David is a statistician, scientist, and entrepreneur. He is a venture partner at GV, where he focuses on investments at the intersection of machine learning, healthcare, and life sciences.
David’s career has focused on using machine learning to identify and characterize structure in high-dimensional data. His work has been published in high-impact journals including Science, The Journal of Machine Learning Research, and The Annals of Applied Statistics, and he has focused on applications across a broad range of fields including computer-aided diagnostics, disease modeling, high-throughput screens, and immunotherapy. David has also spent time working on public health initiatives in India, Zambia, and Peru.
David received his Ph.D. in computer science from MIT, where he was a Soros Fellow and a National Science Foundation Fellow. Prior to that, he studied statistics at the University of Oxford as a Marshall Scholar. David also holds a bachelor’s degree and a master’s degree in computer science from MIT. His work earned a best thesis award from the Department of Electrical Engineering and Computer Science at MIT.