Publications

2024

1. Grounded Relational Inference: Domain Knowledge-driven Explainable Autonomous Driving

   Chen Tang, Nishan Srishankar, Sujitha Martin, and Masayoshi Tomizuka

   IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2024

   presented at 2020 NeurIPS Workshop on Machine Learning for Autonomous Driving

   Bib HTML PDF

   @article{tang2020gri,
     title = {Grounded Relational Inference: Domain Knowledge-driven Explainable Autonomous Driving},
     author = {Tang, Chen and Srishankar, Nishan and Martin, Sujitha and Tomizuka, Masayoshi},
     journal = {IEEE Transactions on Intelligent Transportation Systems (T-ITS)},
     year = {2024},
     note = {presented at 2020 NeurIPS Workshop on Machine Learning for Autonomous Driving}
   }

2. Active Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing

   Tommaso Benciolini, Chen Tang, Marion Leibold, Catherine Weaver, Masayoshi Tomizuka, and Wei Zhan

   IEEE Transactions on Control Systems Technology (T-CST), 2024

   Bib HTML PDF

   @article{benciolini2023active,
     title = {Active Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing},
     author = {Benciolini, Tommaso and Tang, Chen and Leibold, Marion and Weaver, Catherine and Tomizuka, Masayoshi and Zhan, Wei},
     journal = {IEEE Transactions on Control Systems Technology (T-CST)},
     year = {2024},
   }

3. Skill-Critic: Refining Learned Skills for Reinforcement Learning

   Ce Hao*, Catherine Weaver*, Chen Tang, Kenta Kawamoto, Masayoshi Tomizuka, and Wei Zhan

   IEEE Robotics and Automation Letters (RA-L), 2024

   accepted for oral presentation at 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

   Bib HTML PDF Code Website

   @article{hao2023skill,
     title = {Skill-Critic: Refining Learned Skills for Reinforcement Learning},
     author = {Hao*, Ce and Weaver*, Catherine and Tang, Chen and Kawamoto, Kenta and Tomizuka, Masayoshi and Zhan, Wei},
     journal = {IEEE Robotics and Automation Letters (RA-L)},
     year = {2024},
     note = {accepted for oral presentation at 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).}
   }

4. Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration

   Jinning Li, Xinyi Liu, Banghua Zhu, Jiantao Jiao, Masayoshi Tomizuka, Chen Tang, and Wei Zhan

   In IEEE International Conference on Robotics and Automation (ICRA), 2024

   Bib HTML PDF Website

   @inproceedings{li2023gold,
     title = {Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration},
     author = {Li, Jinning and Liu, Xinyi and Zhu, Banghua and Jiao, Jiantao and Tomizuka, Masayoshi and Tang, Chen and Zhan, Wei},
     booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
     year = {2024},
   }

5. Pre-training on Synthetic Driving Data for Trajectory Prediction

   Yiheng Li*, Seth Z Zhao*, Chenfeng Xu, Chen Tang, Chenran Li, Mingyu Ding, Masayoshi Tomizuka, and Wei Zhan

   In EEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024

   Bib HTML PDF

   @inproceedings{li2023pre,
     title = {Pre-training on Synthetic Driving Data for Trajectory Prediction},
     author = {Li*, Yiheng and Zhao*, Seth Z and Xu, Chenfeng and Tang, Chen and Li, Chenran and Ding, Mingyu and Tomizuka, Masayoshi and Zhan, Wei},
     booktitle = {EEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
     year = {2024},
   }

6. Quantifying Agent Interaction in Multi-agent Reinforcement Learning for Cost-efficient Generalization

   Yuxin Chen, Chen Tang, Ran Tian, Chenran Li, Jinning Li, Masayoshi Tomizuka, and Wei Zhan

   In Reinforcement Learning Conference (RLC), 2024

   Preliminary version was presented as an extended abstract at 2024 International Conference on Autonomous Agents and Multi-agent Systems (AAMAS).

   Bib HTML PDF Code

   @inproceedings{chen2023quantifying,
     title = {Quantifying Agent Interaction in Multi-agent Reinforcement Learning for Cost-efficient Generalization},
     author = {Chen, Yuxin and Tang, Chen and Tian, Ran and Li, Chenran and Li, Jinning and Tomizuka, Masayoshi and Zhan, Wei},
     booktitle = {Reinforcement Learning Conference (RLC)},
     year = {2024},
     note = {Preliminary version was presented as an extended abstract at 2024 International Conference on Autonomous Agents and Multi-agent Systems (AAMAS).}
   }

7. Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation

   Yixiao Wang, Chen Tang, Lingfeng Sun, Simone Rossi, Yichen Xie, Chensheng Peng, Thomas Hannagan, Stefano Sabatini, Nicola Poerio, Masayoshi Tomizuka, and Wei Zhan

   In European Conference on Computer Vision (ECCV), 2024

   Bib

   @inproceedings{wang2024OGD,
     title = {Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation},
     author = {Wang, Yixiao and Tang, Chen and Sun, Lingfeng and Rossi, Simone and Xie, Yichen and Peng, Chensheng and Hannagan, Thomas and Sabatini, Stefano and Poerio, Nicola and Tomizuka, Masayoshi and Zhan, Wei},
     booktitle = {European Conference on Computer Vision (ECCV)},
     year = {2024}
   }

8. BeTAIL: Behavior Transformer Adversarial Imitation Learning from Human Racing Gameplay

   Catherine Weaver, Chen Tang, Ce Hao, Kenta Kawamoto, Masayoshi Tomizuka, and Wei Zhan

   IEEE Robotics and Automation Letters (RA-L), 2024

   Bib HTML PDF

   @article{weaver2023betail,
     title = {{BeTAIL}: Behavior Transformer Adversarial Imitation Learning from Human Racing Gameplay},
     author = {Weaver, Catherine and Tang, Chen and Hao, Ce and Kawamoto, Kenta and Tomizuka, Masayoshi and Zhan, Wei},
     journal = {IEEE Robotics and Automation Letters (RA-L)},
     year = {2024},
   }

9. Learning Online Belief Prediction for Efficient POMDP Planning in Autonomous Driving

   Zhiyu Huang, Chen Tang, Chen Lv, Masayoshi Tomizuka, and Wei Zhan

   IEEE Robotics and Automation Letters (RA-L), 2024

   Bib HTML PDF

   @article{huang2023pomdp,
     title = {Learning Online Belief Prediction for Efficient POMDP Planning in Autonomous Driving},
     author = {Huang, Zhiyu and Tang, Chen and Lv, Chen and Tomizuka, Masayoshi and Zhan, Wei},
     journal = {IEEE Robotics and Automation Letters (RA-L)},
     year = {2024},
   }

10. Residual-MPPI: Online Policy Customization for Continuous Control

    Pengcheng Wang*, Chenran Li*, Catherine Weaver, Kenta Kawamoto, Masayoshi Tomizuka, Chen Tang, and Wei Zhan

    arXiv preprint arXiv:2407.00898, 2024

    under double-bline review

    Bib HTML PDF Website

    @article{wang2024residual,
      title = {{Residual-MPPI}: Online Policy Customization for Continuous Control},
      author = {Wang*, Pengcheng and Li*, Chenran and Weaver, Catherine and Kawamoto, Kenta and Tomizuka, Masayoshi and Tang, Chen and Zhan, Wei},
      journal = {arXiv preprint arXiv:2407.00898},
      year = {2024},
      note = {under double-bline review}
    }

11. MEReQ: Max-Ent Residual-Q Inverse RL for Sample-Efficient Alignment from Human Intervetion

    Yuxin Chen*, Chen Tang*, Chenran Li, Ran Tian, Peter Stone, Masayoshi Tomizuka, and Wei Zhan

    arXiv preprint arXiv:2406.16258, 2024

    Bib HTML

    @article{chen2024mereq,
      title = {{MEReQ}: Max-Ent Residual-Q Inverse RL for Sample-Efficient Alignment from Human Intervetion},
      author = {Chen*, Yuxin and Tang*, Chen and Li, Chenran and Tian, Ran and Stone, Peter and Tomizuka, Masayoshi and Zhan, Wei},
      journal = {arXiv preprint arXiv:2406.16258},
      year = {2024},
      html = https://arxiv.org/abs/2406.16258
    }

12. WOMD-Reasoning: A Large-Scale Language Dataset for Interactions and Driving Intentions Reasoning

    Yiheng Li, Chongjian Ge, Chenran Li, Chenfeng Xu, Masayoshi Tomizuka, Chen Tang, Mingyu Ding, and Wei Zhan

    arXiv preprint, 2024

    under review for Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track

    Bib

    @article{li2024womd,
      title = {{WOMD-Reasoning}: A Large-Scale Language Dataset for Interactions and Driving Intentions Reasoning},
      author = {Li, Yiheng and Ge, Chongjian and Li, Chenran and Xu, Chenfeng and Tomizuka, Masayoshi and Tang, Chen and Ding, Mingyu and Zhan, Wei},
      note = {under review for Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track},
      journal = {arXiv preprint},
      year = {2024}
    }

13. CaMP: Causal Motion Predictor for Robust Trajectory Forecasting

    Zizhao Wang*, Chen Tang*, Aolin Xu, Enna Sachdeva, Peter Stone, and Teruhisa Misu

    arXiv preprint, 2024

    under double-blind review

    Bib

    @article{wang2024camp,
      title = {{CaMP}: Causal Motion Predictor for Robust Trajectory Forecasting},
      author = {Wang*, Zizhao and Tang*, Chen and Xu, Aolin and Sachdeva, Enna and Stone, Peter and Misu, Teruhisa},
      journal = {arXiv preprint},
      note = {under double-blind review},
      year = {2024}
    }

14. Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes

    Chen Tang*, Ben Abbatematteo*, Jiaheng Hu*, Rohan Chandra, Roberto Martín-Martín, and Peter Stone

    arXiv preprint, 2024

    under review for Annual Review of Control Robotics and Autonomous Systems

    Bib

    @article{tang2024survey,
      title = {Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes},
      author = {Tang*, Chen and Abbatematteo*, Ben and Hu*, Jiaheng and Chandra, Rohan and Mart{\'i}n-Mart{\'i}n, Roberto and Stone, Peter},
      note = {under review for Annual Review of Control Robotics and Autonomous Systems},
      journal = {arXiv preprint},
      year = {2024}
    }

2023

1. Double-Iterative Gaussian Process Regression for Modeling Error Compensation in Autonomous Racing

   Shaoshu Su, Ce Hao, Catherine Weaver, Chen Tang, Wei Zhan, and Masayoshi Tomizuka

   In 22nd IFAC World Congress (IFAC), 2023

   Bib HTML PDF

   @inproceedings{su2022racing,
     title = {Double-Iterative Gaussian Process Regression for Modeling Error Compensation in Autonomous Racing},
     author = {Su, Shaoshu and Hao, Ce and Weaver, Catherine and Tang, Chen and Zhan, Wei and Tomizuka, Masayoshi},
     booktitle = {22nd IFAC World Congress (IFAC)},
     year = {2023},
   }

2. Editing Driver Character: Socially-Controllable Behavior Generation for Interactive Traffic Simulation

   Wei-Jer Chang*, Chen Tang*, Chenran Li, Yeping Hu, Masayoshi Tomizuka, and Wei Zhan

   IEEE Robotics and Automation Letters (RA-L), 2023

   presented at 2023 CVPR Workshop on Multi-Agent Behavior: Properties, Computation, and Emergence (MABe) and 2024 IEEE International Conference on Robotics and Automation (ICRA)

   Bib HTML PDF

   @article{chang2023scbg,
     author = {Chang*, Wei-Jer and Tang*, Chen and Li, Chenran and Hu, Yeping and Tomizuka, Masayoshi and Zhan, Wei},
     journal = {IEEE Robotics and Automation Letters (RA-L)},
     title = {Editing Driver Character: Socially-Controllable Behavior Generation for Interactive Traffic Simulation},
     year = {2023},
     volume = {},
     number = {},
     pages = {1-8},
     doi = {10.1109/LRA.2023.3291897},
     note = {presented at 2023 CVPR Workshop on Multi-Agent Behavior: Properties, Computation, and Emergence (MABe) and 2024 IEEE International Conference on Robotics and Automation (ICRA)}
   }

3. Residual Q-Learning: Offline and Online Policy Customization without Value

   Chenran Li*, Chen Tang*, Haruki Nishimura, Jean Mercat, Masayoshi Tomizuka, and Wei Zhan

   In Advances in Neural Information Processing Systems (NeurIPS), 2023

   Bib HTML PDF Code Website

   @inproceedings{tang2023residual,
     title = {Residual Q-Learning: Offline and Online Policy Customization without Value},
     author = {Li*, Chenran and Tang*, Chen and Nishimura, Haruki and Mercat, Jean and Tomizuka, Masayoshi and Zhan, Wei},
     booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
     year = {2023},
   }

2022

1. Dealing with the unknown: Pessimistic offline reinforcement learning

   Jinning Li, Chen Tang, Masayoshi Tomizuka, and Wei Zhan

   In Conference on Robot Learning (CoRL), 2022

   Bib HTML PDF

   @inproceedings{jinning2021pessimistic,
     title = {Dealing with the unknown: Pessimistic offline reinforcement learning},
     author = {Li, Jinning and Tang, Chen and Tomizuka, Masayoshi and Zhan, Wei},
     booktitle = {Conference on Robot Learning (CoRL)},
     pages = {1455--1464},
     year = {2022},
     organization = {PMLR},
   }

2. Domain Knowledge Driven Pseudo Labels for Interpretable Goal-Conditioned Interactive Trajectory Prediction

   Lingfeng Sun*, Chen Tang*, Yaru Niu, Enna Sachdeva, Chiho Choi, Teruhisa Misu, Masayoshi Tomizuka, and Wei Zhan

   In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022

   Bib HTML PDF

   @inproceedings{tang2022pseudo,
     title = {Domain Knowledge Driven Pseudo Labels for Interpretable Goal-Conditioned Interactive Trajectory Prediction},
     author = {Sun*, Lingfeng and Tang*, Chen and Niu, Yaru and Sachdeva, Enna and Choi, Chiho and Misu, Teruhisa and Tomizuka, Masayoshi and Zhan, Wei},
     booktitle = {2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
     year = {2022},
     volume = {},
     number = {},
     pages = {13034-13041},
     doi = {10.1109/IROS47612.2022.9982147},
   }

3. Interventional Behavior Prediction: Avoiding Overly Confident Anticipation in Interactive Prediction

   Chen Tang, Wei Zhan, and Masayoshi Tomizuka

   In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022

   Bib HTML PDF

   @inproceedings{tang2022ibp,
     title = {Interventional Behavior Prediction: Avoiding Overly Confident
     Anticipation in Interactive Prediction},
     author = {Tang, Chen and Zhan, Wei and Tomizuka, Masayoshi},
     booktitle = {2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
     year = {2022},
     volume = {},
     number = {},
     pages = {11409-11415},
     doi = {10.1109/IROS47612.2022.9981524},
   }

4. Hierarchical Planning Through Goal-Conditioned Offline Reinforcement Learning

   Jinning Li, Chen Tang, Wei Zhan, and Masayoshi Tomizuka

   IEEE Robotics and Automation Letters (RA-L), 2022

   Bib HTML PDF

   @article{li2022goalRL,
     author = {Li, Jinning and Tang, Chen and Zhan, Wei and Tomizuka, Masayoshi},
     journal = {IEEE Robotics and Automation Letters (RA-L)},
     title = {Hierarchical Planning Through Goal-Conditioned Offline Reinforcement Learning},
     year = {2022},
     volume = {7},
     number = {4},
     pages = {10216-10223},
     doi = {10.1109/LRA.2022.3190100},
   }

5. PreTraM: Self-Supervised Pre-training via Connecting Trajectory and Map

   Chenfeng Xu*, Tian Li*, Chen Tang, Lingfeng Sun, Kurt Keutzer, Masayoshi Tomizuka, Alireza Fathi, and Wei Zhan

   In European Conference on Computer Vision (ECCV), 2022

   Bib HTML PDF Code

   @inproceedings{xu2022PreTraM,
     title = {PreTraM: Self-Supervised Pre-training via Connecting Trajectory and Map},
     author = {Xu*, Chenfeng and Li*, Tian and Tang, Chen and Sun, Lingfeng and Keutzer, Kurt and Tomizuka, Masayoshi and Fathi, Alireza and Zhan, Wei},
     booktitle = {European Conference on Computer Vision (ECCV)},
     year = {2022},
     pages = {34--50},
   }

6. Outracing Human Racers with Model-based Planning and Control for Time-trial Racing

   Ce Hao, Chen Tang, Eric Bergkvist, Catherine Weaver, Liting Sun, Wei Zhan, and Masayoshi Tomizuka

   arXiv preprint arXiv:2211.09378, 2022

   under review for IEEE Transactions on Control Systems Technology (T-CST)

   arXiv Bib PDF

   @article{hao2022outracing,
     title = {Outracing Human Racers with Model-based Planning and Control for Time-trial Racing},
     author = {Hao, Ce and Tang, Chen and Bergkvist, Eric and Weaver, Catherine and Sun, Liting and Zhan, Wei and Tomizuka, Masayoshi},
     journal = {arXiv preprint arXiv:2211.09378},
     year = {2022},
     note = {under review for IEEE Transactions on Control Systems Technology (T-CST)}
   }

7. Designing Explainable Autonomous Driving System for Trustworthy Interaction

   Chen Tang

   PhD Dissertation, 2022

   PhD Advisor: Masayoshi Tomizuka

   Bib

   @article{tang2022designing,
     title = {Designing Explainable Autonomous Driving System for Trustworthy Interaction},
     author = {Tang, Chen},
     journal = {PhD Dissertation},
     year = {2022},
     publisher = {University of California, Berkeley},
     note = {PhD Advisor: Masayoshi Tomizuka}
   }

2021

1. Exploring Social Posterior Collapse in Variational Autoencoder for Interaction Modeling

   Chen Tang, Wei Zhan, and Masayoshi Tomizuka

   In Advances in Neural Information Processing Systems (NeurIPS), 2021

   Bib HTML PDF

   @inproceedings{tang2021social,
     author = {Tang, Chen and Zhan, Wei and Tomizuka, Masayoshi},
     booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
     pages = {8481--8494},
     title = {Exploring Social Posterior Collapse in Variational Autoencoder for Interaction Modeling},
     volume = {34},
     year = {2021}
   }

2020

1. Application Specific System Identification for Model-Based Control in Self-Driving Cars

   Julian M. Salt Ducaju, Chen Tang, and Masayoshi Tomizuka

   In 2020 IEEE Intelligent Vehicles Symposium (IV), 2020

   Bib HTML

   @inproceedings{ducaju2020application,
     title = {Application Specific System Identification for Model-Based Control in Self-Driving Cars},
     author = {Ducaju, Julian M. Salt and Tang, Chen and Tomizuka, Masayoshi},
     booktitle = {2020 IEEE Intelligent Vehicles Symposium (IV)},
     year = {2020},
     organization = {IEEE},
   }

2019

1. A Remote Control Strategy for an Autonomous Vehicle with Slow Sensor Using Kalman Filtering and Dual-Rate Control

   Ángel Cuenca, Wei Zhan, Julián Salt, José Alcaina, Chen Tang, and Masayoshi Tomizuka

   Sensors, 2019

   Bib HTML

   @article{cuenca2019remote,
     title = {A Remote Control Strategy for an Autonomous Vehicle with Slow Sensor Using Kalman Filtering and Dual-Rate Control},
     author = {Cuenca, {\'A}ngel and Zhan, Wei and Salt, Juli{\'a}n and Alcaina, Jos{\'e} and Tang, Chen and Tomizuka, Masayoshi},
     journal = {Sensors},
     volume = {19},
     number = {13},
     pages = {2983},
     year = {2019},
     publisher = {Multidisciplinary Digital Publishing Institute},
   }

2. Toward Modularization of Neural Network Autonomous Driving Policy Using Parallel Attribute Networks

   Zhuo Xu, Haonan Chang, Chen Tang, Changliu Liu, and Masayoshi Tomizuka

   In 2019 IEEE Intelligent Vehicles Symposium (IV), 2019

   Bib HTML

   @inproceedings{xu2019toward,
     title = {Toward Modularization of Neural Network Autonomous Driving Policy Using Parallel Attribute Networks},
     author = {Xu, Zhuo and Chang, Haonan and Tang, Chen and Liu, Changliu and Tomizuka, Masayoshi},
     booktitle = {2019 IEEE Intelligent Vehicles Symposium (IV)},
     pages = {1400--1407},
     year = {2019},
     organization = {IEEE},
   }

3. Disturbance-observer-based tracking controller for neural network driving policy transfer

   Chen Tang*, Zhuo Xu*, and Masayoshi Tomizuka

   IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2019

   Bib HTML

   @article{tang2019disturbance,
     title = {Disturbance-observer-based tracking controller for neural network driving policy transfer},
     author = {Tang*, Chen and Xu*, Zhuo and Tomizuka, Masayoshi},
     journal = {IEEE Transactions on Intelligent Transportation Systems (T-ITS)},
     volume = {21},
     number = {9},
     pages = {3961--3972},
     year = {2019},
     publisher = {IEEE},
   }

4. Adaptive Probabilistic Vehicle Trajectory Prediction Through Physically Feasible Bayesian Recurrent Neural Network

   Chen Tang, Jianyu Chen, and Masayoshi Tomizuka

   In 2019 International Conference on Robotics and Automation (ICRA), 2019

   Bib HTML PDF

   @inproceedings{tang2019adaptive,
     title = {Adaptive Probabilistic Vehicle Trajectory Prediction Through Physically Feasible Bayesian Recurrent Neural Network},
     author = {Tang, Chen and Chen, Jianyu and Tomizuka, Masayoshi},
     booktitle = {2019 International Conference on Robotics and Automation (ICRA)},
     pages = {3846--3852},
     year = {2019},
     organization = {IEEE},
   }

2018

1. Zero-shot Deep Reinforcement Learning Driving Policy Transfer for Autonomous Vehicles based on Robust Control

   Zhuo Xu*, Chen Tang*, and Masayoshi Tomizuka

   In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), 2018

   Best Student-Paper Runner-up

   Bib HTML PDF

   @inproceedings{xu2018zero,
     title = {Zero-shot Deep Reinforcement Learning Driving Policy Transfer for Autonomous Vehicles based on Robust Control},
     author = {Xu*, Zhuo and Tang*, Chen and Tomizuka, Masayoshi},
     booktitle = {2018 21st International Conference on Intelligent Transportation Systems (ITSC)},
     pages = {2865--2871},
     year = {2018},
     organization = {IEEE},
     note = {Best Student-Paper Runner-up}
   }

2. Continuous Decision Making for On-Road Autonomous Driving under Uncertain and Interactive Environments

   Jianyu Chen, Chen Tang, Long Xin, Shengbo Eben Li, and Masayoshi Tomizuka

   In 2018 IEEE Intelligent Vehicles Symposium (IV), 2018

   Bib HTML PDF

   @inproceedings{chen2018continuous,
     title = {Continuous Decision Making for On-Road Autonomous Driving under Uncertain and Interactive Environments},
     author = {Chen, Jianyu and Tang, Chen and Xin, Long and Li, Shengbo Eben and Tomizuka, Masayoshi},
     booktitle = {2018 IEEE Intelligent Vehicles Symposium (IV)},
     pages = {1651--1658},
     year = {2018},
     organization = {IEEE},
   }

2017

1. A Highly Sensitive Graphene Woven Fabric Strain Sensor for Wearable Wireless Musical Instruments

   Xu Liu, Chen Tang, Xiaohan Du, Shuai Xiong, Siyuan Xi, Yuefeng Liu, Xi Shen, Qingbin Zheng, Zhenyu Wang, Ying Wu, and  others

   Materials Horizons, 2017

   Bib HTML

   @article{liu2017highly,
     title = {A Highly Sensitive Graphene Woven Fabric Strain Sensor for Wearable Wireless Musical Instruments},
     author = {Liu, Xu and Tang, Chen and Du, Xiaohan and Xiong, Shuai and Xi, Siyuan and Liu, Yuefeng and Shen, Xi and Zheng, Qingbin and Wang, Zhenyu and Wu, Ying and others},
     journal = {Materials Horizons},
     volume = {4},
     number = {3},
     pages = {477--486},
     year = {2017},
     publisher = {Royal Society of Chemistry},
   }

2015

1. The Capillary Number Effect on the Capture Efficiency of Cancer Cells on Composite Microfluidic Filtration Chips

   Cong Zhao, Rui Xu, Kui Song, Dayu Liu, Shuo Ma, Chen Tang, Chun Liang, Yitshak Zohar, and Yi-Kuen Lee

   In 2015 28th IEEE International Conference on Micro Electro Mechanical Systems (MEMS), 2015

   Bib HTML

   @inproceedings{zhao2015capillary,
     title = {The Capillary Number Effect on the Capture Efficiency of Cancer Cells on Composite Microfluidic Filtration Chips},
     author = {Zhao, Cong and Xu, Rui and Song, Kui and Liu, Dayu and Ma, Shuo and Tang, Chen and Liang, Chun and Zohar, Yitshak and Lee, Yi-Kuen},
     booktitle = {2015 28th IEEE International Conference on Micro Electro Mechanical Systems (MEMS)},
     pages = {459--462},
     year = {2015},
     organization = {IEEE},
   }