Superintelligence And Industrial Lab

Advancing AI Technologies for Systems Informatics and Data Analytics

We focus on artificial intelligent technologies for system informatics and data analytics, with the objective to develop systematic analytical methodologies for effective inference and performance improvement for complex data. The methodologies comprise both theoretical and applied aspects of statistics and machine learning, including (1) effective information extraction, online change detection and adaptive sampling for high dimensional structured data (2) system control, intelligent overall decision-making, and data fusion techniques with domain knowledge integration for industrial applications such as semiconductor manufacturing, aircraft manufacturing and transportation systems.

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Research Excellence

Advancing superintelligence through cutting-edge AI, machine learning, and deep learning innovations

AI-Powered High-Dimensional Analytics

Leveraging advanced machine learning for effective information extraction, online change detection, and adaptive sampling in high-dimensional structured data. Our AI models handle complex patterns in real-time streaming data with unprecedented accuracy.

Deep Learning & Foundation Models

Developing next-generation deep learning architectures for time series forecasting, multimodal learning, and large language models. Our research spans functional data analysis, tensor decomposition, and specialized domain foundation models.

Intelligent Decision & Control Systems

AI-driven decision-making frameworks integrating game theory, optimization algorithms, and data-driven control for complex networked systems. Our methods combine domain knowledge with reinforcement learning.

Industrial AI Applications

Transforming industries through AI—from semiconductor manufacturing quality prediction to aircraft production optimization, urban transportation intelligence, and supply chain resilience using state-of-the-art machine learning.

Advanced Statistical Learning

Statistical modeling meets AI—developing robust monitoring frameworks for complex systems through Bayesian networks, Gaussian processes, tensor learning, and graph neural networks for anomaly detection and predictive maintenance.

Graph & Network Intelligence

Pioneering graph relational learning and network analysis using GNNs for spatiotemporal prediction, community detection in functional data networks, and intelligent modeling of metro passenger flows and traffic systems.

Explore Our Research Areas

Detailed Research Research Papers Industry Partnerships

Lab News

Latest announcements and updates from our research lab

Nov 2025

Paper Accepted by IEEE TKDE

Our paper “Adaptive Change Detection in Partially Observable Dynamic Networks” has been accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).

Oct 2025

Paper Accepted by AAAI Workshop

Our paper “Wavelet-based Disentangled Adaptive Normalization for Non-stationary Time Series Forecasting” has been accepted by the AAAI Workshop on AI for Time Series.

Sept 2025

Paper Accepted by AAAI (Main Track)

Our paper “Function-on-Function Bayesian Optimization” has been accepted by the AAAI Conference on Artificial Intelligence (Main Track).

Sept 2025

INFORMS QSR Best Teaching Award

Chen Zhang received the INFORMS Quality, Statistics and Reliability (QSR) Best Teaching Award.

Aug 2025

Paper Accepted by NeurIPS

Our paper “FAME: Adaptive Functional Attention with Expert Routing for Function-on-Function Regression” has been accepted by NeurIPS.

Aug 2025

Dataset Paper Accepted by NeurIPS

Our paper “TraffiDent: A Dataset for Understanding the Interplay Between Traffic Dynamics and Incidents” has been accepted by NeurIPS.

Recent Publications

Highlights from our latest research contributions

Multi-agent causal discovery using large language models
Hao Duong Le, Xin Xia, Zhang Chen
2024 arXiv preprint
Addressing Glaucoma Structure-Function Relationship: A Multi-Task Learning Framework
Xuming An, Jacqueline Chua, Yujin Wang, et al.
2025 IEEE Trans. Medical Imaging
Quickest Causal Change Point Detection by Adaptive Intervention
Haijie Xu, Chen Zhang
2025 arXiv preprint
Low-rank robust subspace tensor clustering for metro passenger flow modeling
Nurretin Dorukhan Sergin, Jiuyun Hu, Ziyue Li, Chen Zhang, et al.
2025 INFORMS Journal on Data Science
AXIS: Explainable Time Series Anomaly Detection with Large Language Models
Tian Lan, Hao Duong Le, Jinbo Li, et al.
2025 arXiv preprint
Bilevel joint optimization for product design changes with resilient supply chain
Yujie Ma, Xin Xia, Yao Pei, Chen Zhang
2025 Int'l Journal of Production Economics
View All Publications (70+)

12

Active Researchers

66

Top-Tier Publications

6

Elite Industry Partners

867

Total Citations

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Our Research

Building the future of superintelligence through cutting-edge AI research and innovation

Core Research Pillars

At the intersection of theoretical innovation and transformative industrial applications

Deep Learning & Neural Architectures

We pioneer advanced deep learning architectures including Graph Neural Networks (GNNs), Transformers, and Recurrent Attention Models for complex data analysis. Our innovations include spatiotemporal graph networks for cellular KPI prediction, multi-task learning frameworks for medical imaging, and deep reinforcement learning for bilevel optimization in product design.

AI-Powered Statistical Learning & Monitoring

Bridging classical statistics with modern AI, we develop intelligent statistical models for real-time monitoring, anomaly detection, and predictive maintenance. Our methods include Bayesian networks for causal inference, Gaussian processes for robust parameter design, and Thompson sampling for partially observable online change detection.

Tensor Learning & High-Dimensional Analytics

We tackle the curse of dimensionality through innovative tensor methods and functional data analysis. Our research includes tensor decomposition for weakly-dependent data on graphs, low-rank robust subspace tensor clustering for metro flow modeling, and latent tensor Gaussian processes for spatial monitoring.

Graph Intelligence & Network Analysis

Advancing graph relational learning and network science through AI. We develop graph regularized tensor latent Dirichlet allocation for individualized passenger travel patterns, functional data edged networks for metro station clustering, and multi-view clustering based on functional data.

Intelligent Decision Systems & Optimization

Creating AI-driven decision frameworks that integrate game theory, optimization, and reinforcement learning. Our research spans deep reinforcement learning for bilevel optimization, data-driven control of complex networked systems, and intelligent decision-making with domain knowledge integration.

Industrial AI & Smart Manufacturing

Transforming industries through practical AI deployments. Our applications span semiconductor manufacturing, aircraft manufacturing, urban transportation, supply chain management, and financial systems. We deploy AI solutions at scale with industry leaders including Huawei, Tencent, Alibaba, Baidu, ByteDance, and Meituan.

Research Impact

Our research has resulted in 70+ publications in premier venues including IEEE Transactions (Medical Imaging, Knowledge and Data Engineering, Automation Science and Engineering, Industrial Informatics), IISE Transactions, Technometrics, Journal of Quality Technology, and top-tier AI conferences including KDD, IJCAI, AAAI, and ECML-PKDD.

We collaborate extensively with industry leaders, deploying AI solutions that impact millions of users daily in transportation, manufacturing, e-commerce, and telecommunications sectors.

Recent Publications

Latest research contributions from our lab

Multi-agent causal discovery using large language models
Hao Duong Le, Xin Xia, Zhang Chen
2024 arXiv preprint
Addressing Glaucoma Structure-Function Relationship: A Multi-Task Learning Framework
Xuming An, Jacqueline Chua, Yujin Wang, et al.
2025 IEEE Trans. Medical Imaging
Quickest Causal Change Point Detection by Adaptive Intervention
Haijie Xu, Chen Zhang
2025 arXiv preprint
Low-rank robust subspace tensor clustering for metro passenger flow modeling
Nurretin Dorukhan Sergin, Jiuyun Hu, Ziyue Li, Chen Zhang, et al.
2025 INFORMS Journal on Data Science
AXIS: Explainable Time Series Anomaly Detection with Large Language Models
Tian Lan, Hao Duong Le, Jinbo Li, et al.
2025 arXiv preprint
Bilevel joint optimization for product design changes with resilient supply chain
Yujie Ma, Xin Xia, Yao Pei, Chen Zhang
2025 Int'l Journal of Production Economics
View All Publications (70+)

Publications

Our research contributions in AI, machine learning, and intelligent systems

Research Publications

Peer-reviewed articles in top-tier journals and conferences

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2025 Publications

Nonlinear Causal Discovery via Dynamic Latent Variables
Xing Yang, Tian Lan, Hao Qiu, Chen Zhang
2025 IEEE Transactions on Automation Science and Engineering
Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy
Tian Lan, Hao Duong Le, Jinbo Li, Wenjun He, Meng Wang, Chenghao Liu, Chen Zhang
2025 arXiv preprint arXiv:2509.21190
SPEVS-CC: Separated parameter estimation with variable selection based on canonical correlation analysis for multivariate functional regression
Xing Yang, Haijie Xu, Yiming Shi, Chen Zhang
2025 Advanced Engineering Informatics
Tensor State Space-based Dynamic Multilayer Network Modeling
Tian Lan, Jie Guo, Chen Zhang
2025 arXiv preprint arXiv:2506.02413
CICADA: Cross-Domain Interpretable Coding for Anomaly Detection and Adaptation in Multivariate Time Series
Tian Lan, Yifei Gao, Yimeng Lu, Chen Zhang
2025 arXiv preprint arXiv:2505.00415
A Deep Reinforcement Learning Method Solving Bilevel Optimization for Product Design Considering Remanufacturing
Yujie Ma, Xin Xia, Jie Guo, Chen Zhang
2025 IEEE Transactions on Engineering Management
Low-rank robust subspace tensor clustering for metro passenger flow modeling
Nurretin Dorukhan Sergin, Jiuyun Hu, Ziyue Li, Chen Zhang, Fugee Tsung, Hao Yan
2025 INFORMS Journal on Data Science
AXIS: Explainable Time Series Anomaly Detection with Large Language Models
Tian Lan, Hao Duong Le, Jinbo Li, Wenjun He, Meng Wang, Chenghao Liu, Chen Zhang
2025 arXiv preprint arXiv:2509.24378
Bilevel joint optimization for product design changes with a resilient supply chain based on deep reinforcement learning
Yujie Ma, Xin Xia, Yao Pei, Chen Zhang
2025 International Journal of Production Economics
Addressing Glaucoma Structure-Function Relationship: A Multi-Task Learning Framework with Multi-Modal and Unpaired Data
Xuming An, Jacqueline Chua, Yujin Wang, Ruben Hemelings, Rahat Husain, Rachel Chong, Tina Wong, Tin Aung, Damon Wong, Chen Zhang, Leopold Schmetterer
2025 IEEE Transactions on Medical Imaging
Quickest Causal Change Point Detection by Adaptive Intervention
Haijie Xu, Chen Zhang
2025 arXiv preprint arXiv:2506.07760

2024 Publications

Multi-agent causal discovery using large language models
Hao Duong Le, Xin Xia, Zhang Chen
2024 arXiv preprint arXiv:2407.15073
Coupled Epidemic-Information Propagation With Stranding Mechanism on Multiplex Metapopulation Networks
Xuming An, Chen Zhang, Lin Hou, Kaibo Wang
2024 IEEE Transactions on Computational Social Systems
XTraffic: A Dataset Where Traffic Meets Incidents with Explainability and More
Xiaochuan Gou, Ziyue Li, Tian Lan, Junpeng Lin, Zhishuai Li, Bingyu Zhao, Chen Zhang, Di Wang, Xiangliang Zhang
2024 arXiv preprint arXiv:2407.11477
MultiFun-DAG: Multivariate Functional Directed Acyclic Graph
Tian Lan, Ziyue Li, Junpeng Lin, Zhishuai Li, Lei Bai, Man Li, Fugee Tsung, Rui Zhao, Chen Zhang
2024 arXiv preprint arXiv:2404.13836
Thompson Sampling-Based Partially Observable Online Change Detection for Exponential Families
Jie Guo, Hao Yan, Chen Zhang
2024 INFORMS Journal on Data Science
Multi-Scenario Cellular KPI Prediction Based on Spatiotemporal Graph Neural Network
Junpeng Lin, Tian Lan, Bo Zhang, Ke Lin, Dandan Miao, Huiru He, Jiantao Ye, Chen Zhang, Yan-Fu Li
2024 IEEE Transactions on Automation Science and Engineering
Online directed-structural change-point detection: A segment-wise time-varying dynamic Bayesian network approach
Xing Yang, Chen Zhang
2024 IISE Transactions
Stream of variation modeling and monitoring for heterogeneous profiles in multi-stage manufacturing processes
Peiyao Liu, Yujie Ma, Chen Zhang
2024 IISE Transactions
A comprehensive survey of recent research on profile data analysis
Peiyao Liu, Haijie Xu, Chen Zhang
2024 Conference Proceedings
Reverse logistics platform decisions integrating crowdsourced contracting: A three-level interactive optimization approach for product design considering remanufacturing
Yujie Ma, Chen Zhang, Gang Du
2024 Computers & Industrial Engineering
Partially-Observable Sequential Change-Point Detection for Autocorrelated Data via Upper Confidence Region
Haijie Xu, Xiaochen Xian, Chen Zhang, Kaibo Liu
2024 arXiv preprint arXiv:2404.00220
Federated Multi-task Bayesian Network Learning in the Presence of Overlapping and Distinct Variables
Xing Yang, Ben Niu, Tian Lan, Chen Zhang
2024 IISE Transactions
MT-RAM: Multi Task-Recurrent Attention Model for partially observable image anomaly classification and localization
Jie Guo, Congyu Han, Yujie Ma, Chen Zhang
2024 IISE Transactions
Heterogeneous Multivariate Functional Time Series Modeling: A State Space Approach
Peiyao Liu, Junpeng Lin, Chen Zhang
2024 IEEE Transactions on Knowledge and Data Engineering
Advanced Data Analytical Techniques for Profile Monitoring
Peiyao Liu, Chen Zhang
2024 Conference Proceedings
Fine‐Grained Passenger Load Prediction inside Metro Network via Smart Card Data
Xiancai Tian, Chen Zhang, Baihua Zheng
2024 International Journal of Intelligent Systems
MPOFI: Multichannel Partially Observed Functional Modeling for Defect Classification with Imbalanced Dataset via Deep Metric Learning
Yukun Xie, Juan Du, Chen Zhang
2024 arXiv e-prints
Functional-Edged Network Modeling
Haijie Xu, Chen Zhang
2024 arXiv preprint arXiv:2404.00218

2023 Publications

Dynamic causal graph convolutional network for traffic prediction
Junpeng Lin, Ziyue Li, Zhishuai Li, Lei Bai, Rui Zhao, Chen Zhang
2023 Conference Proceedings
A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling
Jie Guo, Hao Yan, Chen Zhang
2023 Technometrics
MM-DAG: Multi-task DAG Learning for Multi-modal Data--with Application for Traffic Congestion Analysis
Tian Lan, Ziyue Li, Zhishuai Li, Lei Bai, Man Li, Fugee Tsung, Wolfgang Ketter, Rui Zhao, Chen Zhang
2023 Conference Proceedings
Multi-view metro station clustering based on passenger flows: a functional data-edged network community detection approach
Chen Zhang, Baihua Zheng, Fugee Tsung
2023 Data Mining and Knowledge Discovery
In-profile monitoring for cluster-correlated data in advanced manufacturing system
Peiyao Liu, Juan Du, Yangyang Zang, Chen Zhang, Kaibo Wang
2023 Journal of Quality Technology
A hidden markov model for condition monitoring of time series data in complex network systems
Wanshan Li, Chen Zhang
2023 IEEE Transactions on Reliability
A Markov-switching hidden heterogeneous network autoregressive model for multivariate time series data with multimodality
Wanshan Li, Chen Zhang
2023 IISE Transactions
Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering
Ziyue Li, Hao Yan, Chen Zhang, Wolfgang Ketter, Fugee Tsung
2023 Conference Proceedings
Choose A Table: Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering
Ziyue Li, Hao Yan, Chen Zhang, Lijun Sun, Wolfgang Ketter, Fugee Tsung
2023 arXiv preprint arXiv:2310.20224
A Cluster-Oriented Bayesian Network Approach for Mixed-Type Event Prediction With Application in Order Logistics
Xing Yang, Hui Cao, Chen Zhang
2023 IEEE Transactions on Industrial Informatics
Deep Cascade-Learning Model via Recurrent Attention for Immunofixation Electrophoresis Image Analysis
Xuming An, Pengchang Li, Chen Zhang
2023 IEEE Transactions on Medical Imaging

2022 Publications

GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning.
Weiqi Zhang, Chen Zhang, Fugee Tsung
2022 Conference Proceedings
Individualized passenger travel pattern multi-clustering based on graph regularized tensor latent dirichlet allocation
Ziyue Li, Hao Yan, Chen Zhang, Fugee Tsung
2022 Data Mining and Knowledge Discovery
Modeling of discharge voltage for lithium-ion batteries through orthogonal experiments at subzero environment
Huixing Meng, Yan-Fu Li, Chen Zhang
2022 Journal of Energy Storage
Segment-wise time-varying dynamic Bayesian network with graph regularization
Xing Yang, Chen Zhang, Baihua Zheng
2022 ACM Transactions on Knowledge Discovery from Data (TKDD)
Monitoring Heterogeneous Multivariate Profiles Based on Heterogeneous Graphical Model
Hui Wu, Chen Zhang, Yan-Fu Li
2022 Technometrics
Functional state-space model for multi-channel autoregressive profiles with application in advanced manufacturing
Peng Zhou, Peiyao Liu, Shilong Wang, Chen Zhang, Junxing Zhang, Shaobo Li
2022 Journal of Manufacturing Systems

2021 Publications

Dynamic multivariate functional data modeling via sparse subspace learning
Chen Zhang, Hao Yan, Seungho Lee, Jianjun Shi
2021 Technometrics
Online monitoring of big data streams: A rank-based sampling algorithm by data augmentation
Xiaochen Xian, Chen Zhang, Scott Bonk, Kaibo Liu
2021 Journal of Quality Technology
Transformer Based Spatial-Temporal Fusion Network for Metro Passenger Flow Forecasting
Weiqi Zhang, Chen Zhang, Fugee Tsung
2021 Conference Proceedings
A data-driven method for online monitoring tube wall thinning process in dynamic noisy environment
Chen Zhang, Jun Long Lim, Ouyang Liu, Aayush Madan, Yongwei Zhu, Shili Xiang, Kai Wu, Rebecca Yen-Ni Wong, Jiliang Eugene Phua, Karan M Sabnani, Keng Boon Siah, Wenyu Jiang, Yixin Wang, Emily Jianzhong Hao, Steven CH Hoi
2021 IEEE Transactions on Automation Science and Engineering
Holistic Prediction for Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach
Bingjie He, Shukai Li, Chen Zhang, Baihua Zheng, Fugee Tsung
2021 Conference Proceedings

2020 Publications

Tensor completion for weakly-dependent data on graph for metro passenger flow prediction
Ziyue Li, Nurettin Dorukhan Sergin, Hao Yan, Chen Zhang, Fugee Tsung
2020 Proceedings of the AAAI Conference on Artificial Intelligence
Long-short term spatiotemporal tensor prediction for passenger flow profile
Ziyue Li, Hao Yan, Chen Zhang, Fugee Tsung
2020 IEEE Robotics and Automation Letters
Spatial rank-based high-dimensional monitoring through random projection
Chen Zhang, Nan Chen, Jianguo Wu
2020 Journal of Quality Technology
Crowding Prediction of In-Situ Metro Passengers Using Smart Card Data
Xiancai Tian, Chen Zhang, Baihua Zheng
2020 arXiv preprint arXiv:2009.02880
Time-Warped Sparse Non-negative Factorization for Functional Data Analysis
Chen Zhang, Steven CH Hoi, Fugee Tsung
2020 ACM Transactions on Knowledge Discovery from Data (TKDD)

2019 Publications

Partially observable multi-sensor sequential change detection: A combinatorial multi-armed bandit approach
Chen Zhang, Steven CH Hoi
2019 Proceedings of the AAAI Conference on Artificial Intelligence
A sequential bayesian partitioning approach for online steady-state detection of multivariate systems
Jianguo Wu, Honglun Xu, Chen Zhang, Yuan Yuan
2019 IEEE Transactions on Automation Science and Engineering

2018 Publications

Weakly correlated profile monitoring based on sparse multi-channel functional principal component analysis
Chen Zhang, Hao Yan, Seungho Lee, Jianjun Shi
2018 IISE Transactions
Multiple profiles sensor-based monitoring and anomaly detection
Chen Zhang, Hao Yan, Seungho Lee, Jianjun Shi
2018 Journal of Quality Technology
Clustering Subway Station Arrival Patterns Using Weighted Dynamic Time Warping
Rui Wang, Nan Chen, Chen Zhang
2018 Conference Proceedings
Statistical analysis of simulation output from parallel computing
Chen Zhang, Nan Chen
2018 ACM Transactions on Modeling and Computer Simulation (TOMACS)

2017 Publications

State space modeling of autocorrelated multivariate Poisson counts
Chen Zhang, Nan Chen, Zhiguo Li
2017 IISE Transactions
Modeling tunnel profile in the presence of coordinate errors: A Gaussian process-based approach
Chen Zhang, Yong Lei, Linmiao Zhang, Nan Chen
2017 IISE Transactions
Spectral network approach for multi-channel profile data analysis with applications in advanced manufacturing
Chen Zhang, Linmiao Zhang, Nan Chen
2017 Conference Proceedings

2016 Publications

Robust multivariate control chart based on goodness-of-fit test
Chen Zhang, Nan Chen, Changliang Zou
2016 Journal of Quality Technology

Publication Impact

Research metrics and achievements

66

Total Publications

11

IEEE Transactions

17

H-Index

867

Total Citations

Key Publication Venues

IEEE Transactions

  • Automation Science and Engineering
  • Computational Social Systems
  • Engineering Management
  • IEEE Robotics and Automation Letters

Top Journals

  • INFORMS Journal on Data Science
  • International Journal of Intelligent Systems
  • International Journal of Production Economics
  • Journal of Energy Storage

Top Conferences

  • AAAI Conference on Artificial Intelligence

Awards

Recognizing excellence in research, teaching, and scholarly publications

Selected Honors & Awards

Society, national, international, teaching, and publication-related recognitions

Society, National and International Awards

  • Elsevier Highly Cited Chinese Researchers, 2023.
  • 8th China Association for Science and Technology Young Talent Support Program, 2022–2024.
  • Ministry of Education Outstanding Scientific Research Achievement Award (Science and Technology) – Second Prize, 2023.
  • Brumbaugh Award, American Society for Quality (ASQ), 2019.

Awards Related to Teaching

  • Tsinghua University Young Faculty Teaching Competition, Second Prize, 2024.

Awards Related to Publications

  • Winner of Best Paper Competition in 2025 INFORMS Conference on Quality, Statistics and Reliability, for the paper “Spatial In-Profile Monitoring via Latent Tensor Gaussian Process with Mixed Effects”.
  • Best Application Paper Award in IISE Transactions for the paper “A Markov-Switching Hidden Heterogeneous Network Autoregressive Model for Multivariate Time Series Data with Multimodality”, 2025.
  • Best Paper Finalist Award in the QCRE Section of Industrial and Systems Engineering Research Conference (ISERC), for the paper “Interactive Resource Planning and Change Detection via Multi-agent Reinforcement Learning”, 2025.
  • Feature Article “Federated multi-task Bayesian network learning in the presence of overlapping and distinct variables”, in ISE Magazine, 2025.
  • Runner-up of INFORMS 2024 Data Mining and Decision Analytics Workshop Best Paper Competition, for the paper “Heterogeneous Multivariate Functional Time Series Modeling: A State Space Approach”, 2024.
  • Best Paper Finalist Award of the INFORMS 2024 Quality, Statistics and Reliability Section, for the paper “Spatial In-Profile Monitoring via Latent Tensor Gaussian Process with Mixed Effects”, 2024.
  • Feature Article “Online Directed-structural Change-point Detection: A Segment-wise Time-varying Dynamic Bayesian Network Approach”, in ISE Magazine, 2024.
  • Runner-up of INFORMS 2023 Data Mining and Decision Analytics Workshop Best Paper Competition, for the paper “Thompson Sampling based Partially Observable Online Monitoring Approach for Large Dynamic Networks”, 2023.
  • Best Paper Finalist Award of 2023 QCRE Best Track Paper Competition, for the paper “Graph-aware Tensor Topic Models for Individualized Passenger Travel Pattern Clustering”, 2023.
  • Second Place of 16th INFORMS Data Mining and Decision Analytics Workshop Poster Competition, for the paper “Holistic Prediction for Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach”, 2021.
  • Runner-up of 16th INFORMS Data Mining and Decision Analytics Workshop Theoretical Best Paper Competition, for the paper “Low-rank Sparse Tensor Decomposition with Ridge Regularized Subspace Clustering for Metro Passenger Flow Modeling”, 2021.
  • Best Paper Award of 2020 IEEE Conference on Automation Science and Engineering for the paper “Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile”.
  • Best Paper Award in IISE Transactions for the paper “Multichannel Profile Monitoring based on Sparse Multichannel Functional Principal Component Analysis”, 2019.
  • Best Paper Award in IISE Transactions for the paper “State space modeling of autocorrelated multivariate Poisson counts”, 2018.
  • Winner of 2017 INFORMS Data Mining Best Paper Competition, for the paper “Dynamic Multivariate Functional Data Modeling via Sparse Subspace Learning”.
  • Winner of 2017 INFORMS QSR Best Student Poster Competition, for the paper “Multichannel Profile Monitoring based on Sparse Multichannel Functional Principal Component Analysis”.

Our Team

Meet the researchers advancing AI and data analytics

Dr. Chen Zhang
CZ

Dr. Chen Zhang

Associate Professor & Principal Investigator

Department of Industrial Engineering, Tsinghua University

Research Interests
  • Statistical modeling and monitoring for complex systems
  • Machine learning and data mining for large-scale systems
  • Online learning and real-time monitoring for streaming data
Education
  • Ph.D. in Industrial Systems Engineering, National University of Singapore (2017)
  • Visiting Student, Georgia Institute of Technology (2016)
  • B.E. in Electronic Science and Technology, Tianjin University (2012)
Contact
  • Email: zhangchen01@tsinghua.edu.cn
  • Office: Room 602, Shunde Building, Tsinghua University
  • Tel: +86-10-62796135

Research Fellows

Yujie Ma
YM
Yujie Ma
Postdoctoral Fellow

Yujie Ma is a Postdoctoral Fellow in the Department of Industrial Engineering at Tsinghua University, China. She received her Ph.D. in Management Science and Engineering from Tianjin University in January 2022. Her research interests include supply chain resilience, bi-level programming, and deep reinforcement learning.

Research Gragh
Bo Zhang
BZ
Bo Zhang
Postdoctoral Fellow

Postdoctoral research in advanced machine learning methodologies and their applications to complex systems.

Yifei Gao
YG
Yifei Gao
Postdoctoral Fellow

Yifei Gao is a Postdoctoral Fellow in the Department of Industrial Engineering, Tsinghua University, China. He received the Doctor of Engineering degree in Management Science and Engineering at Beijing University of Posts and Telecommunications in June 2024. His research focuses on deep learning-based time series and functional data analysis.

Research Gragh
Manrui Jiang
MJ
Manrui Jiang
Postdoctoral Fellow

Manrui Jiang is a Postdoctoral Fellow in the Department of Industrial Engineering, Tsinghua University, China. She received the doctor degree in School of Management and Engineerin at Capital University of Economics and Business in June 2024. Her research focuses on deep learning, complex networks, and financial risk management.

Research Gragh

PhD Students

Haijie Xu
HX
Haijie Xu
PhD Student

Haijie Xu is currently a PhD student in the Department of Industrial Engineering of Tsinghua University. His research focuses on change point detection, functionl data analysis, tensor data analysis and causal inference.

Research Gragh
Tian Lan
TL
Tian Lan
PhD Student

Tian Lan is a PhD student in the department of Industrial Engineering. His research focuses on multimodal LLM and time-series anomaly detection.

Xuming An
XA
Xuming An
PhD Student

Xuming An is currently a Ph.D Student in the Department of Industrial Engineering, Tsinghua University. He received the Master degree in Control Science and Engineering from Wuhan University in 2020. His current research interests include optimization algorithms, game theory and data-driven control of complex networked systems.

Research Gragh
Yimeng Lu
YL
Yimeng Lu
PhD Student

Research in advanced machine learning and statistical methodologies.

Hao Duong Le
HL
Hao Duong Le
PhD Student

Hao Duong Le is a PhD candidate in the Industrial Engineering Department at Tsinghua University, focusing his research on deep learning foundation models, large language models (LLMs), and time series foundational models. He holds a Bachelor of Arts in Applied Foreign Languages from the Taiwan University of Science and Technology and a Master of Science in Engineering from Tsinghua University.

Research Assistants

JH
Jingru Huang
Research Assistant

Supporting research in data analytics and machine learning applications.

Jia Cao
JC
Jia Cao
Research Assistant

Jia Cao received her Master’s degree from the Department of Computer Science, Faculty of Engineering, The University of Hong Kong, and her Bachelor’s degree from the School of Software, Dalian University of Technology. She is currently a research assistant at the Department of Industrial Engineering, Tsinghua University. Her research interests include video anomaly detection, medical image analysis, and medical large language models.

Yingyuan Yang
JC
Yingyuan Yang
Research Assistant

Yingyuan Yang is currently a Research Assistant in the Department of Industrial Engineering, Tsinghua University. He received a Master's degree in Signal and Information Processing from the Shenzhen Institutes of Advanced Technology, University of Chinese Academy of Sciences in 2025. His current research interests include time-series anomaly detection based on multimodal large language models (MLLMs) and interpretable analysis of time-series MLLMs.

Notable Alumni

Peiyao Liu
PL
Peiyao Liu
Research Fellow, National University of Singapore

Peiyao Liu received her Ph.D. in Industrial Engineering in 2025 (advised by Dr. Chen Zhang) and her B.Eng. in Precision Instrument in 2020, both from Tsinghua University. Her research focuses on functional data analysis, tensor decomposition, Gaussian processes, state space models, and Bayesian networks, with applications in advanced manufacturing and medical testing. Dr. Liu has published in leading international journals in Quality, Statistics, and Reliability, including IISE Transactions, Journal of Quality Technology, and IEEE Transactions on Knowledge and Data Engineering. Her work has been recognized with multiple prestigious awards, including the ICQSR, INFORMS-DMDA, INFORMS-QSR, IISE-QCRE, and QRSE. Currently, she is a Research Fellow in the Department of Industrial Systems Engineering and Management at the National University of Singapore, working under the guidance of Dr. Nan Chen.

Research Gragh
Junpeng Lin
JL
Junpeng Lin
Algorithm Engineer, Huawei Technologies

Junpeng Lin is currently an Algorithm Engineer at Huawei Technologies Co., Ltd., focusing on communication network operations and maintenance. He received his Master of Engineering degree in Management Science and Engineering from Tsinghua University in 2025. Prior to that, he obtained his Bachelor of Engineering degree in Industrial Engineering from Tsinghua University in 2022. During his graduate studies, his research interests included spatiotemporal data modeling and deep learning.

Research Gragh
Bingjie He
BH
Bingjie He
PhD Student, UC Berkeley

Bingjie He was a graduate student in Industrial Engineering, Tsinghua University. She received her Bachelor’s degree in Tsinghua University in 2020. Her research interest was transportation application, including urban flow prediction and anomaly detection. She is now pursuing her PhD degree in UC Berkeley, the US.

Congyu Han
CH
Congyu Han
PhD Student, National University of Singapore

Congyu Han was a Research Assistant in the Department of Industrial Engineering, Tsinghua University, China. She has graduated from the Master of Information Systems Management program (Business Intelligence & Data Analytics pathway) at Carnegie Mellon University in December 2020. Her research focuses on adaptive sampling in the context of deep learning framwork. She is now pursuing her PhD degree in National University of Singapore.

Xin Xia
XX
Xin Xia
PhD Student, University of Wisconsin–Madison

Xin Xia has graduated from the M.S. program of Electrical and Computer Engineering in Georgia Institute of Technology, the US, in 2022 and received his bachelor degree of Electrical Engineering and Automation from Tianjin University, China, in 2020. He was a Research Assistant in the Department of Industrial Engineering, Tsinghua University. His research interest focuses on deep reinforcement learning and multi-modal data fusion and feature extraction based on pretrained language model. He is now pursuing his PhD degree in University of Wisconsin–Madison.

Research Gragh
Xing Yang
XY
Xing Yang
Associate Researcher, Shenzhen University

Xing Yang is currently an associate researcher in Shenzhen University. She received her Ph.D. degree in the Department of Industrial Engineering, Tsinghua University, and her B.S. degree in industrial engineering from Huazhong University of Science and Technology, Wuhan, Hubei Province, China, in 2016. Her research interests include Bayesian network, discrete event prediction, ontology modeling.

Research Gragh
Hao Qiu
HQ
Hao Qiu
Former Research Assistant

Hao Qiu was once a Research Assistant in the Department of Industrial Engineering at Tsinghua University. He holds a Master of Statistics from Rice University and a B.S. in Actuarial Science and B.S. in Economics from University of Delaware. His research focuses on Time Series/ Spatial-Temporal data, Statistical Learning, and Stochastic Process Modeling and Estimation.

Jie Guo
JG
Jie Guo
Associate Professor, Nanjing University of Aeronautics and Astronautics

Jie Guo received her Ph.D. degree and bachelor degree in Industrial Engineering from Tsinghua University. And she is now an associate professor in Nanjing University of Aeronautics and Astronautics. Her interest research area is adaptive sampling, high dimensional data monitoring and reinforcement learning.

Research Gragh
Wanshan Li
WL
Wanshan Li
Lecturer, Jinan University

Wanshan Li is currently a lecturer in Jinan University. She received her Ph.D. degree in the Department of Industrial Engineering, Tsinghua University, China, and her BSc in Control Science and Engineering from Shandong University, China. Her research focuses on maintenance strategies optimization of multiple‐component systems with complex networked structure.

Research Gragh
Peng Zhou
PZ
Peng Zhou
Associate Professor, Guizhou University

Peng Zhou is currently a associate professor at the School of Mechanical Engineering, Guizhou University, Guiyang, China. His current research interests include in Statistical modeling and monitoring for complex systems, Intelligent maintenance and health management.

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PhD Students

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