Hybrid TFET-MOSFET circuits: An approach to design reliable ultra-low power circuits in the presence of process variation. - Maede Hemmat; Mehdi Kamal; Ali Afzali-Kusha; Massoud Pedram (VLSI-SoC, 2016)

Robust Hybrid TFET-MOSFET Circuits in Presence of Process Variations and Soft Errors. - Maedeh Hemmat; Mehdi Kamal; Ali Afzali-Kusha; Massoud Pedram (VLSI-SoC (Selected Papers), 2016)

Hybrid TFET-MOSFET circuit: A solution to design soft-error resilient ultra-low power digital circuit. - Maede Hemmat; Mehdi Kamal; Ali Afzali-Kusha; Massoud Pedram (Integr., 2017)

Dynamic Reconfiguration of CNNs for Input-Dependent Approximation. - Maedeh Hemmat; Azadeh Davoodi (ISQED, 2019)

Power-efficient ReRAM-aware CNN model generation. - Maedeh Hemmat; Azadeh Davoodi (Integr., 2019)

CRANIA: Unlocking Data and Value Reuse in Iterative Neural Network Architectures. - Maedeh Hemmat; Tejas Shah; Yuhua Chen; Joshua San Miguel (ASP-DAC, 2020)

CAP'NN: Class-Aware Personalized Neural Network Inference. - Maedeh Hemmat; Joshua San Miguel; Azadeh Davoodi (DAC, 2020)

AirNN: A Featherweight Framework for Dynamic Input-Dependent Approximation of CNNs. - Maedeh Hemmat; Joshua San Miguel; Azadeh Davoodi (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021)

$ text{Edge}^{n}$ AI: Distributed Inference with Local Edge Devices and Minimal Latency. - Maedeh Hemmat; Azadeh Davoodi; Yu Hen Hu (ASP-DAC, 2022)

CAP'NN: A Class-aware Framework for Personalized Neural Network Inference. - Maedeh Hemmat; Joshua San Miguel; Azadeh Davoodi (ACM Trans. Embed. Comput. Syst., 2022)