Computing Systems for Data-Driven Science
Carl Vondrick is an assistant professor of computer science at Columbia University. His research focuses on computer vision and machine learning. By training machines to observe and interact with their surroundings, we believe we can create robust and versatile models for perception. We often develop visual models that capitalize on large amounts of unlabeled data and transfer across tasks and modalities. Other interests include sound and language, interpretable models, high-level reasoning, and perception for robotics.
Before Columbia, Carl was a research scientist at Google AI. He completed his PhD in computer science at the Massachusetts Institute of Technology in 2017, and his BS in computer science at the University of California, Irvine in 2011.