Weizhe Chen

I received my Ph.D. degree from the Luddy School of Informatics, Computing, and Engineering at Indiana University Bloomington, working with Lantao Liu in Vehicle Autonomy and Intelligence Lab and Roni Khardon in Machine Learning Research Group.

My research aims to empower robots to proactively interact with their environment and people, while effectively addressing uncertainty stemming from various sources. My Ph.D. research focuses on robotic information gathering, which encompasses data-efficient learning and information-driven planning and control.

I am happy to chat or collaborate with you! please feel free to reach out:

Google Scholar | Github | Twitter | LinkedIn | wchen.robotics at outlook.com

Updates

Jun 2024 One paper got accepted to RSS 2024, enabling probabilistic, online, and attentive mapping (POAM).
May 2024 Attended CPS Rising Stars 2024, a great opportunity to meet excellent researchers and learn about academic careers.
Apr 2024 I successfully defended my Ph.D. thesis on "Towards Automated Science: Active Robot Learning for Information Gathering".
Jun 2023 One paper got accepted to IJRR, discussing how non-stationary GPs enables more adaptive information gathering behaviors.
May 2022 I started my second internship at Mitsubishi Electric Research Labs (MERL), working on quadrupedal robot.
Apr 2023 One paper got accepted to IJCAI 2023. We propose an online planner based on differentiable symbolic propagation of distributions.
Jan 2023 One paper got accepted to ICRA 2023. This paper suggests calibrating perception uncertainty in cooperative autonomous driving.
Jun 2022 AK won the Best Student Paper Award at RSS 2022!
May 2022 I started my summer internship at Mitsubishi Electric Research Labs (MERL), working on robotic manipulation.
Apr 2022 Attentive Kernel (AK) got accepted to RSS 2022. AK improves spatial modeling accuracy and uncertainty quantification.
Jan 2022 One paper got accepted to ICRA 2022. This work sheds light on the impact of outliers on active mapping.
Dec 2021 Our work is posted on Amazon Research Awards.
Aug 2021 Spent two years on developing the Autonomous Surface Vehicle (ASV) and non-stationary Gaussian processes (GPs).

Released a ROS package for the BlueRobotics single-beam sonar driver.
Released a ROS package of tracking PID controller for differential-drive vehicles.
Oct 2019 Presented one work at OCEANS 2019 Seattle. We apply streaming sparse GP regression to environmental monitoring.
Sep 2019 One paper got accepted by CDC 2019, extending ParetoMCTS to spatiotemporal scenarios.
Jun 2019 ParetoMCTS got accepted by RSS 2019. This work generalizes Monte Carlo tree search to multi-objective informative planning.

Publications

	Adaptive Robotic Information Gathering via Non-Stationary Gaussian Processes Weizhe Chen, Roni Khardon, Lantao Liu International Journal of Robotics Research (IJRR), 2023 ArXiv \| Code \| BibTeX
	DiSProD: Differentiable Symbolic Propagation of Distributions for Planning Palash Chatterjee, Ashutosh Chapagain, Weizhe Chen, Roni Khardon International Joint Conference on Artificial Intelligence (IJCAI), August 2023 Webpage \| ArXiv \| Code \| BibTeX
	Model-Agnostic Multi-Agent Perception Framework Runsheng Xu, Weizhe Chen, Hao Xiang, Xin Xia, Lantao Liu, Jiaqi Ma International Conference on Robotics and Automation (ICRA*), June 2023 ArXiv \| BibTeX
	AK: Attentive Kernel for Information Gathering Weizhe Chen, Roni Khardon, Lantao Liu Robotics: Science and Systems (RSS), June 2022 Webpage \| ArXiv \| Video \| Code \| IU News \| BibTeX Best Student Paper
	Informative Planning in the Presence of Outliers Weizhe Chen, Lantao Liu International Conference on Robotics and Automation (ICRA), May 2022 ArXiv \| BibTeX
	Multi-Objective and Model-Predictive Tree Search for Spatiotemporal Informative Planning Weizhe Chen, Lantao Liu Conference on Decision and Control (CDC), December 2019 ArXiv \| BibTeX
	Long-Term Autonomous Ocean Monitoring with Streaming Samples Weizhe Chen, Lantao Liu OCEANS, October 2019 ArXiv \| BibTeX
	Pareto Monte Carlo Tree Search for Multi-Objective Informative Planning Weizhe Chen, Lantao Liu Robotics: Science and Systems (RSS), June 2019 ArXiv \| Video \| Code \| BibTeX

	Adaptive Robotic Information Gathering via Non-Stationary Gaussian Processes Weizhe Chen, Roni Khardon, Lantao Liu International Journal of Robotics Research (IJRR), 2023 ArXiv \| Code \| BibTeX
	DiSProD: Differentiable Symbolic Propagation of Distributions for Planning Palash Chatterjee, Ashutosh Chapagain, Weizhe Chen, Roni Khardon International Joint Conference on Artificial Intelligence (IJCAI), August 2023 Webpage \| ArXiv \| Code \| BibTeX
	Model-Agnostic Multi-Agent Perception Framework Runsheng Xu, Weizhe Chen, Hao Xiang, Xin Xia, Lantao Liu, Jiaqi Ma International Conference on Robotics and Automation (ICRA*), June 2023 ArXiv \| BibTeX
	AK: Attentive Kernel for Information Gathering Weizhe Chen, Roni Khardon, Lantao Liu Robotics: Science and Systems (RSS), June 2022 Webpage \| ArXiv \| Video \| Code \| IU News \| BibTeX Best Student Paper
	Informative Planning in the Presence of Outliers Weizhe Chen, Lantao Liu International Conference on Robotics and Automation (ICRA), May 2022 ArXiv \| BibTeX
	Multi-Objective and Model-Predictive Tree Search for Spatiotemporal Informative Planning Weizhe Chen, Lantao Liu Conference on Decision and Control (CDC), December 2019 ArXiv \| BibTeX
	Long-Term Autonomous Ocean Monitoring with Streaming Samples Weizhe Chen, Lantao Liu OCEANS, October 2019 ArXiv \| BibTeX
	Pareto Monte Carlo Tree Search for Multi-Objective Informative Planning Weizhe Chen, Lantao Liu Robotics: Science and Systems (RSS), June 2019 ArXiv \| Video \| Code \| BibTeX