A Fast and Simple Block-Based Approach for Common Path Pessimism Removal in Static Timing Analysis. - Guojie Luo; Baihong Jin; Wentai Zhang 001 (CAD/Graphics, 2015)

Learning Convex Piecewise Linear Machine for Data-Driven Optimal Control. - Yuxun Zhou; Baihong Jin; Costas J. Spanos (ICMLA, 2015)

A Contract-based Framework for Integrated Demand Response Management in Smart Grids. - Baihong Jin; Pierluigi Nuzzo 002; Mehdi Maasoumy; Yuxun Zhou; Alberto L. Sangiovanni-Vincentelli (BuildSys, 2015)

A fast and accurate approach for common path pessimism removal in static timing analysis. - Baihong Jin; Guojie Luo; Wentai Zhang 001 (ISCAS, 2016)

Online computation of polytopic flexibility models for demand shifting applications. - Baihong Jin; Mehdi Maasoumy; Pierluigi Nuzzo 002; Alberto L. Sangiovanni-Vincentelli (CASE, 2017)

Design Automation for Smart Building Systems. - Ruoxi Jia 001; Baihong Jin; Ming Jin 002; Yuxun Zhou; Ioannis C. Konstantakopoulos; Han Zou; Joyce Kim; Dan Li 016; Weixi Gu; Reza Arghandeh; Pierluigi Nuzzo 002; Stefano Schiavon; et al. (Proc. IEEE, 2018)

A tractable ellipsoidal approximation for voltage regulation problems. - Pan Li 004; Baihong Jin; Ruoxuan Xiong; Dai Wang; Alberto L. Sangiovanni-Vincentelli; Baosen Zhang (ACC, 2019)

MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks. - Dan Li 016; Dacheng Chen; Baihong Jin; Lei Shi; Jonathan Goh; See-Kiong Ng (ICANN (4), 2019)

An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing. - Yingshui Tan; Baihong Jin; Alexander J. Nettekoven; Yuxin Chen 001; Yisong Yue; Ufuk Topcu; Alberto L. Sangiovanni-Vincentelli (ICMLA, 2019)

A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection. - Baihong Jin; Yuxin Chen 001; Dan Li 016; Kameshwar Poolla; Alberto L. Sangiovanni-Vincentelli (ICPHM, 2019)

Detecting and Diagnosing Incipient Building Faults Using Uncertainty Information from Deep Neural Networks. - Baihong Jin; Dan Li 016; Seshadhri Srinivasan; See-Kiong Ng; Kameshwar Poolla; Alberto L. Sangiovanni-Vincentelli (ICPHM, 2019)

Augmenting Monte Carlo Dropout Classification Models with Unsupervised Learning Tasks for Detecting and Diagnosing Out-of-Distribution Faults. - Baihong Jin; Yingshui Tan; Yuxin Chen 001; Alberto L. Sangiovanni-Vincentelli (CoRR, 2019)

Super-Resolution Reconstruction of Interval Energy Data. - Jieyi Lu; Baihong Jin (BuildSys, 2020)

Are Ensemble Classifiers Powerful Enough for the Detection and Diagnosis of Intermediate-Severity Faults? - Baihong Jin; Yingshui Tan; Yuxin Chen 001; Kameshwar Poolla; Alberto L. Sangiovanni-Vincentelli (CoRR, 2020)

Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI. - Yingshui Tan; Baihong Jin; Xiangyu Yue 001; Yuxin Chen 001; Alberto L. Sangiovanni-Vincentelli (CoRR, 2020)

Using Ensemble Classifiers to Detect Incipient Anomalies. - Baihong Jin; Yingshui Tan; Albert Liu; Xiangyu Yue 001; Yuxin Chen 001; Alberto L. Sangiovanni-Vincentelli (CoRR, 2020)

Generalizing Fault Detection Against Domain Shifts Using Stratification-Aware Cross-Validation. - Yingshui Tan; Baihong Jin; Qiushi Cui; Xiangyu Yue 001; Alberto L. Sangiovanni-Vincentelli (CoRR, 2020)

Gordian: Formal Reasoning-based Outlier Detection for Secure Localization. - Matthew Weber; Baihong Jin; Gil Lederman; Yasser Shoukry; Edward A. Lee; Sanjit Seshia; Alberto L. Sangiovanni-Vincentelli (ACM Trans. Cyber Phys. Syst., 2020)

Incipient Anomaly Detection with Ensemble Learning. - Baihong Jin (2020)

Explainable AI for Chiller Fault-Detection Systems: Gaining Human Trust. - Seshadhri Srinivasan; Pandarasamy Arjunan; Baihong Jin; Alberto L. Sangiovanni-Vincentelli; Zuraimi Sultan; Kameshwar Poolla (Computer, 2021)

Class-wise Thresholding for Detecting Out-of-Distribution Data. - Matteo Guarrera; Baihong Jin; Tung-Wei Lin; Maria A. Zuluaga; Yuxin Chen 001; Alberto L. Sangiovanni-Vincentelli (CoRR, 2021)

One-class graph neural networks for anomaly detection in attributed networks. - Xuhong Wang; Baihong Jin; Ying Du; Ping Cui; Yingshui Tan; Yupu Yang (Neural Comput. Appl., 2021)

Class-wise Thresholding for Robust Out-of-Distribution Detection. - Matteo Guarrera; Baihong Jin; Tung-Wei Lin; Maria A. Zuluaga; Yuxin Chen 001; Alberto L. Sangiovanni-Vincentelli (CVPR Workshops, 2022)

Predicting Electricity Infrastructure Induced Wildfire Risk in California. - Mengqi Yao; Meghana Bharadwaj; Zheng Zhang; Baihong Jin; Duncan S. Callaway (CoRR, 2022)