Energy-Efficient Hardware for Language Guided Reinforcement Learning. - Aidin Shiri; Arnab Neelim Mazumder; Bharat Prakash; Nitheesh Kumar Manjunath; Houman Homayoun; Avesta Sasan; Nicholas R. Waytowich; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2020)

An Energy-Efficient Low Power LSTM Processor for Human Activity Monitoring. - Arnab Neelim Mazumder; Hasib-Al Rashid; Tinoosh Mohsenin (SoCC, 2020)

End-to-end Scalable and Low Power Multi-modal CNN for Respiratory-related Symptoms Detection. - Haoran Ren; Arnab Neelim Mazumder; Hasib-Al Rashid; Vandana Chandrareddy; Aidin Shiri; Nitheesh Kumar Manjunath; Tinoosh Mohsenin (SoCC, 2020)

Neural Networks for Pulmonary Disease Diagnosis using Auditory and Demographic Information. - Morteza Hosseini; Haoran Ren; Hasib-Al Rashid; Arnab Neelim Mazumder; Bharat Prakash; Tinoosh Mohsenin (CoRR, 2020)

CoughNet: A Flexible Low Power CNN-LSTM Processor for Cough Sound Detection. - Hasib-Al Rashid; Arnab Neelim Mazumder; Utteja Panchakshara Kallakuri Niyogi; Tinoosh Mohsenin (AICAS, 2021)

An Energy-Efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. - Aidin Shiri; Bharat Prakash; Arnab Neelim Mazumder; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (AICAS, 2021)

2021 Roadmap on Neuromorphic Computing and Engineering. - Dennis V. Christensen; Regina Dittmann; Bernabé Linares-Barranco; Abu Sebastian; Manuel Le Gallo; Andrea Redaelli; Stefan Slesazeck; Thomas Mikolajick; Sabina Spiga; Stephan Menzel; Ilia Valov; Gianluca Milano; et al. (CoRR, 2021)

A Survey on the Optimization of Neural Network Accelerators for Micro-AI On-Device Inference. - Arnab Neelim Mazumder; Jian Meng; Hasib-Al Rashid; Utteja Kallakuri; Xin Zhang 025; Jae-Sun Seo; Tinoosh Mohsenin (IEEE J. Emerg. Sel. Topics Circuits Syst., 2021)

Cyclic Sparsely Connected Architectures for Compact Deep Convolutional Neural Networks. - Morteza Hosseini; Nitheesh Kumar Manjunath; Bharat Prakash; Arnab Neelim Mazumder; Vandana Chandrareddy; Houman Homayoun; Tinoosh Mohsenin (IEEE Trans. Very Large Scale Integr. Syst., 2021)

A Fast Network Exploration Strategy to Profile Low Energy Consumption for Keyword Spotting. - Arnab Neelim Mazumder; Tinoosh Mohsenin (CoRR, 2022)

XAI-Increment: A Novel Approach Leveraging LIME Explanations for Improved Incremental Learning. - Arnab Neelim Mazumder; Niall Lyons; Anand Dubey; Ashutosh Pandey; Avik Santra (CoRR, 2022)

Automatic Detection of Respiratory Symptoms Using a Low-Power Multi-Input CNN Processor. - Arnab Neelim Mazumder; Haoran Ren; Hasib-Al Rashid; Morteza Hosseini; Vandana Chandrareddy; Houman Homayoun; Tinoosh Mohsenin (IEEE Des. Test, 2022)

A Hardware Accelerator for Language-Guided Reinforcement Learning. - Aidin Shiri; Arnab Neelim Mazumder; Bharat Prakash; Houman Homayoun; Nicholas R. Waytowich; Tinoosh Mohsenin (IEEE Des. Test, 2022)

2022 roadmap on neuromorphic computing and engineering. - Dennis V. Christensen; Regina Dittmann; Bernabé Linares-Barranco; Abu Sebastian; Manuel Le Gallo; Andrea Redaelli; Stefan Slesazeck; Thomas Mikolajick; Sabina Spiga; Stephan Menzel; Ilia Valov; Gianluca Milano; et al. (Neuromorph. Comput. Eng., 2022)

Harnessing the Power of Explanations for Incremental Training: A LIME-Based Approach. - Arnab Neelim Mazumder; Niall Lyons; Ashutosh Pandey; Avik Santra; Tinoosh Mohsenin (EUSIPCO, 2023)

Reg-TuneV2: A Hardware-Aware and Multiobjective Regression-Based Fine-Tuning Approach for Deep Neural Networks on Embedded Platforms. - Arnab Neelim Mazumder; Tinoosh Mohsenin (IEEE Micro, 2023)

Reg-Tune: A Regression-Focused Fine-Tuning Approach for Profiling Low Energy Consumption and Latency. - Arnab Neelim Mazumder; Farshad Safavi; Maryam Rahnemoonfar; Tinoosh Mohsenin (ACM Trans. Embed. Comput. Syst., 2024)

ViT-Reg: Regression-Focused Hardware-Aware Fine-Tuning for ViT on TinyML Platforms. - Md Ragib Shaharear; Arnab Neelim Mazumder; Tinoosh Mohsenin (IEEE Des. Test, 2025)