Dynamic power estimation based on switching activity propagation. - Yehya Nasser; Jean-Christophe Prévotet; M. Heiard; Jordane Lorandel (FPL, 2017)

Power modeling on FPGA: a neural model for RT-level power estimation. - Yehya Nasser; Jean-Christophe Prévotet; Maryline Hélard (CF, 2018)

NeuPow: artificial neural networks for power and behavioral modeling of arithmetic components in 45nm ASICs technology. - Yehya Nasser; Carlo Sau; Jean-Christophe Prévotet; Tiziana Fanni; Francesca Palumbo; Maryline Hélard; Luigi Raffo (CF, 2019)

NeuPow: A CAD Methodology for High-level Power Estimation Based on Machine Learning. - Yehya Nasser; Carlo Sau; Jean-Christophe Prévotet; Tiziana Fanni; Francesca Palumbo; Maryline Hélard; Luigi Raffo (ACM Trans. Design Autom. Electr. Syst., 2020)

RTL to Transistor Level Power Modeling and Estimation Techniques for FPGA and ASIC: A Survey. - Yehya Nasser; Jordane Lorandel; Jean-Christophe Prévotet; Maryline Hélard (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021)

Toward Hardware-Assisted Malware Detection Utilizing Explainable Machine Learning: A Survey. - Yehya Nasser; Mohamed Nassar 001 (IEEE Access, 2023)

On Diversity in Discriminative Neural Networks. - Brahim Oubaha; Claude Berrou; Xueyao Ji; Yehya Nasser; Raphaël Le Bidan (ISIVC, 2024)

Power Consumption Analysis for Reverse Engineering Digital Modulation: A Novel Approach to Physical Layer Attacks on Communication Systems. - Pablo Pareja; Yehya Nasser; Ahmed Masmoudi 003; Sébastien Houcke (EICC, 2025)