Samuel D. Conte Professor of Computer Science
B.E., Computer Science and Technology, University of Roorkee (India); M.S., Computer Engineering, Wayne State University; Ph.D., Computer Science, University of Minnesota
Parallel and Distributed Computing Architectures, Algorithms, and Applications, Particle Dynamics Methods and Dense Linear System Solvers, Fast Algorithms for Data Compression and Analysis
Assurable Software and Architecture
Work focuses on distributed infrastructure deals with development of software support for dynamic clustered and multi-clustered environments. More recent work has been done on resource location and allocation mechanisms in peer-to-peer networks.
Amazon Research Award, 2021.
Distinguished Research Award, Purdue University School of Science, 2017.
Distinguished Alumnus Award, Department of Computer Science, University of Minnesota, 2015.
Fellow, American Association for Advancement of Sciences (AAAS), 2013.
Purdue University Most In¯uential Professor in Computer Science, 2010.
Purdue University Scholar, 2002.
Purdue University School of Science Outstanding Teacher Award, 2002.
National Science Foundation CAREER Award, 1998±2002.
Purdue University School of Science Outstanding Assistant Professor, 1999.
Doctoral Dissertation Fellowship, Graduate School of the University of Minnesota, 1995-96.
Doctoral Dissertation Award, Department of Computer Science, University of Minnesota, 1994.
Vice-Chancellors Gold Medal for best overall grades among all engineering majors at the Indian Institute of Technology, Roorkee, India, 1989.
Vice-Chancellors Gold Medal for best engineering design project titled ªLoad Balancing in LANsº, Indian Institute of Technology, Roorkee, India, 1989.
AAAS, Sigma Xi.
Compression of Particle Data for Hierarchical Approximation Techniques (with D.-Y. Yang, N. Ramakrishnan, and V. Sarin), ACM Transactions on Mathematical Software, Vol. 27, No. 3 (2001). 2D-Pattern Matching Image and Video Compression: Theory, Algorithms, and Experiments, IEEE Transactions on Image Processing (December 2001). Co-authored a textbook "Introduction to Parallel Computing: Design and Analysis of Algorithms" (2003)
Professor Grama's research interests span the areas of parallel and distributed computing architectures, algorithms, and applications. His work on distributed infrastructure deals with development of software support for dynamic clustered and multiclustered environments. More recent work has focused on resource location and allocation mechanisms in peer-to-peer networks. His research on applications has focused on particle dynamics methods, their applications to dense linear system solvers, fast algorithms for data compression and analysis. Professor Grama has authored several papers and co-authored a text book "Introduction to Parallel Computing: Design and Analysis of Algorithms" with Vipin Kumar, Anshul Gupta, and George Karypis. He is a member of American Association for Advancement of Sciences and Sigma Xi.