Low Power Speaker Identification using Look Up-free Gaussian Mixture Model in CMOS. - Alberto Gianelli; Nick Iliev; Shamma Nasrin; Mariagrazia Graziano; Amit Ranjan Trivedi (COOL CHIPS, 2019)

Towards Co-designing Neural Network Function Approximators with In-SRAM Computing. - Shamma Nasrin; Diaa Badawi; Ahmet Enis Çetin; Wilfred Gomes; Amit Ranjan Trivedi (EMC2@NeurIPS, 2019)

Supported-BinaryNet: Bitcell Array-based Weight Supports for Dynamic Accuracy-Latency Trade-offs in SRAM-based Binarized Neural Network. - Shamma Nasrin; Srikanth Ramakrishna; Theja Tulabandhula; Amit Ranjan Trivedi (CoRR, 2019)

Supported-BinaryNet: Bitcell Array-Based Weight Supports for Dynamic Accuracy-Energy Trade-Offs in SRAM-Based Binarized Neural Network. - Shamma Nasrin; Srikanth Ramakrishna; Theja Tulabandhula; Amit Ranjan Trivedi (ISCAS, 2020)

Compute-in-Memory Upside Down: A Learning Operator Co-Design Perspective for Scalability. - Shamma Nasrin; Priyesh Shukla; Shruthi Jaisimha; Amit Ranjan Trivedi (DATE, 2021)

ENOS: Energy-Aware Network Operator Search for Hybrid Digital and Compute-in-Memory DNN Accelerators. - Shamma Nasrin; Ahish Shylendra; Yuti Kadakia; Nick Iliev; Wilfred Gomes; Theja Tulabandhula; Amit Ranjan Trivedi (CoRR, 2021)

MF-Net: Compute-In-Memory SRAM for Multibit Precision Inference Using Memory-Immersed Data Conversion and Multiplication-Free Operators. - Shamma Nasrin; Diaa Badawi; Ahmet Enis Çetin; Wilfred Gomes; Amit Ranjan Trivedi (IEEE Trans. Circuits Syst. I Regul. Pap., 2021)

ENOS: Energy-Aware Network Operator Search in Deep Neural Networks. - Shamma Nasrin; Ahish Shylendra; Nastaran Darabi; Theja Tulabandhula; Wilfred Gomes; Ankush Chakrabarty; Amit Ranjan Trivedi (IEEE Access, 2022)

Memory-Immersed Collaborative Digitization for Area-Efficient Compute-in-Memory Deep Learning. - Shamma Nasrin; Maeesha Binte Hashem; Nastaran Darabi; Benjamin Parpillon; Farah Fahim; Wilfred Gomes; Amit Ranjan Trivedi (AICAS, 2023)

MC-CIM: Compute-in-Memory With Monte-Carlo Dropouts for Bayesian Edge Intelligence. - Priyesh Shukla; Shamma Nasrin; Nastaran Darabi; Wilfred Gomes; Amit Ranjan Trivedi (IEEE Trans. Circuits Syst. I Regul. Pap., 2023)

Machine-learning based Blind Digital Calibration of Time-Interleaved ADC. - Sumukh Prashant Bhanushali; Shamma Nasrin; Debnath Maiti; Arindam Sanyal (VTS, 2025)

From Signals to Features to Insights: Multi-Level Novelty Detection for Fast Scientific Discovery. - Devashri Naik; Nastaran Darabi; Sina Tayebati; Dinithi Jayasuriya; Shamma Nasrin; Danush Shekar; Corrinne Mills; Benjamin Parpillon; Farah Fahim; Mark S. Neubauer; Amit Ranjan Trivedi (VTS, 2025)

MOSAIC: Collaborative Compute-in-Memory µArrays for Flexible and Scalable Deep Learning. - Amit Ranjan Trivedi; Shamma Nasrin; Priyesh Shukla; Nastaran Darabi; Divake Kumar; Dinithi Jayasuriya; Nethmi Jayasinghe (VTS, 2025)