Weizhe Chen is a Ph.D. candidate at the Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington. He works with Prof. Lantao Liu in the Vehicle Autonomy and Intelligence Lab and Prof. Roni Khardon in the Machine Learning Research Group. His research focuses on enabling robots to proactively gather informative data from their environment through data-efficient learning and information-driven planning, with applications in active mapping using Autonomous Surface Vehicles (ASVs). Chen was an intern at Mitsubishi Electric Research Labs (MERL) in the summers of 2022 and 2023. He has published in venues like IJRR, RSS, and ICRA, and received the Best Student Paper Award at RSS 2022.
Autonomous robots are playing a pivotal role in exploration and scientific data collection in remote and hazardous environments like Mars, the deep sea, and polluted areas. A fundamental research problem underlying these applications is Robotic Information Gathering (RIG), which focuses on how robots can efficiently gather informative data to model unknown environments while accounting for the embodiment constraints of Cyber-Physical Systems (CPS). My research develops planning algorithms that make informed decisions under uncertainty, and learning algorithms that can faithfully quantify uncertainty when making predictions - enhancing the adaptivity, robustness, effectiveness, and efficiency of information-gathering robots. My future research aims to further explore how to empower robots to proactively interact with their environment and people, while effectively addressing uncertainty stemming from various sources.