Rate My Professor Matt Zucker

Zucker's research focuses on robotics, encompassing motion planning, machine learning, numerical optimization, navigation, manipulation, obstacle avoidance, dynamic simulation, computer vision, computer graphics, laboratory automation, rapid prototyping, and CNC machining. He has led funded projects including the DARPA Robotics Challenge (2012-2014) for humanoid disaster response behaviors, NIH Phase I SBIR with FlySorter LLC (2017-2019) for automated Drosophila sorting, DARPA Learning Locomotion (2007-2009), and NIST Standard Reference Data (1998-2000). Notable publications include "CHOMP: Covariant Hamiltonian Optimization and Motion Planning" (International Journal of Robotics Research, 2013, with Nathan Ratliff et al.), "Optimization and Learning for Rough-Terrain Legged Locomotion" (IJRR, 2011, with Nathan Ratliff et al.), "A general-purpose system for teleoperation of the DRC-HUBO humanoid robot" (Journal of Field Robotics, 2015), and "Cube-to-sphere projections for procedural texturing and beyond" (Journal of Computer Graphics Techniques, 2018, with Yosuke Higashi). His scholarship has garnered over 6,000 citations on Google Scholar. At Swarthmore, he teaches courses such as Mobile Robotics, Computer Vision, Introduction to Engineering Design, Computer-Aided Manufacturing, and Linear Physical Systems Analysis labs. Zucker is a member of Sigma Xi (inducted 2011) and Psi Chi (2002), and co-authored an op-ed in the Philadelphia Inquirer (2025) on executive orders impacting scientific research.