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Lin Gu (photo)

Ph.D. in Computer Science,
University of Virginia, 2006

M.S. in Computer Science,
Peking University, 2001

B.S. in Computer Science,
Fudan University, 1996


Academic links

t-kernel

VDB debugging utility

VigilNet

Non-academic


Photography
Bibliophile
Entertainment
Travel
Artistic
Sports

Gourmet
Writing


Contact information:

Tel: 1-434-825-3115
email: l i n g u @ c s . v i r g i n i a . e d u
(Please remove the spaces when using the email address)


I am interested in research and development in various areas in computer science, including operating systems, wireless sensor networks, embedded systems, and programming support for general networked low-power computing devices. I received Ph.D. from University of Virginia in 2006. Before that, I received B.S. from Fudan University and M.S. from Peking University, and worked in Huatek and Microsoft. For detailed information, please see my Curriculum Vitae.


Awards (since college)


Publications

Conference Papers

Journal


Miscellaneous


Research experience

Wireless Sensor Networks

Working with Prof. Stankovic in the Real-Time and Embedded Computing Lab at UVa, I participated in a number of research projects including the NEST project sponsored by DARPA. I worked on OS design for energy-and-cost-efficient platforms, detection and classification in sensor networks, and passive radio-triggered hardware. The goal is to prove the "superiority" and "feasibility" of the technology of networked low-power, low-cost computers. Superiority asks "can numerous low-power, low-cost computers outperform the current technology with high-power, expensive devices?" Feasibility asks "can we realistically construct reliable systems with this technology at a reasonable development and maintenance cost?"

OS design for general low-power systems
Traditional OS services meet enormous difficulty in low-power embedded systems because of the stringent resource constraints. It is a research challenge to design OS services that are portable among a large spectrum of embedded platforms. I am working on a new OS kernel that supports virtual memory, preemptive scheduling, and reliable OS protection without traditional hardware support.

Lightweight detection and classification in wireless sensor networks
While a variety of sensors have been incorporated into a spectrum of wireless sensor network ( WSN) platforms, traditional signal processing algorithms, however, often prove too complex for energy-and-cost-effective WSN nodes. It is a challenge to to design efficient sensing and classification algorithms that achieve reliable sensing performance on energy-and-cost-effective hardware without special powerful nodes in a continuously changing physical environment. We have developed a lightweight detection and classification architecture and successfully used it in VigilNet.

Power Management for Sensor Networks
Novel hardware, architecture and middleware solutions are needed to make wireless sensor network sustain a long period of time. I am working on implementing radio-triggered hardware which greatly enhance the network nodes' wake-up capability and enable efficient power management services.

Networking

Data-link protocols
TDMA based MAC and data-link layer protocols.




ACM

IEEE

CRA

 

 

 

 

TinyOS

Slashdot

 

 

 

 

 

Notes