Low-Power Audio Keyword Spotting using Tsetlin Machines. - Jie Lei; Tousif Rahman; Rishad A. Shafik; Adrian Wheeldon; Alex Yakovlev; Ole-Christoffer Granmo; Fahim Kawsar; Akhil Mathur (CoRR, 2021)

Adaptive Intelligence for Batteryless Sensors Using Software-Accelerated Tsetlin Machines. - Abu Bakar; Tousif Rahman; Rishad A. Shafik; Fahim Kawsar; Alessandro Montanari (SenSys, 2022)

Logic-based intelligence for batteryless sensors. - Abu Bakar; Tousif Rahman; Alessandro Montanari; Jie Lei; Rishad A. Shafik; Fahim Kawsar (HotMobile, 2022)

Logic-Based Machine Learning with Reproducible Decision Model Using the Tsetlin Machine. - Olga Tarasyuk; Anatoliy Gorbenko; Tousif Rahman; Rishad A. Shafik; Alex Yakovlev (IDAACS, 2023)

IMBUE: In-Memory Boolean-to-CUrrent Inference ArchitecturE for Tsetlin Machines. - Omar Ghazal; Simranjeet Singh; Tousif Rahman; Shengqi Yu; Yujin Zheng; Domenico Balsamo; Sachin B. Patkar; Farhad Merchant; Fei Xia 001; Alex Yakovlev; Rishad A. Shafik (ISLPED, 2023)

Energy-frugal and Interpretable AI Hardware Design using Learning Automata. - Rishad A. Shafik; Tousif Rahman; Adrian Wheeldon; Ole-Christoffer Granmo; Alex Yakovlev (CoRR, 2023)

An FPGA Architecture for Online Learning using the Tsetlin Machine. - Samuel Prescott; Adrian Wheeldon; Rishad A. Shafik; Tousif Rahman; Alex Yakovlev; Ole-Christoffer Granmo (CoRR, 2023)

REDRESS: Generating Compressed Models for Edge Inference Using Tsetlin Machines. - Sidharth Maheshwari; Tousif Rahman; Rishad A. Shafik; Alex Yakovlev; Ashur Rafiev; Lei Jiao 001; Ole-Christoffer Granmo (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

MATADOR: Automated System-on-Chip Tsetlin Machine Design Generation for Edge Applications. - Tousif Rahman; Gang Mao; Sidharth Maheshwari; Rishad A. Shafik; Alex Yakovlev (DATE, 2024)

Runtime Tunable Tsetlin Machines for Edge Inference on eFPGAs. - Tousif Rahman; Gang Mao; Bob Pattison; Sidharth Maheshwari; Marcos L. L. Sartori; Adrian Wheeldon; Rishad A. Shafik; Alex Yakovlev (SAS, 2025)

Dynamic Tsetlin Machine Accelerators for On-Chip Training at the Edge using FPGAs. - Gang Mao; Tousif Rahman; Sidharth Maheshwari; Bob Pattison; Zhuang Shao; Rishad A. Shafik; Alex Yakovlev (CoRR, 2025)