Multimodal patient models
Work on systems that combine histopathology, transcriptomics, EHR context, and model infrastructure in a form clinicians can inspect.
Computational biology, AI, oncology, wearables, writing
Hanson Wen is a Molecular and Cell Biology + Computer Science student at UC Berkeley building across computational biology, AI systems, oncology, wearable technology, and writing.
Current work spans research, side projects, and writing: multimodal biology, wearable sensing, evaluation for agent systems, and hacker-built prototypes that make technical questions tangible sooner.
Three active threads
This page is a short overview. More detail lives on the projects, writing, about, and resume pages.
Work on systems that combine histopathology, transcriptomics, EHR context, and model infrastructure in a form clinicians can inspect.
Research on agent benchmarks, biological workflows, and the interface choices that make a system more reliable in practice.
Essays and notes that help explain how I am thinking about the technical work and the questions around it.
An interest in wearable technology and fast experimental builds that make biology, behavior, and decision-making easier to inspect in the real world.
Selected projects
A fully local pathology AI system for treatment-response prediction, evidence retrieval, and reporting on whole-slide images.
Top 10 in Google MedGemma Impact Challenge
An agentic workflow for extracting decision-useful insight from clinical trial protocols and trial documents.
CalHacks 12.0 Regeneron Track Winner
Processed 131GB of whole-genome sequencing data, identified 4.99 million variants, and built a full pipeline for ancestry and pharmacogenomics analysis.
Full-stack genome pipeline
Humanity's Last Exam for computer-use agents, spanning 63 high-GDP domains and a much tougher standard for useful agent performance.
Benchmark design at Berkeley RDI
Photography
Photography is where I practice composition, patience, and noticing details outside the usual research loop.
Writing
Essays and notes that add context to the projects and research.
Essays on AI, computational biology, philosophy, and the practical questions around building things that might last.
Current experience, education, projects, and awards pulled from the resume.