张晨 - 清华大学 - 工业工程系

个人简介

教育背景 2013— 2017 新加坡国立大学工业系统工程管理博士 2008—2012 天津大学电子科学与技术学士工作经历 2020—至今 : 清华大学工业工程系副教授 2018—2020 : 清华大学工业工程系助理教授 2017—2018: 新加坡管理大学信息系统学院博士后所获奖励第八届中国科协青年人才托举工程，2022-2024 IEEE Conference on Automation Science and Engineering, 2020, 最佳论文奖美国质量协会（ASQ）Brumbaugh Award, 2019 IISE Transactions最佳论文奖, 2018，2019 新加坡半导体金牌, 2018 管理科学与运筹学会（INFORMS）数据挖掘(DM)分会最佳论文奖, 2017 管理科学与运筹学会（INFORMS）质量统计可靠性(QSR)分会最佳学生展板奖, 2016

研究领域

系统信息学：工业大数据建模（半导体制造，航空航天制造，钢铁冶金）, 质量管理, 统计过程监控智慧交通：城市轨道交通数据挖掘，交通拥堵根因分析智能医学：个性化医疗，基于人工智能的医学影像分析

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

期刊 Yang, X., and Zhang, C.* (2023) Online Directed Structural Change-point Detection: A Segment-wise Time-varying Dynamic Bayesian Network Approach, IISE Transactions, accepted. 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, accepted. Li, W., and Zhang, C.* (2022) A Markov-Switching Hidden Heterogeneous Network Autoregressive Model for Multivariate Time Series Data with Multimodality, IISE Transactions, online. Liu, P., Du, J., Zang, Y., Zhang, C.*, and Wang, K. (2022) Functional state-space model for multi-channel autoregressive profiles with application in advanced manufacturing, Journal of Quality Technology, online. 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, online. 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, online. Zhou, P., Liu, P., Wang, S., Zhang*, C., Zhang, J., and Li, S. (2022) Functional state-space model for multi-channel autore- gressive profiles with application in advanced manufacturing, Journal of Manufacturing Systems, 64, 356-371. Yang, X., Zhang, C.*, and Zheng, B. H. (2022) Structure Learning for Time-varying Dynamic Bayesian Network with Fused lasso and Graph Laplacian. ACM Transactions on Knowledge Discovery from Data, 16, (6), 1-23. 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, pages1247–1278. Guo, J., Yan, H., and Zhang, C.* (2022) A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling, Technometrics, online https://doi.org/10.1080/00401706.2022.2127914. 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. Wu, H., Zhang, C., and Li, Y F. (2021). Monitoring Heterogeneous Multivariate Profiles Based on Heterogeneous Graphical Model. Technometrics, 64(2), 210-223. Li, Z., Yan, H., Zhang, C. Tsung, F. (2020). Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile, IEEE Robotics and Automation Letters. Zhang, C. and Hoi, C.H. (2020) A Data-Driven Method for Online Monitoring Tube Wall Thinning Process in Dynamic Noisy Environment, accepted, IEEE Transactions on Automation, Systems and Engineering. Zhang, C., Hoi, C.H. and Tsung, F. (2020). Multivariate Functional Data Modeling via Nonnegative Functional Factorization with Time Warping, accepted, ACM Transactions on Knowledge Discovery from Data. Xian, X., Zhang, C., Bonk, S., and Liu, K. (2019). Online Monitoring of Big Data Streams: A Rank-based Sampling Algorithm by Data Augmentation," in press, Journal of Quality Technology. Wu, J., Xu, H., Zhang, C., and Yuan, Y. (2019). A Sequential Bayesian Partitioning Approach for Online Steady-State Detection of Multivariate Systems, in press, IEEE Transactions on Automation Science and Engineering. Zhang, C., Chen, N. and Wu, J. (2019). Spatial Rank based High-dimensional Monitoring Through Random Projection, accepted, Journal of Quality Technology. Zhang, C., Yan, H., Lee, S., and Shi, J. (2020). Dynamic Multivariate Functional data Modeling via Sparse Subspace Learning, accepted, Technometrics (2017 INFORMS Data Mining Section Best Paper Award). 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. 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(2016 INFORMS Quality, Statistics, and Reliability Section Best Student Poster Award). Zhang, C., Yan, H., Lee, S., and Shi, J. (2017). Multiple Profiles Sensor-Based Monitoring and Anomaly Detection, accepted, Journal of Quality Technology, 50:4, 344-362. Zhang, C., Lei, Y., Zhang, L., Chen N. (2017). Modeling Tunnel Profile in Presence of Coordinate Errors: A Gaussian Process Based Approach, IISE Transactions, 49(11), 1065-1077. Zhang, C., Chen, N., and Li, Z. (2016). State Space Modeling of Autocorrelated Multivariate Poisson Counts, IISE Transactions, 49(5), 518-531. 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. 会议 Lan, T., Ziyue Li, Zhishuai Li, Lei Bai, Man Li, Fugee Tsung, Wolfgang Ketter, Rui Zhao, and Chen Zhang*, “MM-DAG: Multi-task DAG Learning for Multi-modal Data - with Application for Traffic Congestion Analysis”, SIGKDD, 2023, accepted. 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), 2022. Zhang, W., Zhang, C., and Tsung, F., Transformer Based Spatial-Temporal Fusion Network for Metro Passenger Flow Forecasting, 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), 2021, pp. 1515-1520. He, B., Li S, Zhang, C.*, Zheng B., and Tsung, F. 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). Springer, Cham, 2021: 321-336. Li, Z., Yan, H., Zhang, C. and Tsung, F (2020). Tensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction", accepted, 34th AAAI Conference on Artificial Intelligence, 2020. Zhang, C., and Hoi, C.H. (2019). Online Learning for Partially Observable Multisensor Sequential Change Detection, 33rd AAAI Conference on Artificial Intelligence 2019. Wang, R., Chen, N. and Zhang, C. (2018). Clustering Subway Station Arrival Patterns Using Weighted Dynamic Time Warping, in 2018 IEEM, pp 531-535. Zhang, C., Zhang, L., and Chen, N. (2017). Spectral Network Approach for Multi-channel Profile Data Analysis with Applications in Advanced Manufacturing,in 2017 IEEM, pp. 1709-1713. Zhang, C., Chen, N., and Zhang, L. (2016). Time Series of Multivariate Zero-inflated Poisson Counts,in 2016 IEEM pp. 1365-1369. Zhang, C., and Chen, N. (2015). Statistical Monitoring of Longitudinal Categorical Survey Data, in 2015 IEEM pp. 1397-1401. Zhang, C., and Chen, N. (2014). Robust On-line Monitoring for Univariate Processes Based on Two Sample Goodness-of-fit Test,in 2014 IEEM pp. 813-817.