Research

Dr. Lu’s research focuses on improving efficiency of computer systems and analyze large amounts of data from distributed sources.

Current Topics

Topic	Sponsor	Summary
Low-Power Computer Vision	Google, Facebook, Xilinx	Create efficient computer vision running on embedded sysems
Drone Video	National Science Foundation	Create video datasets captured by drone
Observe Crowd Size in COVID-19	National Science Foundation	Estimate crowd sizes worldwide during COVID-19
Open-Source TensorFlow Garden	Google	Create open-source implementation of computer vision
Image Processing for Solar Sail	NASA	Estiamate the optical force from the shape of solar Sail

Research Funding

National Science Foundation

• 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

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

Current Graduate Students

• Abhinav Goel. Topic: Efficient Computer Vision using Hierarchical Neural Network

• Caleb Tung. Topic: Efficient Computer Vision using Contextual Information

• Xiao Hu. Topic: Efficient Object Tracking on Embedded Systems

• Haobo Wang. Topic: Network Management for Surveillance Video

Past Graduate Students

• Ph.D.

  • 2017 Anup Mohan, Ph.D., Thesis: “Cloud Resource Management for Big Visual Data Analysis from Globally Distributed Network Cameras”.

  • 2016 Ahmed Kaseb, Ph.D., Thesis: “A Cost-Effective Cloud-Based System for Analyzing Big Real-Time Visual Data From Thousands of Network Cameras”.

  • 2012 Jing (Jackie) Feng, Ph.D., Thesis: “Energy-Efficient Collaborative Data Transmission in Wireless Sensor Networks”.

  • 2011 Karthik Kumar, Ph.D. Thesis: “Application-Based Energy Efficient Mobile and Server Computing”, Bilsland Dissertation Fellowship.

  • 2010 Yamini Nimmagadda, Ph.D., Thesis: “Resource-Driven Transmission, Display, and Processing of Multimedia in Mobile Devices”.

  • 2008 Changjiu Xian, Ph.D., Thesis: “Collaborative Power Management between Operating Systems and Applications”.

  • 2008 Nathaniel (Eddie) Pettis, Ph.D., Thesis: “Automatic Configuration and Selection of Power Management Policies”. Bilsland Dissertation Fellowship and a finalist of Chorafas Top Doctoral Award.

  • 2007 Yongguo Mei, Ph.D., Thesis: “Energy-Efficient Mobile Robots”.

  • 2006 Le Cai, Ph.D., Thesis: “Joint Power Management of Memory and Hard Disks”

• MS

  • 2020 Sara Aghajanzadeh, M.S., Thesis: “Camera Placement Meeting Restrictions of Computer Vision”.

  • 2019 Ryan Dailey, M.S., Thesis: “Automated Discovery of Network Cameras in Heterogeneous Web Pages”.

  • 2019 Aniesh Chawla, M.S., Thesis: “Automated System for Identifying Usable Sensors in a Large Scale Sensor Network for Computer Vision Applications”.

  • 2018 Yifan Li, M.S., Thesis: “Study of Pedestrian Jaywalking in Campus Area by Analyzing Network Camera Data”.

  • 2018 Fengjian Pan, M.S., Thesis: “Faster CNN-based Object Detection with Adaptive Network Selection on Embedded System”.

  • 2016 Youngsol Koh, M.S., Thesis: “Efficient Data Processing from Network Camera and its Application”.

  • 2015 Ganesh Prahlad Rao Gingade, M.S., Thesis: “Hybrid Power Management for Office Equipment”.

  • 2015 Wenyi Chen, M.S., Thesis: “Dynamic Resource Allocation for Large-Scale Streaming Data”.

  • 2008 Karthik Kumar, M.S., Thesis: “Energy Conservation for Content-Based Image Retrieval on Mobile Devices”.

  • 2007 Douglas Herbert, M.S., Thesis: “Wireless Sensor Network Debugging Using Invariant Insertion”.

  • 2006 Jeffrey Brateman, M.S., Thesis: “Frequency and Speed Setting for Energy Conservation in Autonomous Mobile Robots”.