Data-driven prognostic techniques for estimation of the remaining useful life of lithium-ion batteries. - Roozbeh Razavi-Far; Maryam Farajzadeh-Zanjani; Shiladitya Chakrabarti; Mehrdad Saif (ICPHM, 2016)

Multi-step-ahead prediction techniques for Lithium-ion batteries condition prognosis. - Roozbeh Razavi-Far; Shiladitya Chakrabarti; Mehrdad Saif (SMC, 2016)

Multi-class heteroscedastic linear dimensionality reduction scheme for diagnosing process faults. - Shiladitya Chakrabarti; Roozbeh Razavi-Far; Mehrdad Saif; Luis Rueda 001 (CCECE, 2017)

Multi-step parallel-strategy for estimating the remaining useful life of batteries. - Roozbeh Razavi-Far; Shiladitya Chakrabarti; Mehrdad Saif (CCECE, 2017)

Extreme Learning Machine Based Prognostics of Battery Life. - Roozbeh Razavi-Far; Shiladitya Chakrabarti; Mehrdad Saif; Enrico Zio; Vasile Palade (Int. J. Artif. Intell. Tools, 2018)

An integrated imputation-prediction scheme for prognostics of battery data with missing observations. - Roozbeh Razavi-Far; Shiladitya Chakrabarti; Mehrdad Saif; Enrico Zio (Expert Syst. Appl., 2019)

Correlation Clustering Imputation for Diagnosing Attacks and Faults With Missing Power Grid Data. - Roozbeh Razavi-Far; Maryam Farajzadeh-Zanjani; Mehrdad Saif; Shiladitya Chakrabarti (IEEE Trans. Smart Grid, 2020)

Imputation-Based Ensemble Techniques for Class Imbalance Learning. - Roozbeh Razavi-Far; Maryam Farajzadeh-Zanjani; Boyu Wang 004; Mehrdad Saif; Shiladitya Chakrabarti (IEEE Trans. Knowl. Data Eng., 2021)

An integrated framework for diagnosing process faults with incomplete features. - Roozbeh Razavi-Far; Mehrdad Saif; Vasile Palade; Shiladitya Chakrabarti (Knowl. Inf. Syst., 2022)