








1400 Townsend Drive
Houghton, MI 49931
906-487-2209
906-487-2283 (fax)
Email: csdept@mtu.edu
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CS Alum Recognition
June 2009 --
We send congratulations to two of our Computer Science alums.
Dan Wakeman, B.S. in Computer Science 1990, was named to
Computerworld's Premier 100 IT Leaders
list for 2009.
According to Computerworld's website, "Computerworld's annual list of the men and women shaping the IT industry showcases the best talent in the industry." Dan is currently the Chief Information Officer at Educational Testing Service.
Dr. Janet Burge, B.S. in Computer Science 1984, recently received a prestigious NSF Faculty Early Career Development (CAREER)
Award. Janet's proposed research is entitled,
"CAREER: Rationale Capture for High-Assurance Systems".
Janet is currently an Assistant Professor of Computer Science and Systems
Analysis at Miami University of Ohio.
Recent News Bits
MTU Computer Science Students Finish First
Computational Discovery and Innovation: Strategic Faculty Hiring Initiative
BonzAI Brawl 2009
New Research Funding
Exploring Sustainability in Computing Education
Click HERE for a complete list of
recent news bits
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Ph.D. Student Receives Best Paper Award
March 25, 2009 --
Computer Science Doctoral candidate Alicia Thorsen, Assistant
Professor Phil Merkey, and Professor Fredrik Manne from the University of
Bergen, Norway received the Best Paper Award for their paper, "Maximum
Weighted Matching Using the Partitioned Global Address Space Model", at
the High Performance Computing and Simulation Symposium (HPC 2009) March
23-25 in San Diego, California. Alicia presented the paper at the
conference.
The paper described the design and implementation of an algorithm for
the weighted matching graph processing problem. The algorithm was
expressed in the new programming language, UPC. UPC is based on C and
expresses parallel computations using a partitioned global address space.
Languages such as UPC are being developed to make programming the
coming generation of peta-scale supercomputers easier and more reliable.
The UPC implementation developed is much simpler than a similar
implementation using MPI, which is currently the most common way to
express algorithms for parallel systems.
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