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Newsletter of the Department of Electrical Engineering

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Faculty News

Yang, Zaki Receive Celebrating Teachers Award

Professors Chia-Hung Yang and Kawthar Zaki were both recipients of the Celebrating Teachers Award.

This award is an initiative of the Center for Teaching Excellence, in collaboration with the Office of the Dean for Undergraduate Studies and the Office of School-University Cooperative Programs. The award seeks to recognize the most influential teaching faculty both on and off campus. Recipients of the Celebrating Teachers Awards were nominated by outstanding graduating seniors.

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Pictured: Prof. Jeffrey Hollingsworth
New Affiliate Faculty Strengthen Computer Engineering Program

Prof. Jeffrey K. Hollingsworth, from the Department of Computer Science, was appointed affiliate assistant professor of the Department of Electrical Engineering. Hollingsworth, who joined Maryland in 1994, earned his Ph.D. degree in Computer Science from the University of Wisconsin-Madison.

Hollingsworth’s research has focused primarily on environments for parallel programming, including performance monitoring and debugging, operating systems, computer networks, and distributed systems. Two of his recent papers include “Benchmarking a Network of PCs Running Parallel Applications,” and “LBF: A Performance Metric for Program Reorganization.” His software distributions include “dyninstAPI,” a library for runtime instrumentation of programs, and “Grindstone,” a set of PVM programs designed to test parallel tools.

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Pictured: Prof. Peter Keleher
Prof. Peter J. Keleher, from the Department of Computer Science, was appointed affiliate assistant professor of the Department of Electrical Engineering. Keleher, who joined Maryland in 1994, earned his Ph.D. degree in Computer Science from Rice.

Keleher's research interests lie primarily in the field of distributed computing. The two primary thrusts of his current work are in distributed shared memory (DSM) and in global resource management in large-scale systems. His DSM work is aimed at finding the limits to high performance of software DSMs, including communication analysis, assessing the impact of protocol choices, and identifying environmental conditions and application domains for which software DSM makes sense.