Chen Tang

Chen Tang

Postdoctoral Scholar in Mechanical Engineering at UC Berkeley

Publications

Under Review

  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,” under review for IEEE Robotics and Automation Letters (RA-L)
  2. 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)
  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)

Journal

  1. 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
  2. C. Tang*, Z. Xu* and M. Tomizuka, “Disturbance-observer-based tracking controller for neural network driving policy transfer,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 9, pp. 3961-3972, Sept. 2020
  3. 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, vol. 19, no. 13, p. 2983, Jul. 2019.
  4. 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, vol. 4, no. 3, pp. 477–486, 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,” under review for 22nd 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,” 5th 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,” 2020 IEEE Intelligent Vehicles Symposium (IV), pp. 384-390, 2020
  8. C. Tang, J. Chen and M. Tomizuka, “Adaptive probabilistic vehicle trajectory prediction through physically feasible bayesian recurrent neural network,” 2019 International Conference on Robotics and Automation (ICRA), pp. 3846-3852, 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,” 2019 IEEE Intelligent Vehicles Symposium (IV), pp. 1400-1407, 2019
  10. Z. Xu*, C. Tang*, and M. Tomizuka, “Zero-shot deep reinforcement learning driving policy transfer for autonomous vehicles based on robust control,” 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 2865–2871, IEEE, 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,” 2018 IEEE Intelligent Vehicles Symposium (IV), pp. 1651-1658, 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”. 2015 28th IEEE International Conference on Micro Electro Mechanical Systems (MEMS), pp. 459-462, 2015.

Workshop

  1. C. Tang, N. Srishankar, S. Martin and M. Tomizuka, “Explainable autonomous driving with grounded relational inference,” in NeurIPS Workshop on Machine Learning for Autonomous Driving, 2020

The superscript * indicates equal contribution.