May-17-2020: The paper "A Collaborative Gaussian Process Regression Model for Transfer Learning of Capacity Trends between Li-ion Battery Cells" by Abdallah A. Chehade and Ala A. Hussein was accepted at the IEEE Transactions on Vehicular Technology.

May-11-2020: The paper "Robust Artificial Neural Network-Based Models for Accurate Surface Temperature Estimation of Batteries" by Ala A. Hussein and Abdallah Chehade was accepted at the IEEE Transactions on Industry Applications.

May-01-2020: The paper "A Novel Neural Network with Gaussian Process Feedback (NNGP) for Modeling the State-of-Charge of Battery Cells" by Abdallah Chehade and Ala A Hussein was accepted at the 2020 IEEE Energy Conversion Congress and Exposition.

Apr-06-2020: Mayuresh Savargaonkar developed a dashboard to track COVID-19 trends at the Country and US County levels. COVID-19 Tracker

Apr-02-2020: Dr. Abdallah Chehade received a research funding grant from Ford Motor Company to Generate Synthetic Data for Training and Validation of SOTIF and AI-based Systems.

Mar-25-2020: The paper "Accelerating the Discovery of New DP-Steel Using Machine Learning-based Multiscale Materials Simulations" by Abdallah Chehade, Tarek Belgasam, Georges Ayoub, and Hussein Zbib was accepted at Metallurgical and Materials Transactions A.

Feb-28-2020: The paper "An Adaptive Deep Neural Network with Transfer Learning for State-of-Charge Estimations of Battery Cells" by Mayuresh Savargaonkar and Abdallah Chehade was accepted at the 2020 IEEE Transportation Electrification Conference & Expo.

Feb-28-2020: The paper "A Cycle-based Recurrent Neural Network for State-of-Charge Estimation of Li-ion Battery Cells" by Mayuresh Savargaonkar, Abdallah A. Chehade, Zunya Shi, and Ala A. Hussein was accepted at the 2020 IEEE Transportation Electrification Conference & Expo.

Feb-28-2020: The paper "A Long Short-Term Memory Network for Online State-of-Charge Estimation of Li-ion Battery Cells" by Zunya Shi, Mayuresh Savargaonkar, Abdallah A. Chehade, and Ala A. Hussein was accepted at the 2020 IEEE Transportation Electrification Conference & Expo.

Feb-19-2020: The paper "BLNN: An R Package for Training Neural Networks Using Bayesian Inference" by Taysseer Sharaf, Theren Williams, Abdallah Chehade, and Keshav Pokhrel was accepted at SoftwareX.

Feb-14-2020: The paper "Data-driven Adaptive Thresholding Model for Real-time Valve Delay Estimation in Digital Pump/Motors" by Abdallah Chehade, Farid Breidi, Keith Pate and John Lumkes was accepted at the International Journal of Fluid Power.

Feb-01-2020: Dr. Abdallah Chehade received a research funding grant from Ford Motor Company to Develop Hybrid Models for Warranty Data Forecasting based on Machine Learning & Reliability Theories.

Feb-01-2020: Dr. Abdallah Chehade & Dr. Youngki Kim received a research funding grant from Ford Motor Company to Develop Automated Machine Learning (AutoML) Models for Health Monitoring and Prognostics of Vehicle Components.

Dec-10-2019: The paper "Monitoring Digital Technologies in Hydraulic Systems Using CUSUM Control Charts" by Farid Breidi, Abdallah Chehade and John Lumkes was published at the ASME/BATH 2019 Symposium on Fluid Power and Motion Control.

Oct-23-2019: Zunya Shi presented her research work on "Long Short Term Memory Neural Networks for Remaining Useful Life Estimation" at INFORMS Annual Meeting.

Oct-22-2019: Dr. Chehade chaired the "Panel Session for Industrial Data Science" at INFORMS Annual Meeting.

Oct-21-2019: Dr. Chehade chaired the "Industry Job Hunting Session" at INFORMS Annual Meeting.

Oct-14-2019: Dr. Chehade received a research funding grant from Ford Motor Company on "Advanced Deep Learning Models for Warranty Data Analytics".

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