• 2013.07—2017.09: Ph.D., Industrial Systems Engineering & Management, National University of Singapore (advisor: Prof. Nan Chen)

• 2016.01—2016.12: Visiting student, Industrial Systems Engineering, Georgia Institute of Technology (advisor: Prof. Jianjun Shi)

• 2008.09—2012.06: B.E. in Electronic Science and Technology, Tianjin University

• 2020.06—Present: Associate Professor (without tenure), Department of Industrial Engineering, Tsinghua University

• 2018.05—2020.06: Assistant Professor, Department of Industrial Engineering, Tsinghua University

• 2017.09—2018.05: Postdoctoral Fellow, School of Information Systems, Singapore Management University

A. Society, National and International Awards

·Elsevier Highly Cited Chinese Researchers, 2024. (Selected as one of the top-cited scholars in China by Elsevier based on Scopus citation data, recognizing influential contributions, sustained academic impact and national leadership in the related field)

·8th China Association for Science and Technology Young Talent Support Program, 2022-2024. (Selected as one of 100 outstanding young scientists in China across science and engineering disciplines. This prestigious three-year program supports innovative, high-potential researchers under the age of 35 who are driving frontier research directions of national significance.)

·Ministry of Education Outstanding Scientific Research Achievement Award (Science and Technology) – Second Prize, 2023. (Awarded by the Ministry of Education of China for breakthroughs in science and technology, with Second Prize awarded to 20–30 project teams nationwide annually.)

·Brumbaugh Award, American Society for Quality (ASQ), 2019. (Awarded to the author(s) of the paper making the largest single contribution to industrial quality control among all articles published across ASQ journals. This award is highly prestigious and selected annually from over 200 published papers across ASQ’s seven journals.)

·Singapore Semiconductor Gold Medal, 2018. (Presented by the Singapore Semiconductor Industry and be awarded to the higher degree graduate in the Department of Industrial Systems Engineering and Management of NUS who has published the best research paper that has been accepted/published by an international journal.)

B. Awards Related to Teaching

·Tsinghua University Young Faculty Teaching Competition, Second Prize, 2024. (Awarded to top-performing 20 young instructors across Tsinghua University based on teaching design, and classroom performance)

C. 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”. (The best paper selected among 40+ submissions)

·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. (One of the four best papers selected among ~50+ papers from the quality and reliability focused issue of IISE Transactions)

·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. (One of the top four papers selected among 30+ submissions)

·Feature Article “Federated multi-task Bayesian network learning in the presence of overlapping and distinct variables”, in ISE Magazine, 2025. (a spotlighted article selected by the editorial board of ISE Magazine, the flagship publication of the Institute of Industrial and Systems Engineers (IISE))

·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. (The second best paper selected among 20+ submissions)

·Feature Article “Online Directed-structural Change-point Detection: A Segment-wise Time-varying Dynamic Bayesian Network Approach”, in ISE Magazine, 2024. (A spotlighted article selected by the editorial board of ISE Magazine)

·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. (The second best paper selected among 20+ submissions)

·Best Paper Finalist of 2023 QCRE Best Track Paper Competition, for the paper “Graph-aware Tensor Topic Models for Individualized Passenger Travel Pattern Clustering”, 2023. (One of the top four papers selected among 30+ submissions)

·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. (The second best poster selected among 30+ submissions)

·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. (The second best paper selected among 20+ submissions)

·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”. (The best paper selected among 200+ submissions)

·Best Paper Award in IISE Transactions for the paper “Multichannel Profile Monitoring based on Sparse Multichannel Functional Principal Component Analysis” 2019. (One best paper selected among ~50+ papers from the quality and reliability focused issue of IISE Transactions)

·Best Paper Award in IISE Transactions for the paper “State space modeling of autocorrelated multivariate Poisson counts. IISE Transactions,” 2018. (One of the four best papers selected among ~50+ papers from the quality and reliability focused issue of IISE Transactions)

·Winner of 2017 INFORMS Data Mining Best Paper Competition, for the paper “Dynamic Multivariate Functional data Modeling via Sparse Subspace Learning”. (The best paper selected among 30+ submissions)

·Winner of 2017 INFORMS QSR Best Student Poster Competition, for the paper “Multichannel Profile Monitoring based on Sparse Multichannel Functional Principal Component Analysis”. (The best poster selected among 30+ submissions)

Dr. Zhang has published a total of 40 journal papers (including 37 papers published after joining Tsinghua University), as well as 6 peer-reviewed conference papers. In the publication list, student/research assistant/posdoc advisees are underlined, “^#” denotes junior collaborator (pre-tenure at the time of submission) , “^&” denotes senior collaborator (tenured at the time of submission), “^$” denotes industry collaborator, and “*” denotes corresponding authorship. Among the 46 published papers, Dr. Zhang is the first author on 12 and the corresponding author on 25—all of which have advisees as first authors. In addition, 10 journal papers are currently submitted, under review, or in revision.

Refereed Journals

1. An, X., Chua, J.^$, Wang, Y., Hemelings, R.^$, Husain R.^$, Chong R.^$, Wong T.^$, Aung T.^$, Wong D.^$*, Zhang, C.*, Schmetterer L.^$*, Addressing Glaucoma Structure-Function Relationship: A Multi-Task Learning Framework with Multi-Modal and Unpaired Data, IEEE Transactions on Medical Imaging, conditionally accepted.

2. Liu, P., Zhang, C.* (2025), Stream of Variation Modeling and Monitoring for Heterogeneous Profiles in Multi-Stage Manufacturing Processes, IISE Transactions, 1-14, https://doi.org/10.1080/24725854.2024.2413122.

3. Guo, J., Han, C., and Zhang, C.* (2025), MT-RAM: MultiTask-Recurrent Attention Model for Partially Observable Image Anomaly Classification and Localization, IISE Transactions, 1-16, https://doi.org/10.1080/24725854.2024.2425292.

4. Ma, Y., Xia, X., Guo, J., and Zhang, C.* (2025), A Deep Reinforcement Learning Method Solving Bilevel Optimization for Product Design Considering Remanufacturing, IEEE Transaction on Engineering Management, 72, 573-590.

5. Yang, X, Lan, T., Qiu, H., Zhang, C.* (2025), Nonlinear Causal Discovery via Dynamic Latent Variables, IEEE Transactions on Automation Science and Engineering, 22, 10381-10391.

6. Yang, X., Niu, B.^&, Lan, T., Zhang, C.* (2025), Federated Multi-task Bayesian Network Learning in the Presence of Overlapping and Distinct Variables, IISE Transactions, 57(7), 773–787.

7. Tian, X., Zhang, C.*, Zheng, B.^& (2024), Fine-Grained Passenger Load Prediction inside Metro Network via Smart Card Data, International Journal of Intelligent Systems, 2024(1), 6643018.

8. Ma, Y., Zhang, C.*, Du, G. ^& (2024), Reverse logistics platform decisions integrating crowdsourced contracting: A three-level interactive optimization approach for product design considering remanufacturing, Computers & Industrial Engineering, 193, 110305.

9. Liu, P., Lin, J., Zhang, C.* (2024), Heterogeneous Multivariate Functional Time Series Modeling: A State Space Approach, IEEE Transactions on Knowledge and Data Engineering, 36(12), 8421-8433.

10. Lin, J., Lan, T., Zhang, B., Deng, K.^$, Miao, D.^$, Ye., J.^$, Li, Y.^&, and Zhang, C.* (2024), Multi-Scenario Cellular KPI Prediction Based on Spatiotemporal Graph Neural Network, IEEE Transactions on Automation Science and Engineering, 22, 5131-5142.

11. Liu, P., Xu, H., and Zhang, C.* (2024), A Comprehensive Survey of Recent Research on Profile Data Analysis, Journal of Quality Technology, 56(5), 428–454.

12. An, X., Zhang, C.*, Hou, L.^&, and Wang, K.^& (2024), Coupled Epidemic-Information Propagation with Stranding Mechanism on Multiplex Metapopulation Networks, IEEE Transactions on Computational Social Systems, 11(5), 6727-6744.

13. Sergin, N., Hu, J., Li, Z., Zhang, C., and Yan, H.^#* (2024), Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling, INFORMS Journal on Data Science, 4(1), 33-50.

14. Li, W., and Zhang, C.* (2023), A Markov-Switching Hidden Heterogeneous Network Autoregressive Model for Multivariate Time Series Data with Multimodality, IISE Transactions, 55(11), 1118–1132.

15. Yang, X., Zhang, C.*, and Cao, H.^# (2023), A Cluster-oriented Bayesian Network Approach for Mixed-type Event Prediction with Application in Order Logistics, IEEE Transactions on Industrial Informatics, 19(10), 10069 - 10078.

16. Yang, X., and Zhang, C.* (2023), Online Directed Structural Change-point Detection: A Segment-wise Time-varying Dynamic Bayesian Network Approach, IISE Transactions, 56(5), 527–540.

17. Guo, J., Yan, H.^#, and Zhang, C.* (2023), Thompson Sampling based Partially Observable Online Change Detection for Exponential Families, INFORMS Journal on Data Science, 3(2), 145-161.

18. An, X., Li, P.^$, and Zhang, C.* (2023), Deep Cascade-Learning Model via Recurrent Attention for Immunofixation Electrophoresis Image Analysis, IEEE Transactions on Medical Imaging, 42(12), 3847-3859.

19. Meng, H., Li, Y. F.^&*, and Zhang, C. (2022), Estimation of discharge voltage for lithium- ion batteries through orthogonal experiments at subzero environment, Journal of Energy Storage, 52(C), 10508.

20. Guo, J., Yan, H.^#, and Zhang, C.* (2022), A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling, Technometrics, 65(2), 179-191.

21. Li, Z., Yan, H.^#, Zhang, C., and Tsung, F.^&* (2022), Individualized Passenger Travel Pattern Multi-Clustering based on Graph Regularized Tensor Latent Dirichlet Allocation, Data Mining and Knowledge Discovery, 36(4), 1247-1278.

22. Yang, X., Zhang, C.*, and Zheng, B. H.^& (2022), Segment-Wise Time-Varying Dynamic Bayesian Network with Graph Regularization, ACM Transactions on Knowledge Discovery from Data, 16(6), 1-23.

23. Zhou, P., Liu, P., Wang, S.^#, Zhang, C.*, Zhang, J.^#, and Li, S.^& (2022), Functional state-space model for multi-channel autoregressive profiles with application in advanced manufacturing, Journal of Manufacturing Systems, 64, 356-371.

24. Li, W., and Zhang, C.* (2022), A Hidden Markov Model for Condition Monitoring of Time Series Data in Complex Network Systems, IEEE Transactions on Reliability, 72(4), 1478-1492.

25. Zhang, C.*, Zheng, B.^& and Tsung, F.^& (2022), Multi-view Metro Station Clustering based on Passenger Flows: A Functional Data Edged Network Community Detection Approach, Data Mining and Knowledge Discovery, 37(3), 1154-1208.

26. Liu, P., Du, J.^#, Zang, Y.^#, Zhang, C.*, and Wang, K.^& (2022), In-profile Monitoring for Cluster-Correlated Data in Advanced Manufacturing System, Journal of Quality Technology, 55(2), 195–219.

27. Wu, H., Zhang, C., and Li, Y F.^& (2021), Monitoring Heterogeneous Multivariate Profiles Based on Heterogeneous Graphical Model, Technometrics, 64(2), 210-223.

28. Zhang, C., Yan, H.^#*, Lee, S.^$, and Shi, J.^& (2021), Dynamic Multivariate Functional data Modeling via Sparse Subspace Learning, Technometrics , 63(3), 370-383.

29. Zhang, C.*, Hoi, C.H.^& and Tsung, F.^& (2020), Multivariate Functional Data Modeling via Nonnegative Functional Factorization with Time Warping, ACM Transactions on Knowledge Discovery from Data, 14(6), 1-23.

30. Zhang, C.* and Hoi, C.H.^& (2020), A Data-Driven Method for Online Monitoring Tube Wall Thinning Process in Dynamic Noisy Environment, IEEE Transactions on Automation Science and Engineering, 19(1), 441-456.

31. Li, Z., Yan, H.^#, Zhang, C., and Tsung, F.^&* (2020), Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile, IEEE Robotics and Automation Letters, 5(4), 5010-5017.

32. Zhang, C., Chen, N.^& and Wu, J. ^&* (2019), Spatial Rank based High-dimensional Monitoring Through Random Projection, Journal of Quality Technology, 52 (2), 111-127.

33. Wu, J.^&, Xu, H.^#, Zhang, C., and Yuan, Y.^& (2019), A Sequential Bayesian Partitioning Approach for Online Steady-State Detection of Multivariate Systems, IEEE Transactions on Automation Science and Engineering, 16(4), 1882-1895.

34. Xian, X.^#, Zhang, C., Bonk, S.^#, and Liu, K.^& (2019), Online Monitoring of Big Data Streams: A Rank-based Sampling Algorithm by Data Augmentation, Journal of Quality Technology, 53 (2), 135-153.

35. Zhang, C., Yan, H.^#, Lee, S.^$, and Shi, J.^&* (2018), Multiple Profiles Sensor-Based Monitoring and Anomaly Detection, Journal of Quality Technology, 50(4), 344-362.

36. Zhang, C., Yan, H.^#*, Lee, S.^$, and Shi, J.^& (2018), Multichannel Profile Monitoring based on Sparse Multichannel Functional Principal Component Analysis, IISE Transactions, 50(10), 878-891.

37. Zhang, C., and Chen, N.^&* (2018), Statistical Analysis of Simulation Outputs from Parallel Computing, ACM Transactions on Modeling and Computer Simulation (TOMACS), 28(3), 21-35.

38. Zhang, C., Lei, Y., Zhang, L., and Chen, N.^&* (2017), Modelling Tunnel Profile in the Presence of Coordinate Errors: A Gaussian Process-Based Approach, IISE Transactions, 49(11), pp.1065-1077.

39. Zhang, C., Chen, N.^&*, and Li, Z.^& (2017), State space modeling of autocorrelated multivariate Poisson counts, IISE Transactions, 49(5), 518-531.

40. Zhang, C., Chen, N.^&*, and Zou, C.^& (2016), Robust multivariate control chart based on goodness-of-fit test, Journal of Quality Technology, 48(2), 139-161.

Peer-reviewed Conference Proceedings

41. Lan, T., Li, Z.^#, Li, Z.^$, Bai, L.^$, Li, M.^#, Tsung, F.^&, Ketter, W.^&, Zhao, R.^$, and Zhang, C.* (2023), MM-DAG: Multi-task DAG Learning for Multi-modal Data - with Application for Traffic Congestion Analysis, Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 1188-1199.

42. Zhang, W., Zhang, C.*, and Tsung, F.^& (2022), GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning, 31st International Joint Conference on Artificial Intelligence (IJCAI), 2390-2397.

43. Zhang, W., Zhang, C., and Tsung, F.^& (2021), Transformer Based Spatial-Temporal Fusion Network for Metro Passenger Flow Forecasting, IEEE 17th International Conference on Automation Science and Engineering (CASE), 1515-1520.

44. He, B., Li,S.^#, Zhang, C.*, Zheng, B.^&, and Tsung, F.^& (2021), Holistic Prediction for Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach, Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PCDD), 321-336.

45. Li, Z., Yan, H.^#, Zhang, C. and Tsung, F.^& (2020), Tensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction, 34^th AAAI Conference on Artificial Intelligence, 4804-4810.

46. Zhang, C., and Hoi, C.H.^&* (2019), Online Learning for Partially Observable Multisensor Sequential Change Detection, 33^rd AAAI Conference on Artificial Intelligence, 5733-5740.

Book Chapters

47. Liu, P., Zhang, C.*, Advanced Data Analytical Techniques for Profile Monitoring. in Multimodal and Tensor Data Analytics for Industrial Systems Improvement (pp. 21-39). Cham: Springer International Publishing.

48. Zhang, C., Wang, K.^&, Tsung, F.^&, Big Data, in International Encyclopedia of Statistical Science, 2nd Edition, Ed. Lovric, M., Springer, New York, May, 2025.

49. Zhang, C., Li, Y.^&, Tsung, F.^&, Industrial Big Data, in International Encyclopedia of Statistical Science, 2nd Edition, Ed. Lovric, M., Springer, New York, May, 2025.

A. Courses Taught over the Past Three Years

Courses taught in previous years include: Advanced Quality Management (Spring 2019, Spring 2020, Spring 2021), Advanced Statistics (Fall 2020, Fall 2021), Machine Learning and Big Data (Fall 2019, Fall 2020, Fall 2021), Engineering Economics (Fall 2019)

B. Graduate Student Advising

Ph.D. students

1.Xing Yang, 2023, “Application of Multi-type Bayesian Networks in Industrial Big Data”

First Position: Assistant Professor, Shenzhen University

Academic Awards:

·Feature Article in ISE Magazine for the paper “Federated Multi-task Bayesian Network Learning in the Presence of Overlapping and Distinct Variables”

·Feature Article in ISE Magazine for the paper “Online Directed Structural Change-point Detection: A Segment-wise Time-varying Dynamic Bayesian Network Approach”

2.Wanshan Li, 2023, “Intelligent Maintenance of Networked Infrastructure: Statistical Modeling and Stochastic Optimization”

First Position: Assistant Professor, Jinan University (Zhuhai)

Academic Awards:

·Outstanding Ph.D. Dissertation, Tsinghua University

·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.

3.Peiyao Liu, 2025, “Statistical Modeling and Anomaly Detection for Complex Functional Data”

First Position: Research Fellow in National University of Singapore

Academic Awards:

·2nd Place, INFORMS 2024 Annual Meeting Data Mining and Data Analytics Workshop Best Paper Competition

· Finalist, INFORMS 2023 Annual Meeting Quality Statistics and Reliability Best Referee Paper Competition for the paper “Thompson Sampling based Partially Observable Online Monitoring Approach for Large Dynamic Networks”

·Finalist, IISE 2020 Annual Meeting Quality Statistics and Reliability Best Student Paper Competition for the paper “Real-Time Monitoring of Complex Correlated Multi-Channel Profiles in Advanced Manufacturing System”

·Outstanding Ph.D. Dissertation, Tsinghua University

4.Jie Guo, 2025, “Adaptive Sampling based Partially Observable Complex Data Change Detection”

First Position: Associate professor (without tenure) in Nanjing University of Aeronautics and Astronautics

Academic Awards:

·2nd Place, INFORMS 2023 Annual Meeting Data Mining and Data Analytics Workshop Best Paper Competition for the paper “Thompson Sampling based Partially Observable Online Monitoring Approach for Large Dynamic Networks”

·Finalist, INFORMS 2020 Annual Meeting Data Mining Section Best Student Paper Competition for the paper “Thompson Sampling based Partially Observable Online Change Detection via Bayesian Spike-Slab Composite Decomposition”

5.Haijie Xu, 2027 (expected), “Functional Data Modeling and Anomaly Detection”

Academic Awards:

·1st Prize, 2nd National Mathematics & Statistics Ph.D. Forum for the paper “Nonparametric Regression for Continuous Multi-way Data”

6.Tian Lan, 2028 (expected), “Multivariate Time Series Analysis Based on Causal Inference”

7.Xuming An, 2028 (expected), “AI-assisted Disease Prediction and Diagnosis”

8.Hao Duong Le, 2029 (expected)

9.Yimeng Lu, 2029 (expected)

Master of Science students

1.Bingjie He, 2021, “Time Series Forecasting for Traffic Flow”

First Position: Master student, the University of California, Berkeley

Academic Awards:

·2nd Place, INFORMS 2021 Data Mining and Decision Analytics Workshop Best Poster Competition for the paper “Holistic Prediction for Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach”

2.Junpeng Lin, 2025, “Research on Data-Driven Non-stationary Spatiotemporal Prediction”

First Position: Huawei Company

Academic Awards:

·2nd Place, INFORMS 2024 Annual Meeting Data Mining and Data Analytics Workshop Best Paper Competition for the paper “Heterogeneous Multivariate Functional Time Series Modeling: A State Space Approach”

3.Hao Duong Le, 2025, “Causal Structure Discovery Using Large Language Models”

First Position: Ph.D. student in my group in Tsinghua University (start from Fall 2025)

A. Invited Seminars

1.Adaptive Sampling based Partially Observable Complex Data Change Detection, East China Normal University, 2025.04.21

2.AI-Assisted Computer-Aided M-Protein Diagnosis, Nanjing University of Aeronautics and Astronautics, School of Economics and Management, 2024.11

3.Causal Inference for Industrial Big Data, Nanjing University of Aeronautics and Astronautics, School of Economics and Management, 2023.11

4.Causal Inference for Industrial Big Data, Nanjing University of Science and Technology, School of Economics and Management, 2023.11

5.Thompson Sampling-based Partially Observable Online Change Detection for Exponential Families, National University of Singapore, 2023.06

6.Thompson Sampling-based Partially Observable Online Change Detection for Exponential Families, Beijing University of Technology, School of Statistics, 2023.04

7.Thompson Sampling-based Partially Observable Online Change Detection for Exponential Families, University of Cologne, Germany, 2022.11

8.Multi-Channel Profile Modeling and Monitoring for Complex Manufacturing Systems, Hong Kong University of Science and Technology (Guangzhou), 2022.02

9.Adaptive Sampling-based High-Dimensional Process Monitoring, Institute of Systems Science, Chinese Academy of Sciences, 2020.07

10.Multivariate Profile Data Modeling and Monitoring for Advanced Manufacturing, Beijing University of Technology, 2020.05

11.Urban Transportation Passenger Flow Data Analysis, Singapore Management University, 2019.09

12.Adaptive Sampling-based High-Dimensional Process Monitoring, Singapore Management University, 2019.08

13.Multi-Channel Profile Data Modeling and Monitoring with Applications in Advanced Manufacturing, Singapore Management University, 2019.02

B. Keynote and Journal Invited Presentations

14.A Markov-Switching Hidden Heterogeneous Network Autoregressive Model for Multivariate Time Series Data with Multimodality, IISE Annual Conference, IISE Best Paper Invited Session, 2025.05.31-06.03.

15.Thompson Sampling-based Partially Observable Online Change Detection for Exponential Families, 2023 China-Korea Quality Workshop, Keynote Speech, 2023.08.25-27.

16.In-profile Monitoring for Cluster-Correlated Data in Advanced Manufacturing Systems, INFORMS 2023 Annual Meeting, JQT Invited Session, 2023.10.15-18.

17.Modeling Tunnel Profile in the Presence of Coordinate Errors: A Gaussian Process-Based Approach, 2019 IISE Annual Conference, IISE Best Paper Invited Session, 2019.05.18-21.

C. Conference Presentations

18.Profile Data Analysis in Advanced Manufacturing, 2025 International Conference on Reliability, Maintainability and Safety, Shanghai, 2025.07.27-07.31.

19.Modeling and Monitoring for Profile Data in Advanced Manufacturing, Young Scholars Forum on Quality & Reliability (Sichuan University), 2024.10.25-26.

20.Partial Observable Online Change Detection, 2024 Beijing Institute of Technology Quality & Reliability Symposium, 2024.08.19.

21.Adaptive Sampling-based Anomaly Detection, 12th Symposium on Quality & Reliability Science and Technology, 2024.07.27-28.

22.Functional Tucker Decomposition for Functional Edged Network, The 7th International Conference on Econometrics and Statistics, 2024.07.17-19.

23.Causal Inference via Multi-Agent LLM, The 2nd INFORMS Conference on Quality Statistics and Reliability, 2024.07.01-03.

24.Industrial Big Data Analysis Based on Causal Inference, 2024 Annual Meeting of the Reliability Division, Chinese Society of Operations Research, 2024.04.19-21.

25.Statistical Monitoring Based on Adaptive Sampling, 344th Shuangqing Forum, National Natural Science Foundation, 2023.09.14-15.

26.Stream of Variation Based on Profiles in Multi-Stage Manufacturing, 2023 International Conference of Chinese Scholars in Industrial Engineering & Global Chinese Industrial Engineering and Logistics Management Dean Conference, 2023.08.14-15.

27.Adaptive Sampling-based Anomaly Detection for Exponential Families, 1st National Conference on Statistics and Data Science, 2023.07.11-13.

28.Adaptive Sampling-based Anomaly Detection for Exponential Families, 2nd International Workshop on Statistical Theory and Related Fields, 2023.07.07-09.

29.In-Profile Monitoring for Complex Manufacturing Systems, INFORMS 2021 Annual Meeting, 2021.10.24-27.

30.In-Profile Monitoring for Complex Manufacturing Systems, 2021 European Network for Business and Industrial Statistics, 2021.09.29-31.

31.Segment-wise Time-Varying Dynamic Bayesian Network Modeling, 2020 INFORMS Annual Meeting, 2020.10.07-13.

32.Bayesian Composite Decomposition-Based High-Dimensional Process Monitoring with Thompson Sampling, 2019 INFORMS Annual Meeting, 2019.10.20-23.

33.Online Learning for Partially Observable Multisensor Sequential Change Detection, 2018 INFORMS Annual Meeting, 2018.11.04-07.

Editorial Services

·2025.01—Present: Associate Editor, Technometrics

·2024.10—Present: Associate Editor, IISE Transactions

·2024.10—Present: Associate Editor, INFORMS Journal on Data Science

·2023.12—Present: Associate Editor, IEEE Transactions on Automation Science and Engineering

·Referees for IEEE Transactions on Reliability, IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, Journal of Manufacturing Systems, IEEE Robotics and Automation Letters, Journal of Multivariate Statistics

Professional Society Services

·2023—Present: Communication Officer, INFORMS Data Mining Community

·2024—Present: Council Member, Industrial Engineering Sub-Society, Optimization, Scheduling and Economic Mathematics Society of China

·2023—Present: Intelligent Manufacturing Systems Engineering Sub-Society, Systems Engineering Society of China

·2022—Present: Council Member, Intelligent Industrial Data Analytics and Optimization Sub-Society, Operations Research Society of China

Conference Organizing Activities

·Session Chair, 2025 IEEE 19th International Conference on Automation Science and Engineering, LA, 2025.08.17-21

·Member, Conference Program Committee, 13th International Symposium on Quality and Reliability Science and Technology, Beijing, 2025.07.06-2025.07.08

·Member, Conference Program Committee, The 3rd INFORMS Conference on Quality Statistics and Reliability, Singapore, 2025.06.30-2025.07.05

·Session Chair, 2024 Annual Conference of the Industrial Engineering Division of the Chinese Society of Optimization, Overall Planning and Economic Mathematics, Intelligent manufacturing and process control Session, Beijing, China, 2024.12.08-09

·Organizing Committee Member, 2024 INFORMS Annual Meeting, QSR Best Student Paper Competition Session, Seattle, Washington, USA, 2024.10.21-23

·Member, Conference Program Committee, 2024 Annual Conference of Institute for Quality and Reliability, Tsinghua University, Beijing, China, 2024.10.11-13

·Organizing Committee Member, ECCV 2^nd workshop on Vision-based Industrial Inspection (VISION), Milano, Italy, 2024.09.30.

·Session Chair, The 2nd INFORMS Conference on Quality Statistics and Reliability, Quality and Reliability Improvement in Advanced Manufacturing Session, Politecnico di Milano, Bovisa Campus, Milan, Italy, 2024.07.01-03

·Session Chair, The 2nd INFORMS Conference on Quality Statistics and Reliability, Application of Generative AI and LLM in Quality Engineering Session, Politecnico di Milano, Bovisa Campus, Milan, Italy, 2024.07.01-03

·Member, Conference Program Committee, 2023 Annual Conference of Institute for Quality and Reliability, Tsinghua University, Beijing, China, 2023.10.20-22

·Organizing Committee Member, 2023 INFORMS Annual Meeting , QSR Best Student Paper Competition Session, Phoenix, Arizona, USA, 2023.10.15-18

·Session Chair, 2023 INFORMS Annual Meeting, Structural Learning for Heterogeneous Data Session, Phoenix, Arizona, USA, 2023.10.15-18

·Session Chair, 2023 IEEE 19th International Conference on Automation Science and Engineering, Structural Learning for Heterogeneous Data Session, Auckland, New Zealand, 2023.08.26-30

·Member, Conference Program Committee, The 6th Academic Conference on Intelligent Manufacturing Systems Engineering, Beijing, China, 2023.08.19-20

·Member, Conference Program Committee, 2023 Annual Conference of Institute for Quality and Reliability, Tsinghua University, Beijing, China, 2022.08.19-21

·Member, Conference Program Committee, 10th International Symposium on Quality and Reliability Science and Technology, Beijing, China, 2021.11.05

·Member, Conference Program Committee, 2021 INFORMS Annual Meeting, QSR Best Student Paper Competition Session, California, USA, 2021.10.24-27

·Member, Conference Program Committee, 2020 Annual Conference of Institute for Quality and Reliability, Tsinghua University, Beijing, China, 2020.10.23

·Member, Conference Program Committee, 2019 Annual Conference of Institute for Quality and Reliability, Tsinghua University, Beijing, China, 2019.06.08-09

·Member, Conference Program Committee, 2018 Annual Conference of Institute for Quality and Reliability, Tsinghua University, Beijing, China, 2018.06.09-10