Dave Van Veen

PhD Candidate
Stanford University


I’m passionate about exploring new ways we can use data to solve important problems in areas such as medicine, education, and socioeconomic disparity. Ultimately my goal is to steer emerging technology’s societal impact in a more positive direction.

Currently I am pursuing a PhD in Stanford’s Electrical Engineering (EE) Dept advised by John Pauly, Akshay Chaudhari, and Gordon Wetzstein. My research is focused on developing machine learning (ML) algorithms for computational imaging problems, from computer vision applications to physics-based modalities such as MRI and cryo-EM. I’m also excited about harnessing foundation models to improve healthcare workflows.


Prior to beginning his PhD, Dave spent two years as a research scientist at a Bay Area start-up and the Artifical 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.


Sep 14, 2023 Sharing our new LLM paper, an exciting collaboration between clinicians and NLP researchers: Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts.
Jun 6, 2023 Headed across the pond to be a visiting scholar with Reinhard Heckel at TU - Munich! Many thanks to The Europe Center for my fellowship to make this possible.
May 28, 2023 Our paper RadAdapt: Radiology Report Summarization with Large Language Models accepted at ACL BioNLP and selected for oral presentation.
Jan 3, 2023 Published two new blog posts on balanced productivity and reflections from a Peruvian trek.
Jul 6, 2022 Presented our work on scale-agnostic super-resoluion in MRI at MIDL in Zurich.