Hanwen Cao 曹瀚文

I am a Ph.D. student at University of California, San Diego (UCSD). I do research at Extential Robotics Laboratory and am fortunate to be advised by Prof. Nikolay Atanasov.

Before moving to UCSD, I obtained my B.E. degree from Shanghai Jiaotong University, Shanghai, China. My undergraduate supervisor is Prof. Cewu Lu.

I have spent wonderful time doing research internship at NVIDIA (Santa Clara), Microsoft Research (Zurich), and Flexiv (Shanghai).

Email / Google Scholar / Github

News

Sep 2026 🎉 HIGS is on arXiv!
July 2026 I started a robotics research internship at NVIDIA Isaac Robotics Team.
Aug 2025 🎉 PKF is accepted to RA-L!
June 2025 I started a research internship at Microsoft Spatial AI Lab Zurich.
Apr 2025 🎉 MISO is accepted to RSS 2025!
Aug 2024 🎉 Distributed MSCKF is accepted to RA-L!

Research

I'm interested in robotics and computer vision.

	HIGS: Hierarchical Implicit Grids for Joint Geometric and Semantic Scene Understanding Hanwen Cao, Wenqiang We, Kuang-Ting Tu, Mathias Otnes, Jeffrey Delmerico, Rui Wang, Yulun Tian, Nikolay Atanasov, Under review, 2026 project page / paper / Efficient and scalable hierarchical implicit grids for both geometric and semantic features.
	PKF: Probabilistic Data Association Kalman Filter for Multi-Object Tracking Hanwen Cao, George J. Pappas, Nikolay Atanasov, Robotics and Automation Letter (RA-L), 2025 project page / paper / Probabilistic data association Kalman filter for multi-object tracking (MOT).
	MISO: Multiresolution Submap Optimization for Efficient Globally Consistent Neural Implicit Reconstruction Yulun Tian, Hanwen Cao, Sunghwan Kim Nikolay Atanasov, RSS 2025 paper / Deep SDF SLAM with neural implicit grid features.
	Multi-Robot Object SLAM Using Distributed Variational Inference Hanwen Cao, Sriram Shreedharan, Nikolay Atanasov, Robotics and Automation Letter (RA-L), 2024 project page / paper / Distributed MSCKF (Multi-State Constrained Kalman Filter) for multi-robot SLAM.
	SuctionNet-1Billion: A Large-Scale Benchmark for Suction Grasping Hanwen Cao, Hao-Shu Fang, Wenhai Liu, Cewu Lu RA-L, 2021 project page / paper / A large-scale real-world dataset for suction grasping in cluttered scenes.
	ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation Hanwen Cao, Yongyi Lu, Cewu Lu Bo Pang, Gongshen Liu, Alan Yuille BMVC, 2020 paper / code / A flexible module for point cloud sequence segmentation.
	Complex Sequential Understanding through the Awareness of Spatial and Temporal Concepts Bo Pang, Kaiwen Zha, Hanwen Cao, Jiajun Tang, Minghui Yu, Cewu Lu Nature Machine Intelligence, 2020 paper A general model for complex sequential understanding.
	Deep RNN Framework for Visual Sequential Applications Bo Pang, Kaiwen Zha, Hanwen Cao, Cewu Lu CVPR, 2019 paper / code / A new deep RNN framework with better performance on visual sequential applications.

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