Publications
(#) Co-First Authors; (*) Corresponding Authors; [J] Journals; [C] Conferences.
2025
[J22] Symmetry-Informed MARL: A Decentralized and Cooperative UAV Swarm Control Approach for Communication Coverage
Rongye Shi, Xin Yu(*), Yandong Wang, Yongkai Tian, Zhenyu Liu, Wenjun Wu, Xiao-Ping Zhang, and Manuela M. Veloso
IEEE Transactions on Mobile Computing (TMC), 2025. [CCF-A, 中科院1区Top]
-----------------------------------------------------------------------------------------
[J21] Phy-APMR: A Physics-Informed Air Pollution Map Reconstruction Approach with Mobile Crwod-Sensing for Fine-Grained Measurement
Rongye Shi(#), Ji Luo(#), Nan Zhou, Yuxuan Liu, Chaopeng Hong, Xiao-Ping Zhang, and Xinlei Chen(*)
Building and Environment (BAE), 2025. [中科院1区Top]
-----------------------------------------------------------------------------------------
2024
[J20] Estimating and Modeling Spontaneous Mobility Changes during the COVID-19 Pandemic Without Stay-at-Home Orders
Baining Zhao(#), Xuzhe Wang(#), Tianyu Zhang, Rongye Shi, Fengli Xu, Fanhang Man, Erbing Chen, Yang Li, Yong Li, Tao Sun, and Xinlei Chen(*)
Humanities and Social Sciences Communications (HSSC), 2024. [Nature Portfolio Journal (Nature子刊)]
-----------------------------------------------------------------------------------------
[J19] ELAKT: Enhancing Locality for Attentive Knowledge Tracing
Yanjun Pu, Fang Liu, Rongye Shi(*), Haitao Yuan(*), Ruibo Chen, Tianhao Peng, and Wenjun Wu(*)
ACM Transactions on Information Systems (ACM TIOS), 2024. [CCF-A]
-----------------------------------------------------------------------------------------
[C17] AdaptAUG: Adaptive Data Augmentation Framework for Multi-Agent Reinforcement Learning
Xin Yu, Yongkai Tian, Li Wang, Pu Feng, Wenjun Wu, and Rongye Shi(*)
IEEE ICRA, 2024. [CAA-A, CCF-B]
-----------------------------------------------------------------------------------------
[C16] Leveraging Partial Symmetry for Multi-Agent Reinforcement Learning
Xin Yu, Rongye Shi(*), Pu Feng, Yongkai Tian, Simin Li, Shuhao Liao, and Wenjun Wu
AAAI, 2024. (Supplementary here) [CCF-A]
-----------------------------------------------------------------------------------------
[J18] Safe and Efficient Multi-Agent Collision Avoidance With Physics-Informed Reinforcement Learning
Pu Feng, Rongye Shi, Size Wang, Junkang Liang, Xin Yu, Simin Li, and Wenjun Wu(*)
IEEE Robotics and Automation Letters (RA-L), 2024. [中科院2区, CAAI-B]
-----------------------------------------------------------------------------------------
[J17] TALKER: A Task-Activated Language Model based Knowledge-Extension Reasoning System
Jiabin Lou, Rongye Shi, Yuxin Lin, Qunbo Wang, and Wenjun Wu(*)
IEEE Robotics and Automation Letters (RA-L), 2024. [中科院2区, CAAI-B]
-----------------------------------------------------------------------------------------
[C15] Hierarchical Consensus-Based Multi-Agent Reinforcement Learning for Multi-Robot Cooperation Tasks
Pu Feng, Junkang Liang, Size Wang, Xin Yu, Xin Ji, Yiting Chen, Kui Zhang, Rongye Shi, and Wenjun Wu(*)
IEEE/RSJ IROS, 2024. [CAA-A]
-----------------------------------------------------------------------------------------
[C14] Exploiting Hierarchical Symmetry in Multi-Agent Reinforcement Learning
Yongkai Tian, Xin Yu, Yirong Qi, Li Wang, Pu Feng, Wenjun Wu, Rongye Shi, and Jie Luo(*)
ECAI, 2024. [CCF-B]
-----------------------------------------------------------------------------------------
[C13] Synaptic Weight Optimization for Oscillatory Neural Networks: A Multi-Agent RL Approach
Shuhao Liao, Xuehong Liu, Wenjun Wu, Rongye Shi(*), Junyu Zhang, and Haopeng Wang
The IEEE International Conference on Agents (ICA), 2024. [EI]
-----------------------------------------------------------------------------------------
[J16] (in Chinese) 基于情境化神经算子的空气动力学风阻预测
宋琪,陈天宇,王子铭,金圣凯,高崇涵,石荣晔(*),周号益,李建欣(*)
人工智能 (AI-View), 2024.
-----------------------------------------------------------------------------------------
2023
[C12] ESP: Exploiting Symmetry Prior for Multi-Agent Reinforcement Learning
Xin Yu, Rongye Shi(*), Pu Feng, Yongkai Tian, Jie Luo, and Wenjun Wu
ECAI, 2023. (Supplementary here) [CCF-B]
-----------------------------------------------------------------------------------------
[C11] Air-M: A Visual Reality Many-Agent Reinforcement Learning Platform for Large-Scale Aerial Unmanned System
Jiabin Lou, Wenjun Wu, Shuhao Liao, and Rongye Shi(*)
IEEE/RSJ IROS, 2023. [CAA-A]
-----------------------------------------------------------------------------------------
[J15] Energy Harvest of Multiple Smart Sensors With Real-Time Fault-Detection
Chen Hou, Rongye Shi(*), Qilong Huang(*), and Yifang Wang
IEEE Transactions on Automation Science and Engineering (TASE), 2023. [中科院2区, CAA-A+, CCF-B]
-----------------------------------------------------------------------------------------
[J14] Physics-Informed Deep Learning for Traffic State Estimation: A Survey and the Outlook
Xuan Di(*), Rongye Shi, Zhaobin Mo, and Yongjie Fu
Algorithms, 2023. [SCI]
-----------------------------------------------------------------------------------------
[J13] Robust Data Sampling in Machine Learning: A Game-Theoretic Framework for Training and Validation Data Selection
Zhaobin Mo, Xuan Di(*), and Rongye Shi
Games, 2023. [SCI]
-----------------------------------------------------------------------------------------
2022
[J12] A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation
Rongye Shi, Zhaobin Mo, Kuang Huang, Xuan Di(*), and Qiang Du
IEEE Transactions on Intelligent Transportation Systems (TITS), 2022. [中科院1区Top, CAA-A, CCF-B]
-----------------------------------------------------------------------------------------
[J11] TCACNet: Temporal and Channel Attention Convolutional Network for Motor Imagery Classification of EEG-Based BCI
Xiaolin Liu(#), Rongye Shi(#), Qianxin Hui, Susu Xu, Shuai Wang, Rui Na, Ying Sun, Wenbo Ding, Dezhi Zheng(*), and Xinlei Chen(*)
Information Processing and Management (IP&M), 2022. [中科院1区Top, CCF-B]
-----------------------------------------------------------------------------------------
[C10] ST-ICM: Spatial-Temporal Inference Calibration Model for Low Cost Fine-grained Mobile Sensing
Chengzhao Yu(#), Ji Luo(#), Rongye Shi, Xinyu Liu, Fan Dang, and Xinlei Chen(*)
ACM MobiCom, 2022. [CCF-A]
-----------------------------------------------------------------------------------------
[J10] Location Selection for Air Quality Monitoring with Consideration of Limited Budget and Estimation Error
Zhiyong Yu, Huijuan Chang, Zhiwen Yu(*), Bin Guo, and Rongye Shi
IEEE Transactions on Mobile Computing (TMC), 2022. [CCF-A, 中科院1区Top]
-----------------------------------------------------------------------------------------
2021
[C9] Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models
Rongye Shi, Zhaobin Mo, and Xuan Di
AAAI, 2021. [CCF-A]
-----------------------------------------------------------------------------------------
[J9] Improving the On-Vehicle Experience of Passengers through SC-M*: A Scalable Multi-Passenger Multi-Criteria Mobility Planner
Rongye Shi(*), Peter Steenkiste, and Manuela M. Veloso
IEEE Transactions on Intelligent Transportation Systems (TITS), 2021. [中科院1区Top, CAA-A, CCF-B]
-----------------------------------------------------------------------------------------
[C8] TRAMESINO: Traffic Memory System for Intelligent Optimization of Road Traffic Control
Cristian Axenie(#), Rongye Shi(#,*), Daniele Foroni(#), Alexander Wieder(#), Mohamad Al Hajj Hassan(#), Paolo Sottovia(#), Margherita Grossi(#), Stefano Bortoli(#), and Gotz Brasche
Advanced Analytics and Learning on Temporal Data: 6th ECML PKDD Workshop, AALTD, 2021. [EI]
-----------------------------------------------------------------------------------------
[C7] OBELISC: Oscillator-Based Modelling and Control Using Efficient Neural Learning for Intelligent Road Traffic Signal Calculation
Cristian Axenie(#), Rongye Shi(#,*), Daniele Foroni(#), Alexander Wieder(#), Mohamad Al Hajj Hassan(#), Paolo Sottovia(#), Margherita Grossi(#), Stefano Bortoli(#), and Gotz Brasche
ECML-PKDD, 2021. [CCF-B]
-----------------------------------------------------------------------------------------
[J8] A Physics-Informed Deep Learning Paradigm for Car-Following Models
Zhaobin Mo, Rongye Shi, and Xuan Di(*)
Transportation Research Part C: Emerging Technologies, 2021. [中科院1区Top, CAA-A]
-----------------------------------------------------------------------------------------
[J7] A Survey on Autonomous Vehicle Control in the Era of Mixed-Autonomy: From Physics-Based to AI-Guided Driving Policy Learning
Xuan Di(*), and Rongye Shi
Transportation Research Part C: Emerging Technologies, 2021. [中科院1区Top, CAA-A]
-----------------------------------------------------------------------------------------
[J6] Using Naturalistic Driving Data to Predict Mild Cognitive Impairment and Dementia: Preliminary Findings from the Longitudinal Research on Aging Drivers (LongROAD) Study
Xuan Di, Rongye Shi, Carolyn DiGuiseppi, David W. Eby, Linda L. Hill, Thelma J. Mielenz, Lisa J. Molnar, David Strogatz, Howard F. Andrews, Terry E. Goldberg, Barbara H. Lang, Minjae Kim, and Guohua Li(*)
Geriatrics, 2021. [SCI] (Reported by Forbes and ScienceDaily)
-----------------------------------------------------------------------------------------
Before 2020
[J5] An LSTM-Based Autonomous Driving Model Using a Waymo Open Dataset
Zhicheng Li, Zhihao Gu, Xuan Di, and Rongye Shi(*)
Applied Sciences (Appl. Sci.), 2020. [SCI Q2]
---------------------------------------------------------------------------------------
[J4] SC-M*: A Multi-Agent Path Planning Algorithm with Soft-Collision Constraint on Allocation of Common Resources
Rongye Shi(*), Peter Steenkiste(*), and Manuela M. Veloso(*)
Applied Sciences (Appl. Sci.), 2019. [SCI Q2]
-----------------------------------------------------------------------------------------
[C6] Generating Synthetic Passenger Data through Joint Traffic-Passenger Modeling and Simulation
Rongye Shi, Peter Steenkiste, and Manuela Veloso
IEEE ITSC, 2018. (I am a Co-Chair for a Data Mining Session!) [CAA-A]
-----------------------------------------------------------------------------------------
[C5] Second-Order Destination Inference using Semi-Supervised Self-Training for Entry-Only Passenger Data
Rongye Shi, Peter Steenkiste, and Manuela Veloso
BDCAT, 2017. (received NSF Student Travel Award) [EI]
------------------------------------------------------------------------------------------
[C4] LightNN: Filling the Gap between Conventional Deep Neural Networks and Binarized Networks
Ruizhou Ding, Zeye Liu, Rongye Shi, Diana Marculescu, and R. D. (Shawn) Blanton
GLSVLSI, 2017. (Best Paper Award) [CCF-C]
------------------------------------------------------------------------------------------
[C3] On the Design of Phase Locked Loop Oscillatory Neural Networks: Mitigation of Transmission Delay Effects
Rongye Shi, Thomas Jackson, Brian Swenson, Soummya Kar, and Lawrence Pileggi,
IJCNN, 2016. [CCF-C]
----------------------------------------------------------------------------------------
[J3] Implementing Delay Insensitive Oscillatory Neural Networks Using CMOS and Emerging Technology
Thomas Jackson(*), Rongye Shi, Abhishek A. Sharma, James A. Bain, Jeffrey A. Weldon, and Lawrence Pileggi,
Analog Integrated Circuits and Signal Processing (AICSP), 2016. [SCI]
------------------------------------------------------------------------------------------
Before 2015
[C2] Digital-Locking Optically Pumped Cesium Magnetometer
Rongye Shi, Chang Liu, Sheng Zhou, and Yanhui Wang,
EFTF, 2014. [EI]
-------------------------------------------------------------------
[C1] An Optically Detected Cesium Beam Frequency Standard with Magnetic State Selection
Chang Liu, Rongye Shi, Yanhui Wang, Shuqin Liu, and Taiqian Dong,
EFTF, 2014. [EI]
------------------------------------------------------------------------------------------
[J2] (in Chinese) Study on Sensitivity-Related Parameters of DFB Laser-Pumped Cesium Atomic Magnetometer
Gu Yuan, Shi Rong-Ye, and Wang Yan-Hui(*)
Acta Physica Sinica (Acta Phys. Sin.), 2014. [SCI]
------------------------------------------------------------------------------------------
[J1] Analysis of Influence of RF Power and Buffer Gas Pressure on Sensitivity of Optically Pumped Cesium Magnetometer
Shi Rong-Ye, and Wang Yan-Hui(*)
Chinese Physics B (Chin. Phys. B), 2013. [SCI]
Note:
1) CCF-A/B/C: China Computer Federation (中国计算机学会) recommended journals/conferences Rank A/B/C;
2) CAA-A+/A/B/C: Chinese Association of Automation (中国自动化学会) recommended journals/conferences Rank A+/A/B/C;
3) CAAI-A/B/C: Chinese Association for Artificial Intelligence (中国人工智能学会) recommended journals/conferences Rank A/B/C.