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                                                     | 
+=================================+=============================+=============================================================+
| Computer Vision at Edge         | National Science Foundation | Create efficient computer vision for edge device s          |
+---------------------------------+-----------------------------+-------------------------------------------------------------+
| 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              |
+---------------------------------+-----------------------------+-------------------------------------------------------------+
| Computer Vision at Edge Devices | National Science Foundation | Create Cyber Infrastructure for Edge Computing              |
+---------------------------------+-----------------------------+-------------------------------------------------------------+
| Low-Power Computer Vision       | Google, Facebook, Xilinx    | Improve efficiency of computer vision on embedded sysems    |
+---------------------------------+-----------------------------+-------------------------------------------------------------+
| Active Vision + Drone           | Facebook                    | Use real-time computer vision to control drones             |
+---------------------------------+-----------------------------+-------------------------------------------------------------+
| Open-Source TensorFlow Garden   | Google                      | Create open-source implementation of computer vision        |
+---------------------------------+-----------------------------+-------------------------------------------------------------+

Research Funding
----------------

National Science Foundation
^^^^^^^^^^^^^^^^^^^^^^^^^^^

- 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

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


Past Graduate Students
----------------------

- Ph.D.

  * 2017 `Anup Mohan <https://www.linkedin.com/in/anupmohan560/>`_,
    Ph.D., Thesis: "`Cloud Resource Management for Big Visual Data
    Analysis from Globally Distributed Network Cameras
    <https://docs.lib.purdue.edu/dissertations/AAI10272571/>`_".

  * 2016 `Ahmed Kaseb <https://www.linkedin.com/in/akaseb/>`_, Ph.D.,
    Thesis: "`A Cost-Effective Cloud-Based System for Analyzing Big
    Real-Time Visual Data From Thousands of Network Cameras
    <https://docs.lib.purdue.edu/dissertations/AAI10247059/>`_".

  * 2012 `Jing (Jackie) Feng
    <https://www.linkedin.com/in/jing-feng-70507225/>`_, Ph.D.,
    Thesis: "`Energy-Efficient Collaborative Data Transmission in
    Wireless Sensor Networks
    <https://docs.lib.purdue.edu/dissertations/AAI3544137/>`_".

  * 2011 `Karthik Kumar
    <https://www.linkedin.com/in/karthikkumar2/>`_, Ph.D.  Thesis:
    "`Application-Based Energy Efficient Mobile and Server Computing
    <https://docs.lib.purdue.edu/dissertations/AAI3481059/>`_",
    Bilsland Dissertation Fellowship.

  * 2010 `Yamini Nimmagadda
    <https://www.linkedin.com/in/yamini-nimmagadda-6677a08/>`_, Ph.D.,
    Thesis: "`Resource-Driven Transmission, Display, and Processing of
    Multimedia in Mobile Devices
    <https://docs.lib.purdue.edu/dissertations/AAI3453276/>`_".

  * 2008 Changjiu Xian, Ph.D., Thesis: "`Collaborative Power
    Management between Operating Systems and Applications
    <https://docs.lib.purdue.edu/dissertations/AAI3330613/>`_".

  * 2008 `Nathaniel (Eddie) Pettis
    <https://www.linkedin.com/in/eddiepettis/>`_, Ph.D., Thesis:
    "`Automatic Configuration and Selection of Power Management
    Policies
    <https://docs.lib.purdue.edu/dissertations/AAI3330558/>`_".
    Bilsland Dissertation Fellowship and a finalist of Chorafas Top
    Doctoral Award.

  * 2007 `Yongguo Mei
    <https://www.linkedin.com/in/yongguo-mei-45613416/>`_, Ph.D.,
    Thesis: "`Energy-Efficient Mobile Robots
    <https://docs.lib.purdue.edu/dissertations/AAI3287287/>`_".

  * 2006 `Le Cai <https://www.linkedin.com/in/le-cai-8119725/>`_,
    Ph.D., Thesis: "`Joint Power Management of Memory and Hard Disks
    <https://docs.lib.purdue.edu/dissertations/AAI3260005/>`_"

- MS
  
  * 2020 `Sara Aghajanzadeh
    <https://www.linkedin.com/in/sara-aghajanzadeh-524317107/>`_,
    M.S., Thesis: "Camera Placement Meeting Restrictions of Computer
    Vision".

  * 2019 `Ryan Dailey <https://www.linkedin.com/in/rmdailey/>`_, M.S.,
    Thesis: "Automated Discovery of Network Cameras in Heterogeneous
    Web Pages".

  * 2019 `Aniesh Chawla <https://www.linkedin.com/in/anieshchawla/>`_,
    M.S., Thesis: "Automated System for Identifying Usable Sensors in
    a Large Scale Sensor Network for Computer Vision Applications".

  * 2018 `Yifan Li <https://www.linkedin.com/in/yifanli8086/>`_, M.S.,
    Thesis: "Study of Pedestrian Jaywalking in Campus Area by
    Analyzing Network Camera Data".

  * 2018 `Fengjian Pan <https://www.linkedin.com/in/fengjian-pan/>`_,
    M.S., Thesis: "Faster CNN-based Object Detection with Adaptive
    Network Selection on Embedded System".

  * 2016 `Youngsol Koh
    <https://www.linkedin.com/in/youngsol-koh-953a96ba/>`_, M.S.,
    Thesis: "Efficient Data Processing from Network Camera and its
    Application".

  * 2015 `Ganesh Prahlad Rao Gingade
    <https://www.linkedin.com/in/ganeshgp/>`_, M.S., Thesis: "`Hybrid
    Power Management for Office Equipment
    <https://docs.lib.purdue.edu/open_access_theses/1178/>`_".

  * 2015 `Wenyi Chen
    <https://www.linkedin.com/in/wenyi-chen-4273ba42/>`_, M.S.,
    Thesis: "Dynamic Resource Allocation for Large-Scale Streaming
    Data".

  * 2008 `Karthik Kumar
    <https://www.linkedin.com/in/karthikkumar2/>`_, M.S., Thesis:
    “`Energy Conservation for Content-Based Image Retrieval on Mobile
    Devices <https://docs.lib.purdue.edu/ecetheses/20/>`_”.

  * 2007 `Douglas Herbert
    <https://www.linkedin.com/in/doug-herbert-11b1957/>`_, M.S.,
    Thesis: “Wireless Sensor Network Debugging Using Invariant
    Insertion”.

  * 2006 `Jeffrey Brateman <https://www.linkedin.com/in/brateman/>`_,
    M.S., Thesis: “Frequency and Speed Setting for Energy Conservation
    in Autonomous Mobile Robots”.