Caleb Ellington
Research Scientist at GenBio AI
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolCaleb Ellington is a research scientist and computational biologist with a decade of experience applying machine learning and software engineering to precision medicine and therapeutic discovery. Currently at GenBio AI and a PhD candidate in the CMU-PITT Computational Biology program, he builds foundation-model and probabilistic approaches for target identification and rare-disease therapeutics. His background spans deep learning for protein folding at the Institute for Protein Design, ML-driven drug discovery at Genesis Therapeutics, and scalable lab informatics and cloud infrastructure from earlier research and software roles. Equally at home with code and biology, he blends production-ready software practices with cutting-edge probabilistic and multi-task learning methods to move models toward real-world impact. Based in San Francisco, he describes himself succinctly on GitHub as a "Computational Biologer," signaling a pragmatic, research-first approach to computational biology.
11 years of coding experience
4 years of employment as a software developer
B.S., Computer Science, B.S., Computer Science at University of WashingtonDoctor of Philosophy - PhD, Computational Biology, Doctor of Philosophy - PhD, Computational Biology at Carnegie Mellon University School of Computer Science
Github Skills (36)
chatgpt10
python10
langchain10
statistics10
open-source10
typescript10
llm10
sklearn10
openai10
generative-ai10
ai10
bioinformatics10
gemini10
anthropic10
machine-learning9
Programming languages (5)
Github contributions (5)
cnellington/cnellington
Dec 2020 - Jun 2026
Contributions:12 pushes, 1 branch in 5 years 6 months
genbio-ai/ModelGenerator
Dec 2024 - Jan 2026
GB.ModelGenerator is a software stack that enables researchers to adapt pretrained models and generate finetuned models for downstream tasks.
Contributions:19 releases, 12 PRs, 70 pushes in 1 year
pre-trained-model
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