Dave Van Veen

PhD Candidate
Stanford University

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I’m passionate about using data to solve important problems in areas such as healthcare, education, and social equity. My primary ambition is to guide emerging technology’s impact toward beneficial outcomes.

Currently I am a final-year PhD candidate in Stanford’s Electrical Engineering (EE) Dept advised by John Pauly and Akshay Chaudhari.
My research includes two major threads:

  1. adapting foundation models to improve healthcare workflows
  2. developing machine learning (ML) algorithms for inverse problems in computational imaging and signal processing

bio

Prior to beginning his PhD, Dave spent two years as a research scientist at a Bay Area start-up and the Artificial Intelligence in Medicine & Imaging (AIMI) center at Stanford. Previously he earned a MS in EE at the University of Texas conducting ML research under Alex Dimakis and Sriram Vishwanath, during which he also served as a Data Science for Social Good fellow in London. Before that Dave earned a BS in EE at the University of Wisconsin, where he created and led a 150-person organization to build a hyperloop pod for SpaceX.

news

May 2024 Successfully defended my PhD thesis entitled Data-Efficient Machine Learning for Image Reconstruction and Text Summarization in Biomedicine.
Mar 2024 Presented our LLM adaptation work at the Apple ML Health Workshop.
Feb 2024 Nature Medicine published our LLM paper on clinical text summarization!
Jan 2024 Our lab is proud to release CheXagent, a vision-language model for interpreting chest x-rays.
Jan 2024 Beginning Stanford Ignite at the Graduate School of Business and joining the 2024 cohort of Cardinal Venture’s Technical Founders!