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 | +---------------------------------+-----------------------------+-------------------------------------------------------------+ | Analyze Drone Video | National Science Foundation | Create video datasets captured by drone | +---------------------------------+-----------------------------+-------------------------------------------------------------+ | 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 | +---------------------------------+-----------------------------+-------------------------------------------------------------+ | Trust of Machine Learning Code | Cisco | Evaluate Trustworthiness of Pre-Trained Neural Networks | +---------------------------------+-----------------------------+-------------------------------------------------------------+ | Efficient Computer Vision | Cisco | Detect and Eliminate Redundant Data on Edge Devices | +---------------------------------+-----------------------------+-------------------------------------------------------------+ | Trusted Machine Learning | Wistron | Execute Machine Learning Software in Trusted Environment | +---------------------------------+-----------------------------+-------------------------------------------------------------+ Research Funding ---------------- National Science Foundation ^^^^^^^^^^^^^^^^^^^^^^^^^^^ - 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, Collaborative:RAPID:Leveraging New Data Sources to Analyze the Risk of COVID-19 in Crowded Locations - 2019, PI, CCRI: Planning: Collaborative Research: Planning to Develop a Low-Power Computer Vision Platform to Enhance Research in Computing Systems - 2017, PI, Summit of Software Infrastructure for Managing and Processing Big Multimedia Data at the Internet Scale - 2015, PI, SI2-SSE: Analyze Visual Data from Worldwide Network Cameras - 2015, PI, I-Corps: Business Analytics for Large Scale Intelligence - 2014, PI, US-Singapore Workshop: Collaborative Research: Understand the World by Analyzing Many Video Streams - 2013, Co-PI, Planning Grant: I/UCRC for Net-Centric Software and Systems Center Research Center - 2010, Co-PI, CI-ADDO-NEW: Collaborative Research: Development of DARwIn Humanoid Robots for Research, Education and Outreach - 2009, Co-PI, CRI: II-NEW: Adaptive Robotic Testbed for Wireless Sensor Networks and Autonomous Systems - 2008, Co-PI, CRI: Planning - A Testbed for Compiler-supported Scalable Error Monitoring and Diagnosis for Reliable and Secure Sensor Networks - 2007, Co-PI, NeTS-NOSS: AIDA: Autonomous Information Dissemination in RAndomly Deployed Sensor Networks - 2007, Co-PI, CPATH EAE: Extending a Bottom-Up Education Model to Support Concurrency from the First Year - 2007, Co-PI, CT-ISG: Compiler-Enabled Adaptive Security Monitoring on Networked Embedded Systems - 2006, PI, CPA: Cross-Layer Energy Management by Architectures, Operating Systems, and Application Programs - 2005, Co-PI, CSR-EHS: Resource-Efficient Monitoring, Diagnosis, and Programming Support for Reliable Networked Embedded Systems - 2004, PI, CAREER: A Unified Approach for Energy Management by Operating Systems - 2003, Co-PI, IIS: Distributed Energy-Efficient Mobile Robots 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