University of Texas at Austin
Andreas Gerstlauer

Contact

websitehttp://www.ece.utexas.edu/~gerstl

email

phone (512) 232-8294

office EER 5.882

Andreas Gerstlauer

Affiliated Faculty

Professor Electrical & Computer Engineering

Research Interests

High-Performance Computing Computer Architecture

Biography

Andreas Gerstlauer is a Professor of Electrical and Computer Engineering (ECE) at The University of Texas at Austin. He received a Ph.D. degree in Information and Computer Science (ICS) from the University of California, Irvine (UCI) in 2004. Prior to joining UT Austin in 2008, he was an Assistant Researcher in the Center for Embedded Computer Systems (CECS) at UC Irvine. Dr. Gerstlauer is co-author on 3 books and more than 130 conference and journal publications. His work was recognized with the Best Research Paper Awards at at the 2016 Design Automation Conference (DAC), the Best Paper Award at the 2015 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS), several best paper nominations from DAC, DATE and HOST conferences among others, and as one of the most influential contributions in 10 years at DATE in 2008. He is the recipient of a 2016-2017 Humboldt Research Fellowship. He serves or has served as an Associate and Guest Editor for the ACM Transactions on Embedded Computer Systems (TECS) and ACM Transactions on Design Automation of Electronic Systems (TODAES) journals as well as General or Program Chair for major international conferences such as ESWEEK, MEMOCODE, CODES+ISSS and SAMOS.

Dr. Gerstlauer's research interests are generally in the area of system-level design of resource-constrained, energy-efficient/low-power and application- or domain-specific embedded, high-performance and edge computing systems. Research in his lab spans from novel hardware/software compute fabrics, System-on-Chip (SoC) architectures and algorithm/architecture co-design of accelerator-rich, heterogeneous computer systems to system-level design automation methods and tools, with a special emphasis on underlying system modeling foundations.

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