Eric Bohm Department of Computer Science, Thomas M. Siebel Center, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (ebohmuiuc.edu). Mr. Bohm received a B.S. degree in computer science from the State University of New York at Buffalo in 1992. He worked as Director of Software Development for Latpon Corporation from 1992 to 1995, and next as Director of National Software Development from 1995 to 1996. He worked as Enterprise Application Architect at MEDE America from 1996 to 1999 and as an Application Architect at WebMD from 1999 to 2001. Following a career shift toward academia, he joined the Parallel Programming Lab at University of Illinois at Urbana-Champaign in 2003. His current focus as a Research Programmer is on optimizing molecular dynamics codes for tens of thousands of processors.

Abhinav Bhatele Department of Computer Science, Thomas M. Siebel Center, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (bhatele2uiuc.edu). Mr. Bhatele received a B.Tech. degree in computer science and engineering from Indian Institute of Technology, Kanpur, India, in 2005. He is a Ph.D. student at the Parallel Programming Lab at the University of Illinois. His research is centered on topology-aware mapping and load balancing for parallel applications. He is a co-developer of the molecular dynamics applications NAMD and LeanCP, developed at the Parallel Programming Lab.

Laxmikant V. Kalé Department of Computer Science, Thomas M. Siebel Center, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (kaleuiuc.edu). Professor Kalé has been working on various aspects of parallel computing, with a focus on enhancing performance and productivity via adaptive runtime systems. His collaborations involve the widely used biomolecular simulation program NAMD, which won the Gordon Bell Prize at the Supercomputing Conference in 2002. Other collaborative work focuses on computational cosmology, quantum chemistry, rocket simulation, space-time meshes, and other unstructured mesh applications. His group successfully distributes and supports software embodying his research ideas involving Charm++, adaptive MPI, and the ParFUM framework. Professor Kalé received the B.Tech. degree in electronics engineering from Benares Hindu University, Varanasi, India, in 1977, and an M.E. degree in computer science from Indian Institute of Science in Bangalore, India, in 1979. He received a Ph.D. degree in computer science from the State University of New York, Stony Brook, in 1985. He worked as a scientist at the Tata Institute of Fundamental Research from 1979 to 1981. He joined the faculty of the University of Illinois at Urbana-Champaign as an Assistant Professor in 1985, where he is currently employed as a professor.

Mark E. Tuckerman Department of Chemistry and Courant Institute of Mathematical Sciences, New York University, New York, New York 10003 (mark.tuckermannyu.edu). Professor Tuckerman obtained his Ph.D. degree in physics from Columbia University in 1993. From 1993 to 1994, he held an IBM postdoctoral fellowship at the IBM Forschungslaboratorium in Rüschlikon, Switzerland, and from 1995 to 1996, he held an NSF postdoctoral fellowship in advanced scientific computing at the University of Pennsylvania in Philadelphia. He is currently an Associate Professor of Chemistry and Mathematics at New York University. His research interests include reactions in solution, organic reactions on semiconductor surfaces, dynamics of molecular crystals, development of the methodology of molecular dynamics, including novel techniques for enhancing conformational sampling and prediction of free energies in biological systems, and the development of new approaches to electronic structure and ab initio molecular dynamics calculations. In 2005, he received the Wilhelm Friedrich Bessel Research Prize from the Alexander von Humboldt Foundation.

Sameer Kumar IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598 (sameerkus.ibm.com). Dr. Kumar received a B.Tech. degree in computer science from Indian Institute of Technology, Madras, India, in 1999, and M.S. and Ph.D. degrees in computer science from the University of Illinois at Urbana-Champaign. His Ph.D. thesis focused on optimizing communication for massively parallel processing. He is currently a Research Staff Member at the IBM T. J. Watson Research Center and is working on the Blue Gene* Project. His research interests include scaling parallel applications to massively parallel machines and next-generation interconnection network design. He coauthored a paper on scaling the molecular dynamics program NAMD, and it was one of the winners of the Gordon Bell Prize at the 2002 Supercomputing Conference.

John A. Gunnels IBM Research Division, IBM T. J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598 (gunnelsus.ibm.com). Dr. Gunnels received his Ph.D. degree in computer science from the University of Texas at Austin. He joined the Mathematical Sciences Department of the IBM T. J. Watson Research Center in 2001. His research interests include high-performance mathematical routines, parallel algorithms, library construction, compiler construction and verification, and graphics processors. Dr. Gunnels has coauthored several journal papers and conference papers on these topics and has been the recipient of three Outstanding Technical Achievement Awards, two Gordon Bell Prizes, and the Gerstner Award for Client Excellence.

Glenn J. Martyna Physical Sciences Division, IBM T. J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598 (martynaus.ibm.com). Dr. Martyna received his Ph.D. degree in chemical physics from Columbia University and then became an NSF Postdoctoral Fellow in computational science and engineering at the University of Pennsylvania. He was a tenured faculty member at Indiana University, Bloomington, before joining IBM. Dr. Martyna's research has focused on atomistic modeling of chemical, biological, and materials processes. He is well known for developing novel techniques that markedly increase the speed and efficiency of computer simulations, as well as for applying the methods to investigate important phenomena.

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