Research Topics and Sponsors
Current Topics
Dr. Lu’s research focuses on improving efficiency of computer systems and analyze large amounts of data from distributed sources.
Topic |
Sponsor |
Summary |
|---|---|---|
Computer Vision at Edge |
National Science Foundation |
Create efficient computer vision for edge device s |
Computer Vision at Edge Devices |
National Science Foundation |
Create Cyber Infrastructure for Edge Computing |
AI Institute: Cybersecurity |
National Science Foundation |
Agent-Based Cyber Threat Intelligence and Operation |
AI for Future Musicians |
National Science Foundation |
AI-Based Software to help music performers |
Trusted Machine Learning |
Wistron |
Execute Machine Learning Software in Trusted Environment |
Research Funding
National Science Foundation
2025, PI, 2504445 “Cyberinfrastructure for Multi-Stream Architectures Applied to Computer Vision: Efficiency via Co-Design of Network Architectures and Framework Operators”
2024, Co-PI, 2343596, “Exploring The Risks and Rewards of Large Language Models in Enabling Energy-Efficient Data Center Software Infrastructure”
2023, Co-PI, 2326198, “Artificial Intelligence Technology for Future Music Performers”
2023, Senior Personnel, “AI Institute for Agent-Based Cyber Threat Intelligence and Operation (ACTION)”
2021, PI, 2120430, “CNS Collaborative Research: CAR:NEW: Research Infrastructure for Real-Time Computer Vision and Decision Making via Mobile Robots”
2021, PI, 2107230, “OAC Core: Advancing Low-Power Computer Vision at the Edge”
2021, PI, 2104709, “CDSE: Collaborative: Cyber Infrastructure to Enable Computer Vision Applications at the Edge Using Automated Contextual Analysis”
2020, PI, 2027524, “Collaborative:RAPID:Leveraging New Data Sources to Analyze the Risk of COVID-19 in Crowded Locations”
2019, PI, 1925713, “CCRI: Planning: Collaborative Research: Planning to Develop a Low-Power Computer Vision Platform to Enhance Research in Computing Systems”
2017, PI, 1747694, “Summit of Software Infrastructure for Managing and Processing Big Multimedia Data at the Internet Scale”
2016, Co-PI, 1702722, “Software Infrastructure for Sustained Innovation (SI2) Principal Investigator Workshop”
2015, PI, 1535108, “SI2-SSE: Analyze Visual Data from Worldwide Network Cameras”
2015, PI, 1530914, “I-Corps: Business Analytics for Large Scale Intelligence”
2014, PI, 1427808, “US-Singapore Workshop: Collaborative Research: Understand the World by Analyzing Many Video Streams”
2013, Co-PI, 1266318, “Planning Grant: I/UCRC for Net-Centric Software and Systems Center Research Center”
2010, Co-PI, 0958487, “CI-ADDO-NEW: Collaborative Research: Development of DARwIn Humanoid Robots for Research, Education and Outreach”
2009, Co-PI, 0855098, “CRI: II-NEW: Adaptive Robotic Testbed for Wireless Sensor Networks and Autonomous Systems”
2008, Co-PI, 0751101, “CRI: Planning - A Testbed for Compiler-supported Scalable Error Monitoring and Diagnosis for Reliable and Secure Sensor Networks”
2007, Co-PI, 0721873, “NeTS-NOSS: AIDA: Autonomous Information Dissemination in RAndomly Deployed Sensor Networks”
2007, Co-PI, 0722212, “CPATH EAE: Extending a Bottom-Up Education Model to Support Concurrency from the First Year”
2007, Co-PI, 0716271, “CT-ISG: Compiler-Enabled Adaptive Security Monitoring on Networked Embedded Systems”
2006, PI, 0541267, “CPA: Cross-Layer Energy Management by Architectures, Operating Systems, and Application Programs”
2005, Co-PI, 0509394, “CSR-EHS: Resource-Efficient Monitoring, Diagnosis, and Programming Support for Reliable Networked Embedded Systems”
2004, PI, 0347466, “CAREER: A Unified Approach for Energy Management by Operating Systems”
2003, Co-PI, 0329061, “IIS: Distributed Energy-Efficient Mobile Robots”
Qualcomm
2024, Qualcomm Faculty Research Award, ``Efficient Computer Vision”
Wistron
2023, PI: Dongyan Xu, Co-PI: Yung-Hsiang Lu, “Execute Machine Learning Software in Trusted Environment”
Cisco
2023, PI: Yung-Hsiang Lu, Co-PI: James Davis, “Efficient Computer Vision for Edge Devices”.
2022, PI: James Davis, Co-PI: Yung-Hsiang Lu, “Trustworthy Re-use of Pre-Trained Neural Networks”.
Sandia National Laboratory
2020, Large Scale Network Simulation for Video Surveillance
Facebook
2019 and 2020, Low-Power Computer Vision Challenge
2017, Computer Vision using Contextual Information
Google
2020, Open-Source TensorFlow Model Garden
2018, Low-Power Computer Vision Challenge
Xilinx
2019, Low-Power Computer Vision Challenge
2020, Low-Power Computer Vision Challenge
HP
2013, Adaptive Power Management for Laser Printers