Eric (Haoran) Chen
AI Platforms in Healthcare & Life Sciences
I design and deploy AI-powered platforms in healthcare and life sciences,
translating complex biomedical workflows into reliable, production-ready systems adopted by scientists and clinicians.
LinkedIn Google Scholar eric@ericchen.ai
What I Work On
- End-to-end AI platforms for digital pathology and biomedical imaging
- Foundation-model–driven image search and similarity systems at institutional scale
- Interactive portals for multimodal data exploration and scientific decision support
- Cross-functional delivery spanning research, engineering, and end users
Selected Platforms & Systems
Pathology Visual Search Engine — PeCan Histology (St. Jude Cloud)
Digital pathology · foundation-model–powered visual similarity search · public portal for case exploration
- Owned backend architecture for embedding generation and large-scale similarity retrieval for whole-slide images
- Integrated foundation-model embeddings with a low-latency search service supporting interactive exploration
- Partnered with the St. Jude Cloud team to translate user needs into interface requirements under operational constraints
- Delivered a production feature surfaced through PeCan’s histology experience (public)
Live site
Reference Architecture — Secure Pathology AI (On-Prem ↔ Cloud)
Reference design · security boundaries & auditability · retrieval + summarization workflow
- Highlights on-prem ingestion, private cloud networking, and least-privilege access controls
- Separates retrieval (embeddings + vector search) from summarization to manage risk and latency
- Emphasizes auditability: structured logs, redaction, and operational monitoring
Interactive Multimodal Data Explorer — COMET Viewer
Multimodal biomedical data integration · interactive visualization · cross-disciplinary initiative
- Designed and delivered an interactive web portal for exploring linked imaging and molecular datasets
- Defined APIs and query interfaces that enable flexible cross-modal queries and interactive visual exploration
- Partnered with domain scientists to ensure accurate representation of exploratory analysis workflows in the interface
- Balanced usability, performance, and maintainability to ensure long-term adoption by research teams
Live site
Background
- PhD, Computational Biology - Carnegie Mellon University, School of Computer Science
- Senior Bioinformatics Research Scientist - St. Jude Children’s Research Hospital
- 7+ years building AI/ML systems across digital pathology, imaging, and multimodal biology
Contact
For collaborations, discussions, or questions about the work above:
eric@ericchen.ai LinkedIn