A New Degradation Indicator Based on a Statistical Anomaly Approach. - João Paulo Pordeus Gomes; Roberto Kawakami Harrop Galvão; Takashi Yoneyama; Bruno P. Leao (IEEE Trans. Reliab., 2016)

Asymmetric Unscented Transform for Failure Prognosis. - Bruno P. Leao; Takashi Yoneyama; João Paulo Pordeus Gomes (IEEE Trans. Reliab., 2016)

Using Degradation Messages to Predict Hydraulic System Failures in a Commercial Aircraft. - João Paulo Pordeus Gomes; Leonardo Ramos Rodrigues; Bruno P. Leao; Roberto Kawakami Harrop Galvão; Takashi Yoneyama (IEEE Trans Autom. Sci. Eng., 2018)

Big Data Processing for Power Grid Event Detection. - Bruno P. Leao; Dmitriy Fradkin; Yubo Wang; Sindhu Suresh (IEEE BigData, 2020)

Unsupervised Power System Event Detection and Classification Using Unlabeled PMU Data. - Tu Lan; You Lin; Jianhui Wang 001; Bruno P. Leao; Dmitriy Fradkin (ISGT-Europe, 2021)

Machine Learning-based False Data Injection Attack Detection and Localization in Power Grids. - Bruno P. Leao; Jagannadh Vempati; Ulrich Münz; Shashank Shekhar 001; Amit Pandey; David Hingos; Siddharth Bhela; Jing Wang; Chris Bilby (CNS, 2022)

Augmented Digital Twin for Identification of Most Critical Cyberattacks in Industrial Systems. - Bruno Paes Leao; Jagannadh Vempati; Siddharth Bhela; Tobias Ahlgrim; Daniel Arnold 001 (CoRR, 2023)

Data Augmentation of Multivariate Sensor Time Series using Autoregressive Models and Application to Failure Prognostics. - Douglas David Baptista de Souza; Bruno Paes Leao (CoRR, 2024)