Experience with the Development and Deployment of Expert Systems in Agriculture. - Ahmed A. Rafea; Sayed El-Azhari; Iman Ibrahim; Soliman Edres; Mostafa Mahmoud (IAAI, 1995)

Using expert systems technology to increase agriculture production and water conservation. - Mostafa Mahmoud; Mahmoud Rafea; Ahmed A. Rafea (ICDIM, 2008)

Usability and its Role in Enhancing the Online User Experience in the Egyptian Web-Based Governmental Services Portals. - Mostafa Mahmoud; Aboul El Neil (WEBIST (2), 2008)

Memory controller design under cloud workloads. - Mostafa Mahmoud; Andreas Moshovos (IISWC, 2016)

IDEAL: image denoising accelerator. - Mostafa Mahmoud; Bojian Zheng; Alberto Delmas Lascorz; Felix Heide; Jonathan Assouline; Paul Boucher; Emmanuel Onzon; Andreas Moshovos (MICRO, 2017)

Characterizing Sources of Ineffectual Computations in Deep Learning Networks. - Milos Nikolic 002; Mostafa Mahmoud; Andreas Moshovos (IISWC, 2018)

Memory Requirements for Convolutional Neural Network Hardware Accelerators. - Kevin Siu; Dylan Malone Stuart; Mostafa Mahmoud; Andreas Moshovos (IISWC, 2018)

Diffy: a Déjà vu-Free Differential Deep Neural Network Accelerator. - Mostafa Mahmoud; Kevin Siu; Andreas Moshovos (MICRO, 2018)

Identifying and Exploiting Ineffectual Computations to Enable Hardware Acceleration of Deep Learning. - Andreas Moshovos; Jorge Albericio; Patrick Judd; Alberto Delmas; Sayeh Sharify; Mostafa Mahmoud; Tayler H. Hetherington; Milos Nikolic 002; Dylan Malone Stuart; Kevin Siu; Zissis Poulos; Tor M. Aamodt; et al. (NEWCAS, 2018)

Bit-Tactical: Exploiting Ineffectual Computations in Convolutional Neural Networks: Which, Why, and How. - Alberto Delmas; Patrick Judd; Dylan Malone Stuart; Zissis Poulos; Mostafa Mahmoud; Sayeh Sharify; Milos Nikolic 002; Andreas Moshovos (CoRR, 2018)

Laconic Deep Learning Computing. - Sayeh Sharify; Mostafa Mahmoud; Alberto Delmas Lascorz; Milos Nikolic 002; Andreas Moshovos (CoRR, 2018)

Bit-Tactical: A Software/Hardware Approach to Exploiting Value and Bit Sparsity in Neural Networks. - Alberto Delmas Lascorz; Patrick Judd; Dylan Malone Stuart; Zissis Poulos; Mostafa Mahmoud; Sayeh Sharify; Milos Nikolic 002; Kevin Siu; Andreas Moshovos (ASPLOS, 2019)

Laconic deep learning inference acceleration. - Sayeh Sharify; Alberto Delmas Lascorz; Mostafa Mahmoud; Milos Nikolic 002; Kevin Siu; Dylan Malone Stuart; Zissis Poulos; Andreas Moshovos (ISCA, 2019)

Characterizing Sources of Ineffectual Computations in Deep Learning Networks. - Milos Nikolic 002; Mostafa Mahmoud; Andreas Moshovos; Yiren Zhao; Robert D. Mullins (ISPASS, 2019)

ShapeShifter: Enabling Fine-Grain Data Width Adaptation in Deep Learning. - Alberto Delmas Lascorz; Sayeh Sharify; Isak Edo Vivancos; Dylan Malone Stuart; Omar Mohamed Awad; Patrick Judd; Mostafa Mahmoud; Milos Nikolic 002; Kevin Siu; Zissis Poulos; Andreas Moshovos (MICRO, 2019)

Accelerating Image-Sensor-Based Deep Learning Applications. - Mostafa Mahmoud; Dylan Malone Stuart; Zissis Poulos; Alberto Delmas Lascorz; Patrick Judd; Sayeh Sharify; Milos Nikolic 002; Kevin Siu; Isak Edo Vivancos; Jorge Albericio; Andreas Moshovos (IEEE Micro, 2019)

Late Breaking Results: Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick. - Isak Edo Vivancos; Sayeh Sharify; Milos Nikolic 002; Ciaran Bannon; Mostafa Mahmoud; Alberto Delmas Lascorz; Andreas Moshovos (DAC, 2020)

TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training. - Mostafa Mahmoud; Isak Edo; Ali Hadi Zadeh; Omar Mohamed Awad; Gennady Pekhimenko; Jorge Albericio; Andreas Moshovos (MICRO, 2020)

TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training and Inference. - Mostafa Mahmoud; Isak Edo Vivancos; Ali Hadi Zadeh; Omar Mohamed Awad; Gennady Pekhimenko; Jorge Albericio; Andreas Moshovos (CoRR, 2020)

FPRaker: A Processing Element For Accelerating Neural Network Training. - Omar Mohamed Awad; Mostafa Mahmoud; Isak Edo; Ali Hadi Zadeh; Ciaran Bannon; Anand Jayarajan; Gennady Pekhimenko; Andreas Moshovos (MICRO, 2021)

Boveda: Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick. - Isak Edo Vivancos; Sayeh Sharify; Daniel Ly-Ma; Ameer Abdelhadi; Ciaran Bannon; Milos Nikolic 002; Mostafa Mahmoud; Alberto Delmas Lascorz; Gennady Pekhimenko; Andreas Moshovos (MLSys, 2021)

Mokey: enabling narrow fixed-point inference for out-of-the-box floating-point transformer models. - Ali Hadi Zadeh; Mostafa Mahmoud; Ameer Abdelhadi; Andreas Moshovos (ISCA, 2022)

APack: Off-Chip, Lossless Data Compression for Efficient Deep Learning Inference. - Alberto Delmas Lascorz; Mostafa Mahmoud; Andreas Moshovos (CoRR, 2022)

Schrödinger's FP: Dynamic Adaptation of Floating-Point Containers for Deep Learning Training. - Milos Nikolic 002; Enrique Torres-Sánchez; Jiahui Wang; Ali Hadi Zadeh; Mostafa Mahmoud; Ameer Abdelhadi; Andreas Moshovos (CoRR, 2022)

Power Level Control of Nuclear Power Plants During Load Following Operation Using Fractional Order Controller Based on a Modified Algorithm. - Tarek A. Boghdady; Mostafa Mahmoud; Essam El-Din Abou El-Zahab; Elsayed Tag-Eldin; Mahmoud M. Sayed (IEEE Access, 2023)

Every Bit Matters: A Hardware/Software Approach for Enabling More Powerful Machine Learning Models. - Enrique Torres-Sánchez; Milos Nikolic 002; Kareem Ibrahim; Alberto Delmas Lascorz; Ali Hadi Zadeh; Jiahui Wang; Ameer Abdelhadi; Mostafa Mahmoud; Christina Giannoula; Andreas Moshovos (IEEECONF, 2024)

Atalanta: A Bit is Worth a "Thousand" Tensor Values. - Alberto Delmas Lascorz; Mostafa Mahmoud; Ali Hadi Zadeh; Milos Nikolic 002; Kareem Ibrahim; Christina Giannoula; Ameer Abdelhadi; Andreas Moshovos (ASPLOS (2), 2024)

Marple: Scalable Spike Sorting for Untethered Brain-Machine Interfacing. - Eugene Sha; Andy Liu; Kareem Ibrahim; Mostafa Mahmoud; Christina Giannoula; Ameer Abdelhadi; Andreas Moshovos (ASPLOS (2), 2024)

Schrodinger's FP Training Neural Networks with Dynamic Floating-Point Containers. - Milos Nikolic 002; Enrique Torres-Sánchez; Jiahui Wang; Ali Hadi Zadeh; Mostafa Mahmoud; Ameer Abdelhadi; Kareem Ibrahim; Andreas Moshovos (MLSys, 2024)