Irrelevant Pixels are Everywhere: Find and Exclude Them for More Efficient Computer Vision. - Caleb Tung; Abhinav Goel; Xiao Hu 004; Nick Eliopoulos; Emmanuel S. Amobi; George K. Thiruvathukal; Vipin Chaudhary; Yung-Hsiang Lu (AICAS, 2022)

Directed Acyclic Graph-based Neural Networks for Tunable Low-Power Computer Vision. - Abhinav Goel; Caleb Tung; Nick Eliopoulos; Xiao Hu 004; George K. Thiruvathukal; James C. Davis 001; Yung-Hsiang Lu (ISLPED, 2022)

Why Accuracy is Not Enough: The Need for Consistency in Object Detection. - Caleb Tung; Abhinav Goel; Fischer Bordwell; Nick Eliopoulos; Xiao Hu 004; Yung-Hsiang Lu; George K. Thiruvathukal (IEEE Multim., 2022)

Lightning Talk 6: Bringing Together Foundation Models and Edge Devices. - Nick Eliopoulos; Yung-Hsiang Lu (DAC, 2023)

An automated approach for improving the inference latency and energy efficiency of pretrained CNNs by removing irrelevant pixels with focused convolutions. - Caleb Tung; Nicholas Eliopoulos; Purvish Jajal; Gowri Ramshankar; Chen-Yung Yang; Nicholas Synovic; Xuecen Zhang; Vipin Chaudhary; George K. Thiruvathukal; Yung-Hsiang Lu (CoRR, 2023)

Tree-Based Unidirectional Neural Networks for Low-Power Computer Vision. - Abhinav Goel; Caleb Tung; Nick Eliopoulos; George K. Thiruvathukal; Amy Wang; Yung-Hsiang Lu; James C. Davis 001 (IEEE Des. Test, 2023)

An automated approach for improving the inference latency and energy efficiency of pretrained CNNs by removing irrelevant pixels with focused convolutions. - Caleb Tung; Nicholas Eliopoulos; Purvish Jajal; Gowri Ramshankar; Cheng-Yun Yang; Nicholas Synovic; Xuecen Zhang; Vipin Chaudhary; George K. Thiruvathukal; Yung-Hsiang Lu (ASPDAC, 2024)

Securing Deep Neural Networks on Edge from Membership Inference Attacks Using Trusted Execution Environments. - Cheng-Yun Yang; Gowri Ramshankar; Nicholas Eliopoulos; Purvish Jajal; Sudarshan Nambiar; Evan Miller; Xun Zhang; Dave (Jing) Tian; Shuo-Han Chen; Chiy-Ferng Perng; Yung-Hsiang Lu (ISLPED, 2024)

Large Language Models for Energy-Efficient Code: Emerging Results and Future Directions. - Huiyun Peng; Arjun Gupte; Nicholas John Eliopoulos; Chien Chou Ho; Rishi Mantri; Leo Deng; Wenxin Jiang 001; Yung-Hsiang Lu; Konstantin Läufer; George K. Thiruvathukal; James C. Davis 001 (CoRR, 2024)

nickjeliopoulos/PruneOneMoreToken. - Nick John Eliopoulos; George K. Thiruvathukal (Zenodo, 2024)

Detecting Music Performance Errors with Transformers. - Benjamin Shiue-Hal Chou; Purvish Jajal; Nicholas John Eliopoulos; Tim Nadolsky; Cheng-Yun Yang; Nikita Ravi; James C. Davis 001; Kristen Yeon-Ji Yun; Yung-Hsiang Lu (AAAI, 2025)

Pruning One More Token is Enough: Leveraging Latency-Workload Non-Linearities for Vision Transformers on the Edge. - Nicholas John Eliopoulos; Purvish Jajal; James C. Davis 001; Gaowen Liu; George K. Thiravathukal; Yung-Hsiang Lu (WACV, 2025)

Token Turing Machines are Efficient Vision Models. - Purvish Jajal; Nick John Eliopoulos; Benjamin Shiue-Hal Chou; George K. Thiravathukal; James C. Davis 001; Yung-Hsiang Lu (WACV, 2025)

Inference-Time Alignment of Diffusion Models with Evolutionary Algorithms. - Purvish Jajal; Nick John Eliopoulos; Benjamin Shiue-Hal Chou; George K. Thiruvathukal; James C. Davis 001; Yung-Hsiang Lu (CoRR, 2025)

SysLLMatic: Large Language Models are Software System Optimizers. - Huiyun Peng; Arjun Gupte; Ryan Hasler; Nicholas John Eliopoulos; Chien Chou Ho; Rishi Mantri; Leo Deng; Konstantin Läufer; George K. Thiruvathukal; James C. Davis 001 (CoRR, 2025)