrating the DSSP algorithm for secondary structure prediction and solvent accessibility analysis. Furthermore, they added AAIndex features to the graph nodes.
pythonpdbbioinformaticsprotein-data-bankprotein-design
cch1999/cch1999.github.io
May 2021 - Feb 2025
Contributions:2 PRs, 92 pushes, 4 branches in 3 years 9 months
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