| A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to ai-guided driving policy learning X Di, R Shi Transportation Research Part C: Emerging Technologies 125, 103008, 2021 | 147 | 2021 |
| A Physics-Informed Deep Learning Paradigm for Car-Following Models Z Mo, R Shi, X Di Transportation Research Part C: Emerging Technologies 130, 103240, 2021 | 99 | 2021 |
| A physics-informed deep learning paradigm for traffic state and fundamental diagram estimation R Shi, Z Mo, K Huang, X Di, Q Du IEEE Transactions on Intelligent Transportation Systems 23 (8), 11688-11698, 2022 | 85* | 2022 |
| Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models R Shi, Z Mo, X Di Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 540-547, 2021 | 59 | 2021 |
| LightNN: Filling the Gap between Conventional Deep Neural Networks and Binarized Networks R Ding, Z Liu, R Shi, D Marculescu, S Blanton The 27th edition of the ACM Great Lakes Symposium on VLSI (GLSVLSI), 35-40, 2017 | 48 | 2017 |
| An LSTM-Based Autonomous Driving Model Using Waymo Open Dataset Z Li, Z Gu, X Di, R Shi Applied Sciences 10 (6), 2046, 2020 | 47 | 2020 |
| TCACNet: Temporal and channel attention convolutional network for motor imagery classification of EEG-based BCI X Liu, R Shi, Q Hui, S Xu, S Wang, R Na, Y Sun, W Ding, D Zheng, ... Information Processing and Management 59 (5), 103001, 2022 | 31 | 2022 |
| Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook X Di, R Shi, Z Mo, Y Fu Algorithms 16 (6), 305, 2023 | 13 | 2023 |
| SC-M*: A Multi-Agent Path Planning Algorithm with Soft-Collision Constraint on Allocation of Common Resources R Shi, P Steenkiste, MM Veloso Applied Sciences 9 (19), 4037, 2019 | 13 | 2019 |
| Analysis of influence of RF power and buffer gas pressure on sensitivity of optically pumped cesium magnetometer RY Shi, YH Wang Chinese Physics B 22 (10), 100703, 2013 | 13 | 2013 |
| Location Selection for Air Quality Monitoring with Consideration of Limited Budget and Estimation Error Z Yu, H Chang, Z Yu, B Guo, R Shi IEEE Transactions on Mobile Computing 21 (11), 4025-4037, 2021 | 12 | 2021 |
| study on sensitivity-related parameters of distributed feedback laser-pumped cesium atomic magnetometer Y Gu, RY Shi, YH Wang Acta Phys. Sin. 63 (11), 110701, 2014 | 12 | 2014 |
| Using Naturalistic Driving Data to Predict Mild Cognitive Impairment and Dementia: Preliminary Findings from the Longitudinal Research on Aging Drivers (LongROAD) Study X Di, R Shi, C DiGuiseppi, DW Eby, LL Hill, TJ Mielenz, LJ Molnar, ... Geriatrics 6 (2), 45, 2021 | 11 | 2021 |
| On the design of phase locked loop oscillatory neural networks: mitigation of transmission delay effects R Shi, TC Jackson, B Swenson, S Kar, L Pileggi 2016 International Joint Conference on Neural Networks (IJCNN), 2039-2046, 2016 | 9 | 2016 |
| Second-order destination inference using semi-supervised self-training for entry-only passenger data R Shi, P Steenkiste, M Veloso Proceedings of the Fourth IEEE/ACM International Conference on Big Data …, 2017 | 7 | 2017 |
| Implementing delay insensitive oscillatory neural networks using CMOS and emerging technology TC Jackson, R Shi, AA Sharma, JA Bain, JA Weldon, L Pileggi Analog Integrated Circuits and Signal Processing 89, 619-629, 2016 | 7 | 2016 |
| Improving the On-Vehicle Experience of Passengers Through SC-M*: A Scalable Multi-Passenger Multi-Criteria Mobility Planner R Shi, P Steenkiste, MM Veloso IEEE Transactions on Intelligent Transportation Systems 22 (2), 1026-1040, 2021 | 6 | 2021 |
| An optically detected cesium beam frequency standard with magnetic state selection C Liu, R Shi, Y Wang, S Liu, T Dong 2014 European Frequency and Time Forum (EFTF), 175-177, 2014 | 6 | 2014 |
| Generating synthetic passenger data through joint traffic-passenger modeling and simulation R Shi, P Steenkiste, M Veloso 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 5 | 2018 |
| ST-ICM: Spatial-Temporal Inference Calibration Model for Low Cost Fine-grained Mobile Sensing C Yu, J Luo, R Shi, X Liu, F Dang, X Chen MobiCom'22: Proceedings of the 28th Annual International Conference on …, 2022 | 3 | 2022 |
Xuan Sharon DiAssociate Professor at Civil Engineering & Engineering Mechanics, Columbia UniversityVerified email at columbia.edu
