I’m passionate about exploring new ways that data can be used to solve important problems in areas such as medicine, education, and socioeconomic disparity. My goal is to equip myself with the skills to steer emerging technology’s societal impact in a more positive direction.
To that end, 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 algorithms for computational imaging problems, from computer vision applications to physics-based modalities such as MRI, cryo-EM, and fluoroscopy.
Prior to beginning at Stanford, Dave spent two years at a Bay Area start-up developing new imaging algorithms for commercial deployment. Previously he earned a M.S. in EE from the University of Texas performing machine learning research under the supervision of Alex Dimakis and Sriram Vishwanath, during which time he also served as a Data Science for Social Good fellow in London. Before that Dave earned a B.S. in EE from the University of Wisconsin, where his main project was leading a 150-person organization to build a hyperloop pod for SpaceX.
|May 24, 2022||Started an ongoing list of my all-time favorite books distilled by genre.|
|May 10, 2022||Our work on scale-agnostic super-resoluion in MRI accepted as a short paper at MIDL.|
|Mar 28, 2022||Our work on multiscale scene representation, BACON: Band-Limited Coordinate Networks, accepted at CVPR and selected for oral presentation.|
|Sep 20, 2021||Started the PhD program in Stanford University’s EE Dept. Go Trees!|
|Jun 1, 2021||Began a solo bikepacking trip across Mexico following this route.|