Christoph Kessler Email and Phone Number

Christoph W. Kessler (german spelling: Keßler) is a professor for Computer Science at Linköping University, Sweden, where he leads the Programming Environment Laboratory's research group on compiler technology and parallel computing.Christoph Kessler received a PhD degree in Computer Science in 1994 from the University of Saarbrücken, Germany, and a Habilitation degree in 2001 from the University of Trier, Germany.In 2001 he joined Linköping university, Sweden, as associate professor at the programming environments lab (PELAB) of the computer science department (IDA).In 2007 he was appointed full professor at Linköping university.His research interests include parallel programming, compiler technology, code generation, program optimization, system modeling, and software composition.He has published two books, several book chapters and more than 130 scientific papers in international peer-reviewed journals and conferences, and several open-source software systems. His contributions include e.g. algorithms for scheduling of tasks and instructions for time-, space- and energy-optimal execution on parallel and heterogeneous target architectures, the OPTIMIST retargetable optimizing integrated code generator for VLIW and DSP processors, the PARAMAT approach to pattern-based automatic parallelization of sequential code, the concept of performance-aware parallel components for optimized software composition for parallel systems, the PEPPHER component model and software composition tool for heterogeneous multicore/manycore based systems, the C++ based single-source multi-backend programming framework SkePU with high-level programming abstractions based on algorithmic patterns/skeletons for portable autotunable execution on heterogeneous parallel systems and clusters, and the parallel programming languages Fork and NestStep.List of publications: http://www.ida.liu.se/~chrke55/publ.htmlChristoph Kessler teaches courses at undergraduate, master and PhD level at Linköping University in the areas of parallel and distributed computing, multicore and GPU computing, operating systems, compiler construction and software composition, as well as the Scientific Methods course preparing students in computer science and engineering for their master thesis project.