Zhengyang Zhou @ DiLab, USTC
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周正阳 特任副研究员 细节决定成败，创新源于积累！ |
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Biography
I was born in Taizhou, Jiangsu Pronvince. I received my B.Sc. degree in School of IoT Engineering in June 2018 from Jiangnan University. In the same year, I was admitted to study for a M.Sc. degree in School of Computer Science and Technology, University of Science and Technology of China without entrance examination. From Sept. 2020, I started my Ph.D. degree under the supervision of Professor Yang Wang. I received my PhD degree of computer science in June, 2023 at USTC.
My research interests include but not limited to Machine learning, Spatiotemporal data mining, Traffic data mining. Our research results have been published on top conferences, e.g., KDD, NeurIPS, ICLR, WWW, AAAI, and top journals (transactions) e.g., IEEE TKDE, IEEE TMC, IEEE TVT.
Chinese version of Biography
周正阳，中国科大软件学院/苏州高等研究院特任副研究员。周正阳于2023年6月在中国科学技术大学计算机科学与技术系获“计算机软件与理论”博士学位，主要研究领域是时空数据挖掘与城市计算，致力于提升深度时空学习模型精准性、可靠性和泛化性，赋能交通预测、城市安全、污染治理等领域，推动城市治理科学化与现代化。 近五年来，周正阳博士共发表高水平学术论文20余篇，其中包括第一/通讯作者CCF-A类会议/期刊（KDD、AAAI、WWW、TMC、TKDE）、高水平IEEE汇刊（IEEE TVT）及机器学习领域顶级会议ICLR、中文CCF-A类期刊（电子学报）等A类成果十余篇，以及CCF-B类（数据挖掘领域顶级会议SDM、WSDM）共3篇。截至目前，周正阳博士已作为审稿人服务于包括CVPR、AAAI、ICCV、ICML、KDD等在内的CCF-A类会议10余次，其谷歌学术引用近200次，H-index=7。 攻读博士学位期间，周正阳获中国科学院院长奖（优秀奖）、ACM SIGSPATIAL中国分会优博奖提名、中国科大优秀博士学位论文提名、研究生国家奖学金、中国科大-姑苏优秀学生奖学金特等奖、中国科大-国睿奖学金等荣誉及奖学金。此外，他曾于2020年获得了之江实验室“之江国际青年人才基金”资助并顺利结题。目前，周正阳博士已全职加入中国科大软件学院/苏州高等研究院。Exciting News
[2023.07] One paper on human mobility mining and forecasting has been accepted by IEEE TMC!
[2023.06] I will join School of Software Enginnering, USTC as the Associate Researcher in June 2023！ Diverse cooperation from both academia and industria are welcome.
[2023.05] Four papers are accepted by Top conference SIGKDD!
Education
2020.09 ~ 2023.06
PhD Candidate: Computer Science, School of Computer Science and Technology, University of Science and Technology of China.2018.09 ~ 2020.06
M.Sc. student: Computer Science, School of Computer Science and Technology, University of Science and Technology of China.2014.09 ~ 2018.06
B.Eng. student: IoT Engineering, School of IoT Engineering, Jiangnan University.
Research Interests
We focus on four aspects regarding both advanced deep learning techniques and human-centered computing.
– Fundamental learning theory for spatiotemporal data forecasting (eg., data property discovery, new designs of GNNs, fairness in learning process)
– Model generalization and parameter-efficient transfer, initialized general ST learning (e.g., cross-task model adaptation and transfer)
– ST data-driven urban evolution （e.g., prediction and planning on functional regions and social connections）
– AI for molecular science (e.g., prediction on molecular interactions, molecular property prediction, and Retrosynthesis)
Chinese version of Research Interests
我们从人工智能技术与“以人为中心”的应用场景出发，主要聚焦于以下四个方面：
Publications (* indicates the (joint) corresponding author.)
Journal Articles
1. Zhengyang Zhou, Kuo Yang, Yuxuan Liang, Binwu Wang, Hongyang Chen, Yang Wang*. Predicting collective human mobility via countering spatiotemporal heterogeneity. IEEE Transactions on Mobile Computing, IEEE TMC (CCF-A, IF= 7.9), Accepted.
2. Zhengyang Zhou, Yang Wang*, Xike Xie, et,al. “ Foresee Urban Sparse Traffic Accidents: A Spatiotemporal Multi-Granularity Perspective.” IEEE Transactions on Knowledge and Data Engineering, (TKDE), 2021 (CCF Rank A, IF = 6.977)，[Code],
3. Yang Wang, Zhengyang Zhou, Kai Liu, et,al. “Large-Scale Intelligent Taxicab Scheduling: A Distributed and Future-Aware Approach.” IEEE Transactions on Vehicular Technology (TVT), 2020 (JCR Q1, IF = 5.978)
4. 周正阳，刘浩，王琨，王鹏焜，王旭，汪炀*， 基于教师-学生时空半监督网络的城市事件预测方法. 电子学报, 已录用.
5. Pengkun Wang, Chuancai Ge, Zhengyang Zhou, Xu Wang, Yuantao Li, Yang Wang*. “ Joint Gated Co-attention Based Multi-modal Networks for Subregion House Price Prediction.” IEEE Transactions on Knowledge and Data Engineering, (TKDE), 2021 (CCF Rank A, IF = 6.977)
6. Wenjie Du, Lianliang Chen, Haoran Wang, Ziyang Shan, Zhengyang Zhou, Wenwei Li*, Yang Wang*. Deciphering Urban Traffic Impacts on Air Quality by Deep Learning and Emission Inventor, Journal of Environmental Sciences, (JESC), 2022.
7. Wang Kun, Zhengyang Zhou, Xu Wang, Pengkun Wang, Qi Fang, Yang Wang*, A2DJP: A Two Graph-based Component Fused Learning Framework for Urban Anomaly Distribution and Duration Joint-Prediction. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
8. Wang Pengkun, Chaochao Zhu, Xu Wang, Zhengyang Zhou, Guang Wang, Yang Wang*, Inferring Intersection Traffic Patterns with Sparse Video Surveillance Information: An ST-GAN method. IEEE Transactions on Vehicular Technology (TVT), 2022.
Conference Papers
1. Zhengyang Zhou, Kuo Yang, Wei Sun, Yang Wang*, et, al. “Towards Learning in Grey Spatiotemporal Systems: A Prophet to Non-consecutive Spatiotemporal Dynamics.” SDM 2023 (CCF Rank B)
2. Zhengyang Zhou, Qihe Huang, Gengyu Lin, Kuo Yang, Lei Bai, Yang Wang*, “ GReTo: Remedying dynamic graph topology-task discordance via target homophily.” The International Conference on Learning Representations. (ICLR), 2023.
3. Zhengyang Zhou, Yang Wang*, Xike Xie, et,al. “STUaNet: Understanding uncertainty in spatiotemporal collective human mobility.” Web Conference 2021 (formerly known as WWW) (CCF Rank A)
4. Zhengyang Zhou , Yang Wang*, Xike Xie, et,al. “RiskOracle: A Minute-level Citywide Traffic Accident Forecasting Framework.” 2020 34th AAAI, 2020. (CCF Rank A)
5. Zhengyang Zhou, Qihe Huang, Kuo Yang, Kun Wang, Xu Wang, Yudong Zhang, Yuxuan Liang, Yang Wang*. "Maintaining the status quo: Capturing invariant relations for OOD spatiotemporal learning." In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023.
6. Zhengyang Zhou, Jiahao Shi, Hongbo Zhang, Qiangyu Chen, Xu Wang*, Hongyang Chen, Yang Wang. CreST: A Credible Spatiotemporal Learning Framework for Uncertainty-aware Traffic Forecasting. The 17th ACM International Conference Web Search and Data Mining, 2024.
7. Kuo Yang, Zhengyang Zhou*, Wei Sun, Pengkun Wang, Xu Wang, Yang Wang*. EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation. The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023.
8. Qihe Huang, Lei Shen, Ruixin Zhang, Shouhong Ding, Binwu Wang, Zhengyang Zhou*, Yang Wang*. CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement. The 37th Conference on Neural Information Processing Systems, (NeurIPS), 2023.
9. Yutong Xia, Yuxuan Liang*, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann. Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment. The 37th Conference on Neural Information Processing Systems, (NeurIPS), 2023.
10. Yudong Zhang, Binwu Wang, Ziyang Shan, Zhengyang Zhou*, Yang Wang*, CMT-Net: A Mutual Transition Aware Framework for Taxicab Pick-ups and Drop-offs Co-Prediction, The Fifteenth International Conference on Web Search and Data Mining, (WSDM), 2022 (CCF Rank B).
11. Xu Wang, Lianliang Chen, Hongbo Zhang, Pengkun Wang, Zhou Zhengyang, Yang Wang*. A Multi-graph Fusion Based Spatiotemporal Dynamic Learning Framework. ACM International Conference on Web Search and Data Mining, 2023. (CCF Rank B)
12. Kangjia Shao, Yang Wang*, Zhengyang Zhou, Xike Xie, et,al. “TrajForesee: How limited detailed trajectories enhance large-scale sparse information to predict vehicle trajectories?” 2021 37th IEEE ICDE, 2021, Chania, Greece (CCF Rank A)
13. Zhengyang Zhou, “Attention Based Stack ResNet for Citywide Traffic Accident Prediction.” 2019 20th IEEE International Conference on Mobile Data Management (MDM). IEEE, 2019: 369-370. (CCF Rank C)
14. Chuancai Ge, Yang Wang, Xike Xie, Hengchang Liu, Zhengyang Zhou, “An Integrated Model for Urban Subregion House Price Forecasting: A Multi-source Data Perspective.” 2019 IEEE International Conference on Data Mining (ICDM), Beijing, China, 2019, pp. 1054-1059.(CCF Rank B)
15. Wen Zhang, Zhengyang Zhou, Chuaicai Ge, Pengkun Wang, “Data-driven Vehicular Communications in Urban Vehicular Network.” 2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN), Chongqing, China, 2019, pp. 1-8.
16. Zhengyang Zhou, Lianliang Chen, Chaochao Zhu, Pengkun Wang, “Stack ResNet For Short-term Accident Risk Prediction Leveraging Cross-domain Data.” 2019 Chinese Automation Congress (CAC), Hangzhou, China, 2019, pp. 782-787.
Slides of Invited Talks
Materials/Tutoriols for learning spatiotemporal data mining
Projects Undergoing
1. Zhejiang Lab's International Talent Fund for Young Professionals, “Sparse Sensing Oriented Urban Spatiotemporal Data Mining,”（之江国际青年人才基金-面向稀疏感知的城市时空数据挖掘） CNY 30,000 grant, Jan. 2021 to Dec. 2021 项目主持人, 已结题.
2. Natural Science Foundation of China (NSFC) General Program, “Research on key supporting technologies of urban intelligent driving assistance,”（国家自然科学基金面上项目-面向多车协同智能辅助驾驶的若干关键支撑技术研究） Project number: 62072427, CNY 580,000 grant, Jan. 2021 to Dec. 2024 技术骨干
3. Anhui Science Foundation for Distinguished Youth Scholars, “Research on Real-time and Reliable Vehicular Networking Technologies for Urban Intelligent Driving,”（安徽省自然科学基金杰青项目-面向城市智能驾驶的车联网实时可靠通信关键技 术研究） Project number: 1908085J24, CNY 400,000 grant, Jul. 2019 to Jun. 2022 技术骨干
Teaching/Academic Services
2024 Review invitation from The web conference 2024/CVPR 2024 (PC member, Reviewer)
2023 Review invitation from NeurIPS/ECAI/ECML/KDD 2023 /CVPR 2023/ICCV 2023 (PC member, Reviewer)
2022 Review invitation from CVPR 2022 /ECCV 2022/ICML 2022 (PC member, Reviewer)
2021 Review invitation from ICCV 2021 (PC member, Reviewer)
2021 Review invitation from CVPR 2021 (Reviewer)
2021 Serve as a PC member for AAAI 2021 (Reviewer)
2020 Serve as a TA for Algorithm Design and Analysis (Autumn 2021) , School of Computer Science and Technology, USTC
2020 Serve as a TA for Advanced Algorithm (Spring 2020) , School of Software Engineering, USTC
2020 IEEE Student Member
2019，2020 AAAI Student Member
Awards
2023 Excellent Doctoral Dissertation of ACM SIGSPATIAL CHINA, Nomination Award（ACM SIGSPATIAL中国分会优博奖 (提名)）
2023 Excellent Doctoral Dissertation of USTC, Nomination Award（中国科学技术大学优秀博士学位论文(提名)）
2023 Chinese Academy of Sciences President's Award - Excellence Award（中国科学院院长奖-优秀奖）
2022 USTC-GuoRui Scholarship（中国科大-国睿奖学金）
2021 Special Award of USTC-GUSU Lab Scholarship（中国科大-姑苏实验室姑苏奖学金特别奖）
2021 Outstanding Volunteer Award of USTC Summer Camp（中国科大夏令营优秀志愿者）
2021 Outstanding Volunteer Award of Suzhou Institute for Advanced Research, USTC （苏州高等研究院优秀志愿者）
2021 First Prize, Yihaijiali Academic Forum for Graduate Students, Jiangnan University （江南大学益海嘉里杯研究生学术论坛一等奖）
2021 Outstanding Achievement Award of Graduate Academic Forum, USTC （研究生学术论坛优秀成果奖）
2020 Scholarship of Suzhou Industry Park, USTC （2020 苏州工业园区奖学金）
2020 National scholarship for Postgraduates, USTC （2020 研究生国家奖学金-计算机科学与技术学院）
2020, 2019, 2018 First-class Scholarship for Outstanding Students, USTC （2018,2019,2020 研究生一等学业奖学金）
2018 Outstanding Communicator in 60th Anniversary of USTC, USTC （中国科大60周年校庆 优秀传播奖）
2018 Outstanding Undergraduate Student, Jiangnan University (江南大学2018届优秀本科毕业生)
2016 Merit Student of Wuxi City, Jiangnan University (无锡市三好学生)
2015 Merit Student of Jiangnan University, Jiangnan University (江南大学三好学生)
Competition Experience
2019 Third Place, National Post-Graduate Mathematical Contest in Modeling, USTC （华为杯研究生数学建模 全国三等奖）
2016 Third Place, China Undergraduate Mathematical Contest in Modeling, JNU （高教社杯大学生数学建模 江苏省三等奖）
Correspondence
Email:
zzy0929@mail.ustc.edu.cn
Laboratory:
Office 216, Sixian Building, West Campus, Suzhou Institute for Advanced Research, USTC
Address1:
188 RenAi Road, Suzhou Industrial Park, Suzhou, Jiangsu, 215123, China
(江苏省苏州市苏州工业园区仁爱路188号, 中国科学技术大学苏州高等研究院西区思贤楼, 215123.)
Address2：West Campus of USTC, 443 Huangshan Road, Hefei 230027, Anhui, China
(安徽省合肥市蜀山区黄山路443号, 中国科学技术大学科技楼西楼1417, 230027.)
Photos and Life
Brief Introduction to data intelligence research center
数据与算法驱动的时空数据挖掘研究面向国民经济与城市发展、国家重大科技前沿及装备制造领域卡脖子关键问题，重点突破城市时空计算、材料构效关系挖掘与逆向合成和工业制造智能管控这三大方面。其中城市时空计算以人为中心，推动城市传感、人类出行与经济活动的信息交互耦合，挖掘人-社会-自然交互影响，形成”数据挖掘-模型预测-智能治理“的城市治理闭环，以自适应时空关联融合与挖掘技术实现城市治理现代化、科学化、精细化，保障城市可持续发展。材料构效关系挖掘与逆向合成聚焦使用图神经网络、蒙特卡洛搜索、化学结构编码等交叉学科技术重点突破有机物分子性质预测、有机分子合成与逆向合成等科学问题，为材料机器科学家提供智力支撑。工业制造智能管控从大科学仪器谱图分析、半导体材料制造、航空航天领域装备装配等卡脖子技术的现实场景出发，通过工业时空数据融合与预测实现异常检测、预测，进而实现制造过程质量补偿与管控，最终形成智能化生产制造的闭环过程。我们基于时空数据挖掘技术从城市计算-工业生产-智能制造三个方面以立体形式为数据驱动的算法理论和科技进步贡献智力。
Job Opportunity and New student Application
**中科大数据智能团队诚招博士后，特任副研究员若干名，研究方向包括时空数据挖掘、AI-Chemistry和面向先进科学仪器的谱图数据分析研究 ****如您对团队研究方向感兴趣，欢迎您直接与团队负责人汪炀 老师联系！ **
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联系邮箱： angyan@ustc.edu.cn zzy0929@mail.ustc.edu.cn