Professor Meleis's research is on developing and evaluating algorithms and
bounds for combinatorially difficult optimization problems. He has made contributions to
the following areas: 

- Optimal scheduling and register allocation, with spill code, for multiple-issue
processors - Microprocessor-aware scheduling algorithms for modern compilers - Algorithms
for weighted-completion time scheduling - Design and analysis of tight lower bounds on
schedule length - Backtracking acyclic schedulers - Parallel and scalable processing
systems and programming toolsets. - Computational infrastructure for seamless, inter-site
Grid computing - Applications of combinatorial optimization to switching, testing, and
reconfigurable computing - Multiagent machine learning for distributed combinatorial
optimization

Workflow

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Design of workflow scheduler (with Juemin Zhang and David Kaeli), Research Thrust R3 Presentations (2007)

This work falls under Research thrust R3, image and data information management. This work can...