Xin Zan, Di Wang, and Xiaochen Xian (2023), “Spatial Rank-Based Augmentation for Nonparametric Online Monitoring and Adaptive Sampling of Big Data Streams”, Technometrics, 65(2), 243-256. DOI: https://doi.org/10.1080/00401706.2022.2143903.
Feature Article in Advances In Engineering.
Xin Zan, Jaclyn Hall, Tom Hladish, and Xiaochen Xian (2023), “Data-driven Adaptive Testing Resource Allocation Strategies for Real-time Monitoring of Infectious Diseases”, IISE Transactions, in press. DOI: https://doi.org/10.1080/24725854.2023.2266488.
Third Place Winner of the 2022 COVID Information Commons (CIC) Student Paper Challenge. (Invited for presentation in CIC Webinar and NEBDHub Student Research Symposium.)
Honorable Mention of the Best Student Poster Competition in Quality, Statistics and Reliability (QSR) Section of 2022 INFORMS Annual Meeting.
Finalist of the Best Paper Competition in Quality Control & Reliability Engineering (QCRE) Track of IISE Annual Conference and Expo 2022.
Xin Zan, Alexander Semenov, Chao Wang, Xiaochen Xian, and Wondi Geremew (2024), “Causality-aware Social Recommender System with Network Homophily Informed Multi-Treatment Confounders”, Information Sciences, 676, 120729. DOI: https://doi.org/10.1016/j.ins.2024.120729.
Xin Zan, Di Wang, Changyue Song, Feng Liu, Xiaochen Xian, and Richard Berry, “Weakly Supervised Deep Learning for Monitoring Sleep Apnea Severity Using Coarse-grained Labels”, IEEE Transactions on Automation Science and Engineering, under revision.
Invited for oral presentation at the 18th INFORMS Data Mining and Decision Analytics (DMDA) Workshop.
Xin Zan, Feng Liu, Xiaochen Xian, and Panos Pardalos, “Empowering Sleep Health: Unleashing the Potential of Artificial Intelligence and Data Science in Sleep Disorders”, In Handbook of AI and Data Sciences for Sleep Disorders, Springer Optimization and its Applications, in press.
Xin Zan, Minhee Kim, Changyue Song, Feng Liu, Xiaochen Xian, and Richard Berry, “A Dual-granularity Bayesian Active Learning Framework with Uncertainty Quantification for Sleep Apnea Severity Estimation”, to be submitted.
Xin Zan, Dongmin Li, and Xiaochen Xian, “Layer-wise Spatial Modeling and With-layer In-situ Monitoring for Additive Manufacturing Processes”, under preparation.
Finalist of the QSR Data Challenge Competition at 2021 INFORMS Annual Meeting.
Minhee Kim, Xin Zan, and Xiaochen Xian, “A Probabilistic Perspective: Bayesian Neural Network for Sleep Apnea Detection”, In Handbook of AI and Data Sciences for Sleep Disorders, Springer Optimization and its Applications, in press.