An Optimization Framework for Efficient Vision-Based Autonomous Drone Navigation. - Mozhgan Navardi; Aidin Shiri; Edward Humes; Nicholas R. Waytowich; Tinoosh Mohsenin (AICAS, 2022)

E2EdgeAI: Energy-Efficient Edge Computing for Deployment of Vision-Based DNNs on Autonomous Tiny Drones. - Mozhgan Navardi; Edward Humes; Tinoosh Mohsenin (SEC, 2022)

Squeezed Edge YOLO: Onboard Object Detection on Edge Devices. - Edward Humes; Mozhgan Navardi; Tinoosh Mohsenin (CoRR, 2023)

MetaE2RL: Toward Meta-Reasoning for Energy-Efficient Multigoal Reinforcement Learning With Squeezed-Edge You Only Look Once. - Mozhgan Navardi; Edward Humes; Tejaswini Manjunath; Tinoosh Mohsenin (IEEE Micro, 2023)

Resource-Aware Saliency-Guided Differentiable Pruning for Deep Neural Networks. - Uttej Kallakuri; Edward Humes; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2024)

MetaTinyML: End-to-End Metareasoning Framework for TinyML Platforms. - Mozhgan Navardi; Edward Humes; Tinoosh Mohsenin (IEEE Embed. Syst. Lett., 2024)

RAFT: Robust Augmentation of FeaTures for Image Segmentation. - Edward Humes; Xiaomin Lin; Uttej Kallakuri; Tinoosh Mohsenin (CoRR, 2025)

Enabling On-Device Medical AI Assistants via Input-Driven Saliency Adaptation. - Uttej Kallakurik; Edward Humes; Rithvik Jonna; Xiaomin Lin; Tinoosh Mohsenin (CoRR, 2025)