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Siheng Chen
Associate Professor
Shanghai Jiao Tong University
Cooperative Medianet Innovation Center (CMIC)
Shanghai Artificial Intelligence Laboratory
Biography
Siheng Chen 陈思衡 is a tenure-track associate professor of Shanghai Jiao Tong University and co-PI at Shanghai AI laboratory. He received his doctorate from Carnegie Mellon University. His research interests include collaborative & graph machine learning. Dr. Chen’s work on sampling theory of graph data received the 2018 IEEE Signal Processing Society Young Author Best Paper Award. His co-authored paper on structural health monitoring received ASME SHM/NDE 2020 Best Journal Paper Runner-Up Award and another paper on 3D point cloud processing received the Best Student Paper Award at 2018 IEEE Global Conference on Signal and Information Processing. His technique on joint perception and prediction was applied on all the UBER’s autonomous cars. Dr. Chen also contributed to the project of scene-aware interaction, winning MERL President’s Award. He also serves as the associate editor of IEEE Transactions on Signal and Information Processing over Networks. Research vision: integrating ai agents into human lives
Join us:
We are actively hiring! We are looking for motivated postdocs, interns, PhD/master/undergraduate students. If you are interested in working with us, please feel free to drop me an email!
- Collaborative agents
- Graph machine learning
- Computational social science
Ph.D in Electrical and Computer Engineering
Carnegie Mellon University
Master of Science in Machine Learning
Carnegie Mellon University
Bachelor of Science in Electronic Engineering
Beijing Institute of Technology
Recent News
[Jan. 2024] Two papers are accepted by ICLR 2024
[Jan. 2024] FreeAlign is accepted by ICRA 2024
[Dec. 2023] Two papers are accepted by ICASSP 2024
[Dec. 2023] Self-supervised BEV motion is accepted by AAAI 2024
[Sep. 2023] Two papers are accepted by NeurIPS 2023
[Jul. 2023] Three papers are accepted by the International Conference on Computer Vision (ICCV)
[Jun. 2023] Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting is accepted by Transactions on Pattern Analysis and Machine Intelligence
[Apr. 2023] Two papers are accepted by The International Conference on Machine Learning (ICML)
[Apr. 2023] CoCa3D is reported by 机器之心
[Mar. 2023] Four papers are accepted by The Conference on Computer Vision and Pattern Recognition (CVPR)
Recent Publications
Projects
MATRIX, a novel social scene simulator that emulates realistic scenes around a user’s input query, enabling the LLM to take social consequences into account before responding."
CoAlign, a novel hybrid collaboration framework that is robust to unknown pose errors.
GroupNet, a multiscale hypergraph neural network, which is novel in terms of both interaction capturing and representation learning.
Contact
- sihengc@sjtu.edu.cn
- 800 Dongchuan Road, Shanghai, 200240
- Enter SEIEE Building 5 and take the stairs to Office 303A on Floor 3


