| 2023 | AAAI | Learning to Shape Rewards Using a Game of Two Partners. | David Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez Nieves, Wenbin Song, Feifei Tong, Matthew E. Taylor, Tianpei Yang, Zipeng Dai, Hui Chen, Jiangcheng Zhu, Kun Shao, Jun Wang, Yaodong Yang |
| 2023 | ICDE | Time-Aware Location Prediction by Convolutional Area-of-Interest Modeling and Memory-Augmented Attentive LSTM (Extended abstract). | Chi Harold Liu, Yu Wang, Chengzhe Piao, Zipeng Dai, Ye Yuan, Guoren Wang, Dapeng Wu |
| 2023 | ICDE | Exploring both Individuality and Cooperation for Air-Ground Spatial Crowdsourcing by Multi-Agent Deep Reinforcement Learning. | Yuxiao Ye, Chi Harold Liu, Zipeng Dai, Jianxin Zhao, Ye Yuan, Guoren Wang, Jian Tang |
| 2023 | ICLR | Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints. | David Henry Mguni, Aivar Sootla, Juliusz Ziomek, Oliver Slumbers, Zipeng Dai, Kun Shao, Jun Wang |
| 2022 | CoRL | Socially-Attentive Policy Optimization in Multi-Agent Self-Driving System. | Zipeng Dai, Tianze Zhou, Kun Shao, David Henry Mguni, Bin Wang, Jianye Hao |
| 2022 | INFOCOM | AoI-minimal UAV Crowdsensing by Model-based Graph Convolutional Reinforcement Learning. | Zipeng Dai, Chi Harold Liu, Yuxiao Ye, Rui Han, Ye Yuan, Guoren Wang, Jian Tang |
| 2021 | INFOCOM | Mobile Crowdsensing for Data Freshness: A Deep Reinforcement Learning Approach. | Zipeng Dai, Hao Wang, Chi Harold Liu, Rui Han, Jian Tang, Guoren Wang |
| 2021 | KDD | Energy-Efficient 3D Vehicular Crowdsourcing for Disaster Response by Distributed Deep Reinforcement Learning. | Hao Wang, Chi Harold Liu, Zipeng Dai, Jian Tang, Guoren Wang |
| 2020 | ICDE | Curiosity-Driven Energy-Efficient Worker Scheduling in Vehicular Crowdsourcing: A Deep Reinforcement Learning Approach. | Chi Harold Liu, Yinuo Zhao, Zipeng Dai, Ye Yuan, Guoren Wang, Dapeng Wu, Kin K. Leung |
| 2020 | INFOCOM | Multi-Task-Oriented Vehicular Crowdsensing: A Deep Learning Approach. | Chi Harold Liu, Zipeng Dai, Haoming Yang, Jian Tang |