吕宜生-中国科学院大学-UCAS
[中文]
[English]
研究领域
招生信息
教育背景
工作经历
获奖情况
学术论文
基本信息
吕宜生 中国科学院自动化研究所复杂系统管理与控制国家重点实验室研究员电子邮件： yisheng.lv@ia.ac.cn, yisheng.casia@gmail.com通信地址： 北京市海淀区中关村东路95号智能化大厦1111房间邮政编码： 100190
研究领域
（1）机器学习，智能控制，平行学习，数据挖掘（2）无人驾驶，智能交通（3）人类移动性，城市模拟
招生信息
欢迎攻读硕士学位、博士学位、博士后或实习生的同学联系我。招非全日制硕士生/实习生，在读本科大三以上/硕士/博士，要求数学和计算机编程基础好，方向为人工智能与无人驾驶/智能交通/城市模拟
教育背景
2007-09--2010-07 中国科学院自动化研究所 博士2005-09--2007-07 哈尔滨工业大学 硕士2001-09--2005-07 哈尔滨工业大学 本科
工作经历
2010-07至今，中国科学院自动化研究所复杂系统管理与控制国家重点实验室，助理研究员、副研究员、研究员2014-02--2015--02，Northwestern University，Visiting Scholar
学术兼职
Associate Editor, IEEE Transactions on Intelligent Transportation SystemsAssociate Editor, IEEE Intelligent Transportation Systems Magazine自动化学报编委智能科学与技术学报编委Guest Editor, IEEE智能交通系统汇刊专刊“Big data and AI for computational transportation in the cyber-physical-social space”Guest Editor, IEEE智能交通系统汇刊专刊“Intelligent transportation systems empowered by AI technologies”Guest Editor, IEEE计算社会系统专刊“Augmenting Urban Brain with Visual and Social Intelligence”客座编委, 自动化学报专刊“智能轨道交通系统”IEEE智能交通学会理事会成员（BoG）中国自动化学会综合智能交通专委会委员IFAC Technical Committee on Transportation Systems, Member
获奖情况
2018 The George N. Saridis Best Transactions Paper Award of IEEE Transactions on Intelligent Transportation Systems2018《IEEE/CAA Journal of Automatica Sinica》钱学森论文奖2018《自动化学报》优秀论文奖2020中国自动化学会自然科学一等奖2018中国自动化学会科学技术进步奖特等奖2019北京市科学技术进步奖二等奖2015 IEEE智能交通杰出应用奖2021 The Outstanding Associate Editor Award of IEEE Intelligent Transportation Systems Magazine
学术论文
[1] Yisheng Lv, Yanjie Duan, Wenwen Kang, Zhengxi Li, Fei-Yue Wang. Traffic Flow Prediction With Big Data: A Deep Learning Approach. IEEE Transactions on Intelligent Transportation Systems, 2015, 16: 865–873. [2] Li Li, Yisheng Lv, Fei-Yue Wang. Traffic Signal Timing Via Deep Reinforcement Learning. IEEE/CAA Journal of Automatica Sinica,2016,3(3): 247-254.[3] Zhishuai Li, Gang Xiong, Zebing Wei, Yisheng Lv, Noreen Anwar and Fei-Yue Wang. A Semi-supervised End-to-end Framework for Transportation Mode Detection by Using GPS-enabled Sensing Devices. IEEE Internet of Things Journal, 2022, 9 (10), 7842-7852. (Corresponding Author) [4] Zhishuai Li, Gang Xiong, Yonglin Tian, Yisheng Lv, Yuanyuan Chen, Pan Hui, Xiang Su. A Multi-Stream Feature Fusion Approach for Traffic Prediction. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(2): 1456-1466 (Corresponding Author) [5] Chizhan Zhang, Fenghua Zhu, Xiao Wang, Leilei Sun, Haina Tang and Yisheng Lv. Taxi Demand Prediction Using Parallel Multi-Task Learning Model. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(2): 794-803. (Corresponding Author) [6] Wei Zhang, Fenghua Zhu, Yisheng Lv, Chang Tan, Wen Liu, XinZhang, Fei-Yue Wang. AdapGL: An Adaptive Graph Learning Algorithm for Traffic Prediction Based on Spatiotemporal Neural Networks. Transportation Research Part C: Emerging Technologies, 2022, 139: 103659. (Corresponding Author) [7] Zhishuai Li, Gang Xiong, Zebing Wei, Yu Zhang, Meng Zheng, Xiaoli Liu, Sasu Tarkoma, Min Huang, Yisheng Lv, Chuheng Wu. Trip Purposes Mining From Mobile Signaling Data. IEEE Transactions on Intelligent Transportation Systems, 2021. (Corresponding Author) [8] Peijun Ye, Yuanyuan Chen, Fenghua Zhu, Yisheng Lv, Wanze Lu, Fei-Yue Wang. Bridging the Micro and Macro: Calibration of Agent-Based Model Using Mean-Field Dynamics. IEEE Transactions on Cybernetics, 2021. (Corresponding Author) [9] Chizhan Zhang, Fenghua Zhu, Yisheng Lv, Peijun Ye, Fei-Yue Wang. MLRNN: Taxi Demand Prediction Based on Multi-Level Deep Learning and Regional Heterogeneity Analysis. IEEE Transactions on Intelligent Transportation Systems, 2021. (Corresponding Author) [10] Li Li, Can Zhao, Xiao Wang, Zhiheng Li, Long Chen, Yisheng Lv, Nan-Ning Zheng, Fei-Yue Wang. Three Principles to Determine the Right-of-Way for AVs: Safe Interaction With Humans. IEEE Transactions on Intelligent Transportation Systems, 2021. [11] Siqi Fan, Fenghua Zhu, Shichao Chen, Hui Zhang; Bin Tian, Yisheng Lv, Fei-Yue Wang. FII-CenterNet: An Anchor-free Detector with Foreground Attention for Traffic Object Detection. IEEE Transactions on Vehicular Technology, 2021. [12] Yuanyuan Chen, Hongyu Chen, Peijun Ye, Yisheng Lv, Fei-Yue Wang. Acting as A Decision Maker: Traffic-Condition- Aware Ensemble Learning for Traffic Flow Prediction. IEEE Transactions on Intelligent Transportation Systems, 2020. (Corresponding Author) [13] Xueliang Zhao, Zhishuai Li, Yu Zhang and Yisheng Lv. Discover Trip Purposes from Cellular Network Data with Topic Modelling. IEEE Intelligent Transportation Systems Magazine, 2020. (Corresponding Author) [14] Peijun Ye, Bin Tian, Yisheng Lv, Qijie Li and Fei-Yue Wang. On Iterative Proportional Updating: Limitations and Improvements for General Population Synthesis. IEEE Transactions on Cybernetics, 2020. (Corresponding Author) [15] Fenghua Zhu, Yisheng Lv, Yuanyuan Chen, Xiao Wang, Gang Xiong and Fei-Yue Wang. Parallel Transportation Systems: Toward IoT-Enabled Smart Urban Traffic Control and Management. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(10): 4063-4071. (Corresponding Author) [16] Yuanyuan Chen, Yisheng Lv, Fei-Yue Wang. Traffic Flow Imputation Using Parallel Data and Generative Adversarial Networks. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(4): 1624-1630. (Corresponding Author) [17] 段艳杰，吕宜生，张杰，赵学亮，王飞跃. 深度学习在控制领域的研究现状与展望. 自动化学报, 2016, 42(5): 643-654. [18] Yisheng Lv, Xiqiao Zhang, Wenwen Kang, Yanjie Duan. Managing Emergency Traffic Evacuation with a Partially Random Destination Allocation Strategy: A Computational-Experiment-Based Optimization Approach. IEEE Transactions on Intelligent Transportation Systems, 2015, 16: 2182–2191. [19] Xiaoyu Chen, Gang Xiong, Yisheng Lv, Yuanyuan Chen, Bing Song, Fei-Yue Wang. A Collaborative Communication-Qmix Approach for Large-scale Networked Traffic Signal Control. 2021 IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021: 3450-3455. [20] Zebing Wei, Zhishuai Li, Chunxiang Wang, Yuanyuan Chen, Qinghai Miao, Yisheng Lv, Fei-Yue Wang. Recurrent Attention Unit: A Simple and Effective Method for Traffic Prediction. 2021 IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021: 1272-1277. (Corresponding Author) [21] Siqi Fan, Qiulei Dong, Fenghua Zhu, Yisheng Lv, Peijun Ye, Fei-Yue Wang. SCF-Net: Learning Spatial Contextual Features for Large-scale Point Cloud Segmentation. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2021: 14504-14513.
2013 中国科学院大学，网络信息中心.