Dependability evaluation of SISO control-theoretic power managers for processor architectures. - Sina Shahhosseini; Kasra Moazzemi; Amir M. Rahmani; Nikil D. Dutt (NORCAS, 2017)

On the feasibility of SISO control-theoretic DVFS for power capping in CMPs. - Sina Shahhosseini; Kasra Moazzemi; Amir M. Rahmani; Nikil D. Dutt (Microprocess. Microsystems, 2018)

An Edge-Assisted and Smart System for Real-Time Pain Monitoring. - Emad Kasaeyan Naeini; Sina Shahhosseini; Ajan Subramanian; Tingjue Yin; Amir M. Rahmani; Nikil D. Dutt (CHASE, 2019)

Dynamic Computation Migration at the Edge: Is There an Optimal Choice? - Sina Shahhosseini; Iman Azimi; Arman Anzanpour; Axel Jantsch; Pasi Liljeberg; Nikil D. Dutt; Amir M. Rahmani (ACM Great Lakes Symposium on VLSI, 2019)

Partition Pruning: Parallelization-Aware Pruning for Deep Neural Networks. - Sina Shahhosseini; Ahmad Albaqsami; Masoomeh Jasemi; Shaahin Hessabi; Nader Bagherzadeh (CoRR, 2019)

Exploring Energy Efficient Quantum-resistant Signal Processing Using Array Processors. - Hamid Nejatollahi; Sina Shahhosseini; Rosario Cammarota; Nikil D. Dutt (IACR Cryptol. ePrint Arch., 2019)

Dynamic iFogSim: A Framework for Full-Stack Simulation of Dynamic Resource Management in IoT Systems. - Dongjoo Seo; Sina Shahhosseini; Milad Asgari Mehrabadi; Bryan Donyanavard; Sung-Soo Lim; Amir M. Rahmani; Nikil D. Dutt (COINS, 2020)

Partition Pruning: Parallelization-Aware Pruning for Dense Neural Networks. - Sina Shahhosseini; Ahmad Albaqsami; Masoomeh Jasemi; Nader Bagherzadeh (PDP, 2020)

Towards Smart and Efficient Health Monitoring Using Edge-enabled Situational-awareness. - Sina Shahhosseini; Anil Kanduri; Milad Asgari Mehrabadi; Emad Kasaeyan Naeini; Dongjoo Seo; Sung-Soo Lim; Amir M. Rahmani; Nikil D. Dutt (AICAS, 2021)

AMSER: Adaptive Multi-modal Sensing for Energy Efficient and Resilient eHealth Systems. - Emad Kasaeyan Naeini; Sina Shahhosseini; Anil Kanduri; Pasi Liljeberg; Amir M. Rahmani; Nikil D. Dutt (CoRR, 2021)

Exploring Energy Efficient Architectures for RLWE Lattice-Based Cryptography. - Hamid Nejatollahi; Sina Shahhosseini; Rosario Cammarota; Nikil D. Dutt (J. Signal Process. Syst., 2021)

AMSER: Adaptive Multimodal Sensing for Energy Efficient and Resilient eHealth Systems. - Emad Kasaeyan Naeini; Sina Shahhosseini; Anil Kanduri; Pasi Liljeberg; Amir M. Rahmani; Nikil D. Dutt (DATE, 2022)

Flexible and Personalized Learning for Wearable Health Applications using HyperDimensional Computing. - Sina Shahhosseini; Yang Ni 001; Emad Kasaeyan Naeini; Mohsen Imani; Amir M. Rahmani; Nikil D. Dutt (ACM Great Lakes Symposium on VLSI, 2022)

Hyperdimensional Hybrid Learning on End-Edge-Cloud Networks. - Mariam Issa; Sina Shahhosseini; Yang Ni 001; Tianyi Hu; Danny Abraham; Amir M. Rahmani; Nikil D. Dutt; Mohsen Imani (ICCD, 2022)

Hybrid Learning for Orchestrating Deep Learning Inference in Multi-user Edge-cloud Networks. - Sina Shahhosseini; Tianyi Hu; Dongjoo Seo; Anil Kanduri; Bryan Donyanavard; Amir M. Rahmani; Nikil D. Dutt (ISQED, 2022)

Efficient Personalized Learning for Wearable Health Applications using HyperDimensional Computing. - Sina Shahhosseini; Yang Ni 001; Hamidreza Alikhani; Emad Kasaeyan Naeini; Mohsen Imani; Nikil D. Dutt; Amir M. Rahmani (CoRR, 2022)

Edge-centric Optimization of Multi-modal ML-driven eHealth Applications. - Anil Kanduri; Sina Shahhosseini; Emad Kasaeyan Naeini; Hamidreza Alikhani; Pasi Liljeberg; Nikil D. Dutt; Amir M. Rahmani (CoRR, 2022)

Exploring computation offloading in IoT systems. - Sina Shahhosseini; Arman Anzanpour; Iman Azimi; Sina Labbaf; Dongjoo Seo; Sung-Soo Lim; Pasi Liljeberg; Nikil D. Dutt; Amir M. Rahmani (Inf. Syst., 2022)

Online Learning for Orchestration of Inference in Multi-user End-edge-cloud Networks. - Sina Shahhosseini; Dongjoo Seo; Anil Kanduri; Tianyi Hu; Sung-Soo Lim; Bryan Donyanavard; Amir M. Rahmani; Nikil D. Dutt (ACM Trans. Embed. Comput. Syst., 2022)

Online Learning for Orchestrating Deep Learning Inference at Edge - Sina Shahhosseini (2023)

ISCA: Intelligent Sense-Compute Adaptive Co-Optimization of Multimodal Machine Learning Kernels for Resilient mHealth Services on Wearables. - Hamidreza Alikhani; Anil Kanduri; Emad Kasaeyan Naeini; Sina Shahhosseini; Pasi Liljeberg; Amir M. Rahmani; Nikil D. Dutt (IEEE Des. Test, 2025)