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Professor James C Browne
Jim Browne earned his Ph.D. in Chemical Physics at The University of Texas in 1960 and taught in the Physics Department at The University of Texas from 1960 through 1964. Between 1965 and 1968 he was Professor of Computer Science at Queens University in Belfast and Director of the Computer Laboratory. During this period he was a frequent visitor to the Atlas Laboratory getting a large quantum chemistry package working on Atlas. He inhabited one of the cells on the bottom corridor complaining about the cold. He got to know the systems programmers well and, later, one of his students from the University of Texas, Wade Shaw, came to work at the Laboratory.
He rejoined The University of Texas in 1968 as Professor of Physics and Computer Science. Parallel programming and high level specification languages for software development became his major research interests. His early research career in computational physics gave the impetus to his interest in large scale computational problems. He served as Department Chair for Computer Science in 1968-69, 1971-75 and 1984-87. He has attained Fellow status in five different professional societies and areas: the Association for Computing Machinery, the British Computer Society, the American Physical Society, the American Association for the Advancement of Science and the Institute for Constructive Capitalism.
Browne received the 2004 University of Texas at Austin Career Research Excellence Award for maintaining a superior research program in such fields as parallel computation, performance measurement and analysis, operating systems, and software engineering for a long time span. Browne has also been active in technology transfer and the technology industry. He founded Hyperformix, an Austin, Texas based software company which sells products and services for performance management and engineering for enterprise level computer systems. Hyperformix was acquired by Computer Associates in October, 2010. His current research interests span parallel programming and computation, performance optimization, software engineering, formal methods and fault/failure management for complex systems.