Assistant Professor
Education
- Ph.D. Industrial and Systems Engineering (2019), University of Wisconsin-Madison
- M.S. Statistics (2017), University of Wisconsin-Madison
- B.S. Mathematics and Applied Mathematics (2014), Zhejiang University
About
Dr. Xiaochen Xian is an assistant professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE). Prior to joining ISyE, she served as an assistant professor in the UF ISE department. Her research interest mainly focuses on big data analytics and system informatics to develop data-driven methodologies for computationally aware systems. Specifically, her research includes big data stream monitoring and sampling, engineering knowledge-enhanced complex process modeling and diagnosis, on-demand machine learning, and system informatics and spatiotemporal real-time prediction. Her research leads to immediate applications in manufacturing, healthcare, environmental monitoring, smart buildings, and traffic, etc. Dr. Xian received her B.S. from the Department of Mathematics, Zhejiang University, Hangzhou, China, in 2014, and her M.S. in Statistics and Ph.D. in Industrial Engineering from the University of Wisconsin-Madison in 2017 and 2019. She is a member of INFORMS, IISE, and IEEE.
Research
Dr. Xian's research interest mainly focuses on big data analytics and system informatics to develop data-driven methodologies for computationally aware systems. Specifically, her research includes big data stream monitoring and sampling, engineering knowledge-enhanced complex process modeling and diagnosis, on-demand machine learning, and system informatics and spatiotemporal real-time prediction. Her research leads to immediate applications in manufacturing, healthcare, environmental monitoring, smart buildings, and traffic, etc.
Teaching
Dr. Xian has been teaching courses related to data analytics, statistics, and quality improvement.
Representative Publications
[1] * Di Wang, Xiaochen Xian and Haidong Li (2025), “Event-based Dynamic Network Modeling Via Spatiotemporal Interactive Hawkes Processes”,Technometrics 67, no. 2: 293-310.
[2] * Dongmin Li, Miao Bai, DiWang, and Xiaochen Xian (2025), “A Bayesian Jump Model-based Pathwise Sampling Approach for Online Anomaly Detection”, accepted by IISE Transactions.
[3] * Yaxi Luo, Meng Jiao, Neel Fotedar, Jun-En Ding, Ioannis Karakis, Vikram R Rao, Melissa Asmar, Xiaochen Xian, Orwa Aboud, Yuxin Wen, Jack J Lin, Fang-Ming Hung, Hai Sun, Felix Rosenow, Feng Liu, (2025) ”Clinical Value of ChatGPT for Epilepsy Presurgical Decision-Making: Systematic Evaluation of Seizure Semiology Interpretation.” Journal of medical Internet research, 27, e69173.
[4] * Meng Jiao, Shihao Yang, Xiaochen Xian, Neel Fotedar, Feng Liu, (2025) “Multi-modal electrophysiological source imaging with attention neural networks based on deep fusion of EEG and MEG”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, accepted.
[5] * Di Wang, Andi Wang, Xiaochen Xian, and Yongxiang Li, (2025) “Partially Observable Online Nonparametric Monitoring of Spatiotemporally Correlated Data Streams”, accepted, Technometrics.
[6] * Xin Zan, DiWang, Changyue Song, Feng Liu, Xiaochen Xian, Richard Berry, (2025) “Weakly Supervised Deep Learning for Monitoring Sleep Apnea Severity Using Coarse-grained Labels”, accepted at IEEE Transactions on Automation Science and Engineering.
[7] * Xianjian Xie, Andi Wang, Xiaochen Xian, (2025) “Adversarial Client Detection via Nonparametric Subspace Monitoring in Internet of Federated Things”, IISE Transactions, 57 (7), 743-755.
[8] * Mohammad Yaseliani, Md Noor-E-Alam, Osama Dasa, Xiaochen Xian, Carl J. Pepine, and Md Mahmudul Hasan, (2025) ”A lightweight graph neural network to predict long-term mortality in coronary artery disease patients: an interpretable causality-aware approach.” Journal of Biomedical Informatics, 104846.
[9] Meng Jiao, Changyue Song, Shihao Yang, Xiaochen Xian, Feng Liu, (2024) “Deep Attention Networks with Multi-Temporal Information Fusion for Sleep Apnea Detection”, IEEE Open Journal of Engineering in Medicine and Biology, accepted.
[10] Xin Zan, Alexander Semenov, ChaoWang, Xiaochen Xian, andWondi Geremew, (2024) “Causality-aware Social Recommender System with Network Homophily Informed Multi-Treatment Confounders”, Information Sciences, 676, 120729.
[11] Dongmin Li, Miao Bai, Xiaochen Xian (2024), “Online Monitoring with Moving Sensors: Data-driven Pathwise Sampling Strategies”, Technometrics, 66(4), 600-613.
[12] Di Wang, Xiaochen Xian, Haidong Li, and Dong Wang (2024), “Distribution-agnostic Probabilistic Few-shot Learning for Multimodal Recognition and Prediction”, IEEE Transactions on Automation Science and Engineering, accepted.
[13] Di Wang, Yuhui Wang, and Xiaochen Xian (2024+), “A Latent Variable-Based Multitask Learning Approach for Degradation Modeling of Machines with Dependency and Heterogeneity”, IEEE Transactions on Instrumentation and Measurement, accepted.
[14] Xin Zan, Jaclyn Hall, Thomas Hladish, and Xiaochen Xian (2024), “Data-driven Adaptive Testing Resource Allocation Strategies for Real-time Monitoring of Infectious Diseases”, IISE Transactions, 56(12), 1279-1293.
[15] Meng Jiao, Xiaochen Xian, Boyu Wang, Yu Zhang, Shihao Yang, Spencer Chen, Hai Sun, Feng Liu, ”XDL-ESI: Electrophysiological Sources Imaging via explainable deep learning framework with validation on simultaneous EEG and iEEG”, Neuroimage, 299, 120802.
[16] Di Wang, Ying Wang, and Xiaochen Xian (2024+), “An Adaptation-Aware Interactive Learning Approach for Multiple Operational Condition-based Degradation Modeling”, IEEE Transactions on Neural Networks and Learning Systems, accepted.