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Computational Theory and Practice Cluster

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Primary objective: The School of Natural Sciences and Mathematics of the University of South Florida (USF) proposes to establish a scholarly focus area in Computation Theory and Practice. Researchers and scholars will develop both fundamental algorithms and the theory of fundamental algorithms, in addition to applications for other disciplines and for educational purposes at various levels.








Significant scientific advances depend on computational power and skill. Establish a research “cluster area” in Computation Theory and Practice within the new USF School of Sciences and Mathematics, through hires targeting research faculty with expertise in computing and its applications. These new faculty hires will complement existing expertise in Computer Science and the School of Sciences and Mathematics, and articulate with researchers throughout USF on interdisciplinary projects requiring novel computational support and assistance. Hiring in this core area will allow the Sciences and Mathematics to formalize cross-disciplinary training of graduate students in scientific computing, greatly enhancing our competitiveness, and the competitiveness of our graduates as they seek positions in academia and industry.

Why is this cluster important now? Scientific computation and data mining are pivotal features of 21st century science. As evidenced by the completion of the GENOME project, scientific computation unifies modern science now more than ever before. The definition of “computation” is currently expanding from its traditional meaning to comprise “smart” devices, algorithmic approaches to problem solving and a wide variety of related computational resources. For the next generation of successful natural scientists and mathematicians, mastery of computational methods will not be an option. Rather, advanced understanding of computational methods will be absolutely critical to research success in virtually every area of the natural sciences and mathematics. For example, analyzing information collected by the many sensors used to gather environmental data remains a challenge and predicting impacts of global change will require increased sophistication in computational skills.

Why is this cluster important? As USF has reached international prominence in a variety of scientific disciplines there has been a tremendous increase in the need for analysis and design of new theoretical structures and computational models, from models of materials and drug behaviors to declining fisheries. As increasingly complex problems (from climate to www??? behavior) require increasingly sophisticated computer work, this demand is not for off-the-shelf technology, but also for novel algorithms. USF’s centrality in fields with heavy computational demands depends on continued development of a faculty with expertise in the applications, limits, and capabilities in scientific and other computation. Such centrality is essential for USF to be competitive for federal funding. New faculty members hired in this cluster will meet these challenges through their own research, by providing exceptionally strong support to a wide variety of research proposals, and will train cross-disciplinary cohorts of graduate students in the Sciences and Mathematics in computational methods. Development of the School of Natural Sciences and Mathematics offers a tremendous opportunity to meet these societal need in a coordinated manner.

Why USF? USF already has a tradition of remarkable cross-disciplinary commitment to high-end computational science, in areas as diverse as biological information processing, computational physics and chemistry, computational fluid dynamics of pharmaceuticals processing, stochastic modeling of natural disasters, and theory and heuristics of fundamental algorithms. These research interests have resulted in the development of core facilities including a computer cluster, CIRCE, that is among the world’s 500 fastest computers. Such centrality and depth of facilities should be used to attract very high caliber faculty to USF. Similarly, our goal is to enhance USF’s reputation in these fields in order to attract the highest caliber doctoral students and train them for success in the future work force.

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NameDepartmentPublicationsFunded
Connor, CharlesGeology One NSF Award NSF Award
Elhamdadi, MohamedMath/Stat
Fox, GordonIB NSF
Garey, JamesCMMB
Jonoska, NatašaMath/Stat One TwoNSF Award
Khavinson, DmitryMath/Stat NSF Award
Killinger, DennisPhysics
Kim, WonkukMath/Stat
Kruse, SarahGeology
Ladde, GangaramMath/Stat
Lee, Seung-YeopMath/Stat
Ma, Wen-XiuMath/Stat One
McColm, GregoryMath/Stat
McCoy, EarlIB
McWaters, MarcusMath/Stat
Nolas, GeorgePhysics NSF Award
Oleynik, IvanPhysics
Pandit, SagarPhysics
Passaglia, ChristopherChemical and Biomedical Engineering One Two
Rabson, DavidPhysics
Rains, MarkGeology
Ramachandran, KandethodyMath/Stat
Rogers, DavidChemistry
Rohr, JasonIB
Saito, MasahikoMath/Stat
Space, BrianChemistry
Stewart, MarkGeology
Tsokos, ChristosMath/Stat
Ullah, GhanimPhysics
Woods, LiliaPhysics NSF Award
You, YunchengMath/Stat