Hoang Ha is a LIMS analyst and life sciences technologist with six years of experience bridging bench science and enterprise software implementations across biotech and pharma. He has led Benchling deployments for startups to $1M+ ARR enterprises, built SQL operational dashboards, and collaborated with engineering teams to deliver custom API and AWS-based integrations that drove repeat business. With a background as an applications scientist and graduate researcher, he combines hands-on molecular biology expertise with practical project management to streamline complex system rollouts. Hoang also contributes front-end work to notable open-source projects in the AI/LLM space—helping adapt chat templates and improve documentation for offline ChatGPT alternatives—reflecting a rare blend of wet-lab credibility and software craftsmanship. Based in San Jose, he is a pharmacist-at-heart who is passionate about applying AI to scientific workflows and improving customer experience in professional services. Colleagues rely on him to translate scientific requirements into auditable, production-ready LIMS solutions that scale across disciplines.
6 years of coding experience
10 years of employment as a software developer
B.S. Cell Biology, B.S. Cell Biology at University of California, Davis
Jan is an open source alternative to ChatGPT that runs 100% offline on your computer.
Role in this project:
Full-stack Developer
Contributions:22 reviews, 71 PRs, 319 pushes in 1 year 1 month
Contributions summary:Hoang primarily contributed to the front-end development of the Jan application, focusing on the user interface and the application's structure. They configured the table of contents and app anatomy by adding a title to the table of contents and adjusting margins. Additionally, the user fixed navigation issues within the Docusaurus configuration. They also updated the sidebar configuration and resolved merge conflicts.
Contributions:3 reviews, 3 PRs, 16 comments in 1 month
Contributions summary:Hoang appears to be focused on front-end development, specifically implementing and modifying chat templates using the `SmolLM2` model. They have modified the `chat_templates_example.ipynb` notebook to demonstrate how to use chat templates. The contributions involve using a tokenizer, decoding conversations, and tokenizing the conversation.
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