Zhengyang Zhou @ DiLab, USTC

周正阳 特任副研究员
Dr. Zhengyang Zhou

PhD, Data Intelligence Lab (DILab)
School of Software Enginnering, USTC
Suzhou Institute for Advanced Research, USTC
University of Science and Technology of China, Suzhou 215123, China

Supervisor: Vice Dean of SSE, USTC, Associate Professor Yang Wang

细节决定成败，创新源于积累！

Biography

I received my B.Sc. degree in School of IoT Engineering in June 2018 from Jiangnan University, and received my PhD. degree in June 2023 from School of Computer Science and Technology, University of Science and Technology of China (USTC), under the supervision of Professor Yang Wang. Now, I am an Associate Researcher at Suzhou Institute for Advanced Research/School of Software Engineering, USTC.

My research interests include but not limited to spatiotemporal data mining and urban computing, generalization on graph data learning and spatiotemporal graph learning. We are devoting into promotion on the accuracy, reliability and generalization of spatiotemporal learning models, energizing urban intelligence on diverse domains such as traffic prediction, urban safety and pollution management, thus improving scientific and modern urban governance. Our research results have been published on 30+ top conferences, e.g., KDD, NeurIPS, ICLR, WWW, AAAI, and top journals (transactions) e.g., IEEE TKDE, IEEE TMC, 电子学报, etc. Till now, he has served as a Reviewer for Top conferences including NeurIPS, ICML, ICLR, KDD, CVPR as well as transactions like TKDE.

Now, he has more than 600 citations on google scholar with one 100-citation paper of AAAI 2020. Zhou Zhengyang has been awarded the President's Award of the Chinese Academy of Sciences, nominated for the ACM SIGSPATIAL China Branch Excellent Doctoral Dissertation Award, nominated for the Outstanding Doctoral Dissertation of the University of Science and Technology of China, National Scholarship and other honorary awards. In addition, as the host, he also undertook the "Zhijiang International Young Talent Fund" of Zhijiang Laboratory, the 2023 Open Fund of the State Key Laboratory of Resources and Environmental Information System, and the Youth Innovation Fund of the Software School.

Chinese version of Biography

周正阳，2018年6月在江南大学物联网工程学院获得学士学位，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，现任中国科大软件学院/苏州高等研究院特任副研究员、软件学院人工智能与大数据方向教研室主任。

主要研究领域是时空数据挖掘与城市计算，以及图数据与时空图数据的泛化性研究，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30余篇，其中包括第一/通讯作者CCF A类会议/期刊（NeurIPS、KDD、AAAI、WWW、TMC、TKDE）、高水平IEEE汇刊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。截止目前，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600+，H-index=15，谷歌学术百引论文一篇。周正阳获中国科学院院长奖、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、国家奖学金等荣誉奖励。此外，他还作为主持人承担了之江实验室“之江国际青年人才基金”、资源与环境信息系统国家重点实验室2023年度开放基金、软件学院青年创新基金等重点实验室及院级基金课题。

Exciting News

[2024.09] One paper on spatiotemporal multi-task learning has been accepted as an oral presentation by NeurIPS 2024, Congrats to Zhongchao!

[2024.09] One paper on environment prompt for ST learning has been accepted by NeurIPS 2024, Congrats to Kuo!

[2024.08] One paper on environment modeling for molecular learning has been accepted by BIBM 2024, Congrats to Limin!

[2024.03] One paper on time-series forecasting has been accepted by IJCAI 2024, Congrats to Qihe!

[2024.01] One paper on time-series forecasting has been accepted by AAAI 2024, Congrats to Qihe!

[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] One paper on time-series forecasting has accepted by Top conference NeurIPS 2023!

[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 growing and evolution modeling (e.g., prediction on urban growing and layout planning)

Graph learning-driven 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

Foresee Urban Sparse Traffic Accidents: A Spatiotemporal Multi-Granularity Perspective
Zhengyang Zhou, Yang Wang*, Xike Xie, et al.
IEEE TKDE 2021 (IEEE Transactions on Knowledge and Data Engineering, CCF A, IF = 6.977) [PDF] [Code] [PPT]
Predicting collective human mobility via countering spatiotemporal heterogeneity
Zhengyang Zhou, Kuo Yang, Yuxuan Liang, Binwu Wang, Hongyang Chen, Yang Wang*
IEEE TMC 2023 (IEEE Transactions on Mobile Computing, CCF A, IF = 7.9) [PDF]
基于教师-学生时空半监督网络的城市事件预测方法
周正阳，刘浩，王琨，王鹏焜，王旭，汪炀*
电子学报 2023 (CCF A) [PDF]
A2DJP: A Two Graph-based Component Fused Learning Framework for Urban Anomaly Distribution and Duration Joint-Prediction
Kun Wang, Zhengyang Zhou, Xu Wang, Pengkun Wang, Qi Fang, Yang Wang*
IEEE TKDE 2022 (IEEE Transactions on Knowledge and Data Engineering, CCF A, IF = 6.977) [PDF]
Joint Gated Co-attention Based Multi-modal Networks for Subregion House Price Prediction
Pengkun Wang, Chuancai Ge, Zhengyang Zhou, Xu Wang, Yuantao Li, Yang Wang*
IEEE TKDE 2021 (IEEE Transactions on Knowledge and Data Engineering, CCF A, IF = 6.977) [PDF]
Large-Scale Intelligent Taxicab Scheduling: A Distributed and Future-Aware Approach
Yang Wang, Zhengyang Zhou, Kai Liu, et al.
IEEE TVT 2020 (IEEE Transactions on Vehicular Technology, JCR Q1, IF = 6.8) [PDF]
Modeling Spatio-Temporal Mobility across Data Silos via Personalized Federated Learning
Yudong Zhang, Xu Wang*, Pengkun Wang, Binwu Wang, Zhengyang Zhou, Yang Wang*
IEEE TMC 2024 (IEEE Transactions on Mobile Computing, CCF A) [PDF]
Condition-Guided Urban Traffic Co-Prediction With Multiple Sparse Surveillance Data
Binwu Wang, Pengkun Wang*, Yudong Zhang, Xu Wang, Zhengyang Zhou, Yang Wang*
IEEE TVT 2024 (IEEE Transactions on Vehicular Technology, JCR Q1, IF = 6.8) [PDF]
Latent Gaussian Processes Based Graph Learning for Urban Traffic Prediction
Xu Wang, Pengkun Wang, Binwu Wang, Yudong Zhang, Zhengyang Zhou, Lei Bai, Yang Wang*
IEEE TVT 2023 (IEEE Transactions on Vehicular Technology, JCR Q1, IF = 6.8) [PDF]
Brave the Wind and the Waves: Discovering Robust and Generalizable Graph Lottery Tickets
Kun Wang, Yuxuan Liang*, Xinglin Li, Guohao Li, Bernard Ghanem, Roger Zimmermann, Zhengyang Zhou, Huahui Yi, Yudong Zhang, Yang Wang*
IEEE TPAMI 2023 (IEEE Transactions on Pattern Analysis and Machine Intelligence, CCF A) [PDF]
Deciphering Urban Traffic Impacts on Air Quality by Deep Learning and Emission Inventory
Wenjie Du, Lianliang Chen, Haoran Wang, Ziyang Shan, Zhengyang Zhou, Wenwei Li*, Yang Wang*
JESC 2022 (Journal of Environmental Sciences) [PDF]
Inferring Intersection Traffic Patterns with Sparse Video Surveillance Information: An ST-GAN method
Pengkun Wang, Chaochao Zhu, Xu Wang, Zhengyang Zhou, Guang Wang, Yang Wang*
IEEE TVT 2022 (IEEE Transactions on Vehicular Technology, CCF A, IF = 6.8) [PDF]

Conference Papers

Get Rid of Isolation: A Continuous Multi-task Spatio-Temporal Learning Framework
Zhongchao Yi, Zhengyang Zhou*, Qihe Huang, Yanjiang Chen, Liheng Yu, Xu Wang, Yang Wang*
NeurIPS 2024 (The 38th Annual Conference on Neural Information Processing Systems, CCF A)
Improving Generalization of Dynamic Graph Learning via Environment Prompt
Kuo Yang, Zhengyang Zhou*, Qihe Huang, Limin Li, Yuxuan Liang, Yang Wang*
NeurIPS 2024 (The 38th Annual Conference on Neural Information Processing Systems, CCF A)
EMoNet: An environment causal learning for molecule OOD generalization
Limin Li, Kuo Yang, Wenjie Du, Zhongchao Yi, Zhengyang Zhou*, Yang Wang*
BIBM 2024 (The 2024 IEEE International Conference on Bioinformatics and Biomedicine, CCF B)
HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting
Qihe Huang, Lei Shen, Ruixin Zhang, Jiahuan Cheng, Shouhong Ding, Zhengyang Zhou*, Yang Wang*
AAAI 2024 (The 38th AAAI Conference on Artificial Intelligence, CCF A) [PDF]
LeRet: Language-Empowered Retentive Network for Time Series Forecasting
Qihe Huang, Zhengyang Zhou*, Kuo Yang, Gengyu Lin, Zhongchao Yi, Yang Wang*
IJCAI 2024 (The 33rd International Joint Conference on Artificial Intelligence, CCF A) [PDF]
CreST: A Credible Spatiotemporal Learning Framework for Uncertainty-aware Traffic Forecasting
Zhengyang Zhou, Jiahao Shi, Hongbo Zhang, Qiongyu Chen, Xu Wang*, Hongyang Chen, Yang Wang
WSDM 2024 (The 17th ACM International Conference on Web Search and Data Mining, CCF B) [PDF]
CrossGNN: Confronting Noisy Multivariate Time Series via Cross Interaction Refinement
Qihe Huang, Lei Shen, Ruixin Zhang, Shouhong Ding, Binwu Wang, Zhengyang Zhou*, Yang Wang*
NeurIPS 2023 (The 37th Conference on Neural Information Processing Systems, CCF A) [PDF]
Maintaining the status quo: Capturing invariant relations for OOD spatiotemporal learning
Zhengyang Zhou, Kuo Yang, Wei Sun, Yang Wang*, et al.
KDD 2023 (The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, CCF A) [PDF]
EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation
Kuo Yang, Zhengyang Zhou*, Wei Sun, Pengkun Wang, Xu Wang, Yang Wang*
KDD 2023 (The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, CCF A) [PDF]
Towards Learning in Grey Spatiotemporal Systems: A Prophet to Non-consecutive Spatiotemporal Dynamics
Zhengyang Zhou, Kuo Yang, Wei Sun, Yang Wang*, et al.
SDM 2023 (The 23rd SIAM International Conference on Data Mining, CCF B) [PDF]
GReTo: Remedying Dynamic Graph Topology-Task Discordance via Target Homophily
Zhengyang Zhou, Qihe Huang, Gengyu Lin, Kuo Yang, Lei Bai, Yang Wang*
ICLR 2023 (The Eleventh International Conference on Learning Representations, 清华-A) [PDF]
STUaNet: Understanding Uncertainty in Spatiotemporal Collective Human Mobility
Zhengyang Zhou, Yang Wang*, Xike Xie, et al.
WWW 2021 (The 30th World Wide Web Conference, CCF A) [PDF]
RiskOracle: A Minute-level Citywide Traffic Accident Forecasting Framework
Zhengyang Zhou, Yang Wang*, Xike Xie, et al.
AAAI 2020 (The 34th AAAI Conference on Artificial Intelligence, CCF A) [PDF]
Attention Based Stack ResNet for Citywide Traffic Accident Prediction
Zhengyang Zhou
MDM 2019 (The 20th IEEE International Conference on Mobile Data Management, CCF C) [PDF]
Stack ResNet For Short-term Accident Risk Prediction Leveraging Cross-domain Data
Zhengyang Zhou*, Lianliang Chen, Chaochao Zhu, Pengkun Wang
CAC 2019 (The Chinese Automation Congress) [PDF]
TrajForesee: How limited detailed trajectories enhance large-scale sparse information to predict vehicle trajectories?
Kangjia Shao, Yang Wang*, Zhengyang Zhou, Xike Xie, et al.
ICDE 2021 (The 37th IEEE International Conference on Data Engineering, CCF A) [PDF]
Data-driven Vehicular Communications in Urban Vehicular Network
Wen Zhang, Zhengyang Zhou, Chuancai Ge, Pengkun Wang
ICCSN 2019 (The 11th IEEE International Conference on Communication Software and Networks) [PDF]
STONE: A Spatio-temporal OOD Learning Framework Kills Both Spatial and Temporal Shifts
Binwu Wang, Jiaming Ma*, Pengkun Wang, Xu Wang, Yudong Zhang, Zhengyang Zhou, Yang Wang*
KDD 2024 (The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, CCF A) [PDF]
Scenario-Driven Cyber-Physical-Social System: Intelligent Workflow Generation Based on Capability
Yi Li, Xinkui Zhao*, Chen Chen, Shengye Pang, Zhengyang Zhou, Jianwei Yin
WWW 2024 (The 33rd World Wide Web Conference, CCF A) [PDF]
Adaptive and Interactive Multi-Level Spatio-Temporal Network for Traffic Forecasting
Yudong Zhang, Pengkun Wang, Binwu Wang, Xu Wang, Zhe Zhao, Zhengyang Zhou, Lei Bai*, Yang Wang*
IEEE TITS 2024 (IEEE Transactions on Intelligent Transportation Systems, CCF B) [PDF]
NondBREM: Nondeterministic Offline Reinforcement Learning for Large-Scale Order Dispatching
Hongbo Zhang*, Guang Wang*, Xu Wang, Zhengyang Zhou, Chen Zhang, Zheng Dong, Yang Wang
AAAI 2024 (The 38th AAAI Conference on Artificial Intelligence, CCF A) [PDF]
A twist for graph classification: Optimizing causal information flow in graph neural networks
Zhe Zhao, Pengkun Wang, Haibin Wen, Yudong Zhang, Zhengyang Zhou, Yang Wang*
AAAI 2024 (The 38th AAAI Conference on Artificial Intelligence, CCF A) [PDF]
Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective
Binwu Wang, Pengkun Wang*, Yudong Zhang, Xu Wang, Zhengyang Zhou, Lei Bai, Yang Wang*
AAAI 2024 (The 38th AAAI Conference on Artificial Intelligence, CCF A) [PDF]
Earthfarsser: Versatile spatio-temporal dynamical systems modeling in one model
Hao Wu, Yuxuan Liang, Wei Xiong*, Zhengyang Zhou, Wei Huang, Shilong Wang, Kun Wang*
AAAI 2024 (The 38th AAAI Conference on Artificial Intelligence, CCF A) [PDF]
An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series
Xu Wang, Hongbo Zhang, Pengkun Wang, Yudong Zhang, Binwu Wang, Zhengyang Zhou, Yang Wang*
KDD 2023 (The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, CCF A) [PDF]
Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction
Binwu Wang, Yudong Zhang, Xu Wang, Pengkun Wang, Zhengyang Zhou, Lei Bai*, Yang Wang*
KDD 2023 (The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, CCF A) [PDF]
Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
Yutong Xia, Yuxuan Liang*, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann
NeurIPS 2023 (The 37th Conference on Neural Information Processing Systems, CCF A) [PDF]
CMT-Net: A Mutual Transition Aware Framework for Taxicab Pick-ups and Drop-offs Co-Prediction
Yudong Zhang, Binwu Wang, Ziyang Shan, Zhengyang Zhou*, Yang Wang*
WSDM 2022 (The Fifteenth International Conference on Web Search and Data Mining, CCF B) [PDF]
A Multi-graph Fusion Based Spatiotemporal Dynamic Learning Framework
Xu Wang, Lianliang Chen, Hongbo Zhang, Pengkun Wang, Zhengyang Zhou, Yang Wang*
WSDM 2023 (The Sixteenth International Conference on Web Search and Data Mining, CCF B) [PDF]
An Integrated Model for Urban Subregion House Price Forecasting: A Multi-source Data Perspective
Chuancai Ge, Yang Wang, Xike Xie, Hengchang Liu, Zhengyang Zhou
ICDM 2019 (The 2019 IEEE International Conference on Data Mining, CCF B) [PDF]

Preprint Papers

ComS2T: A complementary spatiotemporal learning system for data-adaptive model evolution
Zhengyang Zhou, Qihe Huang, Binwu Wang, Jianpeng Hou, Kuo Yang, Yuxuan Liang, Yu Zheng, Yang Wang*
Submitted to IEEE TPAMI [PDF]
FairSTG: Countering performance heterogeneity via collaborative sample-level optimization
Gengyu Lin, Zhengyang Zhou*, Qihe Huang, Kuo Yang, Shifen Cheng, Yang Wang*
Submitted to IEEE TMC [PDF]

Slides of Invited Talks

第五届空间数据智能学术会议SpatialDI 2024：时空数据建模与预测方法：从异质性到泛化性

第二届空间数据智能战略研讨会报告：从时空预测泛化性到任务智能

中国科大数据智能实验室招生宣讲

推免经验分享-江南大学至善学院

第二届时空数据研讨会Slides-以人为中心的时空数据计算

中国科大计算机学院研究生学术论坛-稀疏感知的城市时空数据挖掘

Materials/Tutoriols for learning spatiotemporal data mining

浅谈论文阅读与写作

给数据挖掘研究生新生的一封信

GNN中有趣的可研究的话题

Projects Undergoing

Natural Science Foundation of Jiangsu Province-Youth Project 江苏省自然科学基金青年项目，"Study on extrapolation mechanism of spatiotemporal prediction distribution and predictive inference," (时空数据预测分布外泛化机理及推演预测研究)，BK20240460, CNY 200,000 grant, Oct. 2024 to Sep. 2027 项目主持人, 在研.
Youth Innovation Fund of the Software School, "Study on extrapolation mechanism of spatiotemporal prediction distribution and predictive inference,"（中国科大软件学院青年创新基金-时空预测分布外泛化机理及推演预测研究） CNY 200,000 grant, May. 2024 to May. 2026 项目主持人, 在研.
Open Fund of the State Key Laboratory of Resources and Environmental Information System, “Variable spatiotemporal context traffic prediction: Research on key techniques of spatiotemporal prediction generalization,” （资源与环境信息系统国家重点实验室2023年度开放基金-可变时空语境交通推演预测：时空预测泛化关键技术研究） CNY 50,000 grant, Dec. 2023 to Dec. 2025 项目主持人, 在研.
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.
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
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 软件学院专业课《时空计算方法》，2024.04-2024.06，主讲人

2023 软件学院基础课《人工智能》，2023.09-2023.11，主讲人

2024 Review invitation from KDD 2024/Web conference 2024/CVPR 2024/NeurIPS 2024/ICLR 2024/AAAI 2024/IJCAI 2024/ECML-PKDD 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 Member

2019, 2020 AAAI 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@ustc.edu.cn

Laboratory: Office 216, Sixian Building, West Campus, Suzhou Institute for Advanced Research, USTC

Address1: RenAi Road, Suzhou Industrial Park, Suzhou, Jiangsu, 215123, China
(江苏省苏州市苏州工业园区若水路99号, 中国科学技术大学苏州高等研究院若水路校区至德楼1402-2, 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、科研仪器装备领域卡脖子关键问题，重点突破城市时空计算、微观分子智能和面向谱学的人工智能计算方法这三大方面。

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-智能决策优化“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。 微观分子科学挖掘研发新型图神经网络、蒙特卡洛搜索等技术，配合化学结构编码设计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，为智能化学家提供大脑支撑。 科学仪器及装备研制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，通过融合建模时空状态数据与工艺信息，预测实现异常检测、预测，进而实现制备过程质量补偿与管控，最终形成智能化生产制备工艺闭环过程。

我们基于时空数据挖掘技术从城市计算-微观分子智能-先进科研仪器研制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@ustc.edu.cn