Research

My research concentrates on big data analytics to develop systematic data-driven analytics methodologies for process modeling, quality control, and performance improvement in computationally aware systems. By incorporating engineering domain knowledge with advanced techniques in statistics and machine learning, the  methodologies facilitate (i) the identification of appropriate and robust models that describe the system structures and dynamics, (ii) the effective surveillance of system status, (iii) the more accurate forecasting of future trends and dynamics, and (iv) the informative decisions that improve the system productivity and performance. The generic research leads to immediate applications in manufacturing, healthcare, traffic, climate, energy and service systems, etc.

Google scholar
  1. Di Wang, Ying Wang, and Xiaochen Xian, “An Adaptation-Aware Interactive Learning Approach for Multiple Operational Condition-based Degradation Modeling”, IEEE Transactions on Neural Networks and Learning Systems, accepted.
  2. Yaodan Hu, Xiaochen Xian, Shuo Wang and Yier Jin (2023+), “Fairness Guaranteed DER Coordination under False Data Injection Attacks”, IEEE Internet of Things Journal, accepted.
  3. Danit Shifman Abukasis, Izack Cohen, Kejun Huang, Xiaochen Xian, Gonen Singer (2023+), “Adaptive Learning for the Resource-Constrained Classification Problem”, Engineering Applications of Artificial Intelligence, accepted.
  4. Di Wang, Xiaochen Xian, and Changyue Song (2023+), “Joint Learning of Failure Mode Recognition and Prognostics for Degradation Processes”, IEEE Transactions on Automation Science and Engineering, accepted.
  5. Jinwei Yao, Xiaochen Xian, and Chao Wang (2023+), “Adaptive Sampling for Monitoring Multi-profile with Within-and-between Profile Correlation”, Technometrics, accepted.
  6. Xin Zan and Xiaochen Xian (2022+), “Nonparametric Adaptive Sampling for Online Monitoring Correlated Big Data Streams Using Spatial Rank”, Technometrics, accepted.
  7. Xiaochen Xian, Alexander Semenov, Yaodan Hu, Andi Wang, and Yier Jin (2022+), “Adaptive Sampling and Anomaly Detection in Dynamic Networks”, IEEE Transactions on Automation Science and Engineering, accepted.
  8. Honghan Ye, Xiaochen Xian, Jing-Ru C. Cheng, Brock Hable, Robert W. Shannon, Mojtaba Kadkhodaie Elyaderani, and Kaibo Liu (2022+), “Online nonparametric monitoring of heterogeneous data streams with partial observations based on Thompson sampling”, IISE Transactions, accepted. (This paper was a finalist for QCRE Best Student Paper Competition)
  9. Andrew D. Hanson, Donald R. McCarty, Christopher S. Henry, Xiaochen Xian, Jaya Joshi, Jenelle A. Patterson, Jorge D. García-García, Scott D. Fleischmann, Nathan D. Tivendale, and A. Harvey Millar (2021), “The number of catalytic cycles in an enzyme’s lifetime and why it matters to metabolic engineering”, Proceedings of the National Academy of Sciences, 118(13), e2023348118.
  10. Xiaochen Xian, Chen Zhang, Scott Bonk, and Kaibo Liu (2021), “Online monitoring of big data streams: a rank-based sampling algorithm by data augmentation”, Journal of Quality Technology, 53(2), 135-153. (This paper is selected for presentation in the JQT invited session in the 2021 INFORMS conference)
  11. Hu, Yaodan, Xiaochen Xian, and Yier Jin (2021, May), RADM: a risk-aware DER management framework with real-time DER trustworthiness evaluation. In Proceedings of the ACM/IEEE 12th International Conference on Cyber-Physical Systems (pp. 77-86).
  12. Xiaochen Xian, Honghan Ye, Xin Wang, and Kaibo Liu (2021), “Spatiotemporal modeling and real-time prediction of origin-destination traffic demand”, Technometrics, 63(1), 77-89. (Feature article in AIE, 2021, and YoungStats, 2021)
  13. Xiaochen Xian, Devashish Das, Kalyan S. Pasupathy, Eric T. Boie, and Mustafa Sir (2020), “Quantifying the Impact of Resuscitation-Team Activation in Hospital Emergency Departments”, IEEE Journal of Biomedical and Health Informatics, 24(10), 3029-3037.
  14. Xiaochen Xian, Andi Wang, and Kaibo Liu (2018), “A Nonparametric Adaptive Sampling Strategy for On-line Monitoring of Big Data Streams”, Technometrics, 60(1), 14-25. (This paper received the Best Student Poster award in Quality, Statistics, and Reliability Section of INFORMS, 2016; This paper is selected for presentation in the Technometrics invited session in the 2018 INFORMS conference)
  15. Xiaochen Xian, Jian Li, and Kaibo Liu (2018), “Causation-based monitoring and diagnosis for multivariate categorical processes with ordinal information”, IEEE Transactions on Automation Science and Engineering, 16(2), 886-897. (Best Paper Award in IEEE Transactions on Automation Science and Engineering, second runner-up)
  16. Andi Wang, Xiaochen Xian, Fugee Tsung, and Kaibo Liu (2018), “A spatial adaptive sampling procedure for monitoring of big data streams”, Journal of Quality Technology, 50(4), 329-343. (This paper is selected for presentation in the Journal of Quality Technology invited session in the 2019 INFORMS conference)
  17. Xiaochen Xian, Rich Archibald, Benjamin Mayor, Kaibo Liu, and Jian Li (2018), “An Effective Online Data Monitoring and Saving Strategy for Large-Scale Climate Simulations”, Quality Technology & Quantitative Management, 16(3), 330-346.
  18. Jian Li, Kaibo Liu, and Xiaochen Xian (2017), “Causation-based Process Monitoring and Diagnosis for Multivariate Categorical Processes”, IISE Transactions, 49(3), 332–343. (Feature article in IISE Magazine, 2017; This paper is selected for presentation in the IISE Transactions sponsored session in the 2018 INFORMS conference).
  19. Lin, Ling, Xiaochen Xian, Yujie Yan, Xing He, and Zhiyi Tan (2015), “Inefficiency of Equilibria for Scheduling Game with Machine Activation Costs”, Theoretical Computer Science, 607, 193-207.
  20. Changyue Song, Kaibo Liu, Xi Zhang, Lili Chen, and Xiaochen Xian (2015), “An obstructive sleep apnea detection approach using a discriminative hidden Markov model from ECG signals”, IEEE Transactions on Biomedical Engineering, 63(7), 1532-1542.