Fitz Luo · AI for Drug Discovery · Scientific Discovery Workflows & Software
- AI-powered scientific discovery workflows: building eLabX, an open-source electronic laboratory notebook for researchers, chemists, and engineers.
- Cheminformatics infrastructure: maintaining go-indigo, go-chem, and PyChemKit for molecular structure processing and chemistry data workflows.
- Scientific AI experiments: exploring LLM-assisted lab notes, reaction yield prediction, retrosynthesis workflows, and practical tools for data-heavy research.
| Project | Focus | Stack |
|---|---|---|
| eLabX | AI-driven electronic laboratory notebook for modern research labs | Vue, Go, Gin, GORM, AI |
| go-indigo | High-performance molecule and reaction processing via Indigo CGO bindings | Go, CGO, Indigo |
| go-chem | Go library for molecular structure processing, file formats, and properties | Go, Chemistry |
| PyChemKit | Python toolkit for chemistry and molecular data experiments | Python, Chemistry |
| rxn-yield-prediction | Deep learning model for chemical reaction yield prediction | Python, ML, Chemistry |


