Chen Tang

Chen Tang

Postdoctoral Fellow in Computer Science at UT Austin

Publications

Under Review

  1. H. Ce*, C. Weaver*, C. Tang, K. Kawamoto, M. Tomizuka, and W. Zhan, “Skill-critic: Refining learned skills for reinforcement learning,” under anonymous review
  2. C. Li*, C. Tang*, H. Nishimura, J. Mercat, M. Tomizuka, and W. Zhan, “Residual Q-learning: offline and online policy customization without value,” under anonymous review.
  3. C. Hao, C. Tang, E. Bergkvist, C. Weaver, L. Sun, W. Zhan, and M. Tomizuka, “Outracing human racers with model-based autonomous racing,” under revision for IEEE Transactions on Intelligent Vehicles (T-IV)
  4. C. Tang, N. Srishankar, S. Martin and M. Tomizuka, “Grounded relational inference: Domain knowledge-driven explainable autonomous driving,” under revision for IEEE Transactions on Intelligent Transportation System (T-ITS)

Journal

  1. W. Chang*, C. Tang*, C. Li, Y. Hu, M. Tomizuka, and W. Zhan, “Editing driver character: Socially-controllable behavior generation for interactive traffic simulation,” IEEE Robotics and Automation Letters (RA-L)
  2. J. Li, C. Tang, W. Zhan, and M. Tomizuka, “Hierarchical planning through goal-conditioned offline reinforcement learning,” IEEE Robotics and Automation Letters (RA-L) and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022
  3. C. Tang*, Z. Xu* and M. Tomizuka, “Disturbance-observer-based tracking controller for neural network driving policy transfer,” IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2020
  4. Á. Cuenca, W. Zhan, J. Salt, J. Alcaina, C. Tang and M. Tomizuka, “A remote control strategy for an autonomous vehicle with slow sensor using kalman filtering and dual-rate control,” Sensors, 2019.
  5. X. Liu, C. Tang, X. Du, S. Xiong, S. Xi, Y. Liu, X. Shen, Q. Zheng, Z. Wang, Y. Wu, et al., “A highly sensitive graphene woven fabric strain sensor for wearable wireless musical instruments,” Materials Horizons, 2017

Conference Proceedings

  1. S. Su, C. Hao, C. Weaver, C. Tang, W. Zhan, and M. Tomizuka, “Double-iterative gaussian process regression for modeling error compensation in autonomous racing,” IFAC World Congress, 2023
  2. C. Xu*, T. Li*, C. Tang, L. Sun, K. Keutzer, M. Tomizuka, A. Fathi, and W. Zhan, “PreTraM: Self-supervised pre-training via connecting trajectory and map,” European Conference on Computer Vision (ECCV), 2022
  3. L. Sun*, C. Tang*, Y. Niu, E. Sachdeva, C. Choi, T. Misu, M. Tomizuka, and W. Zhan, “Domain knowledge driven pseudo labels for interpretable goal-conditioned interactive trajectory prediction,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022
  4. C. Tang, W. Zhan, and M. Tomizuka, “Interventional behavior prediction: Avoiding overly confident anticipation in interactive prediction,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022
  5. C. Tang, W. Zhan and M. Tomizuka, “Exploring social posterior collapse in variational autoencoder for interaction modeling,” Conference on Neural Information Processing Systems (NeurIPS), 2021
  6. J. Li, C. Tang, M. Tomizuka and W. Zhan, “Dealing with the unknonw: Pessimistic offline reinforcement learning,” Annual Conference on Robot Learning (CoRL), 2021
  7. J. M. Salt Ducaju, C. Tang, M. Tomizuka and C. -Y. Chan, “Application specific system identification for model-based control in self-driving cars,” IEEE Intelligent Vehicles Symposium (IV), 2020
  8. C. Tang, J. Chen and M. Tomizuka, “Adaptive probabilistic vehicle trajectory prediction through physically feasible bayesian recurrent neural network,” International Conference on Robotics and Automation (ICRA), 2019
  9. Z. Xu, H. Chang, C. Tang, C. Liu and M. Tomizuka, “Toward modularization of neural network autonomous driving policy using parallel attribute networks,” IEEE Intelligent Vehicles Symposium (IV), 2019
  10. Z. Xu*, C. Tang*, and M. Tomizuka, “Zero-shot deep reinforcement learning driving policy transfer for autonomous vehicles based on robust control,” International Conference on Intelligent Transportation Systems (ITSC), 2018 (Best Student Paper Runner-up)
  11. J. Chen, C. Tang, L. Xin, S. E. Li and M. Tomizuka, “Continuous decision making for on-road autonomous driving under uncertain and interactive environments,” IEEE Intelligent Vehicles Symposium (IV), 2018
  12. C. Zhao, R. Xu, K. Song, D. Liu, S. Ma, C. Tang, C. Liang, Y. Zohar, and Y.K. Lee, “The capillary number effect on the capture efficiency of cancer cells on composite microfluidic filtration chips”. IEEE International Conference on Micro Electro Mechanical Systems (MEMS), 2015.

Workshop

  1. W. Chang*, C. Tang*, C. Li, Y. Hu, M. Tomizuka, and W. Zhan, “Editing driver character: Socially-controllable behavior generation for interactive traffic simulation,” CVPR Workshop on Multi-Agent Behavior: Properties, Computation, and Emergence (MABe), 2023
  2. C. Tang, N. Srishankar, S. Martin and M. Tomizuka, “Explainable autonomous driving with grounded relational inference,” NeurIPS Workshop on Machine Learning for Autonomous Driving (ML4AD), 2020

The superscript * indicates equal contribution.