Marc Casas is a senior researcher at the Barcelona Supercomputing Center (BSC). He received a 5-years degree in mathematics in 2004 from the Technical University of Catalonia (UPC) and a PhD degree in Computer Science in 2010 from the Computer Architecture Department of UPC.
He was a postdoctoral research scholar at the Lawrence Livermore National Laboratory (LLNL) from 2010 to 2013 working on algorithmic-based fault tolerance and active measurement methods based on software interference. He received the best paper award at the Euro-Par conference in 2007 and was nominated to the best paper award at the SC conference in 2015. He received the Marie Curie and Ramón y Cajal Fellowships on 2014 and 2017, respectively. His current research interests are high performance computing architectures, runtime systems and parallel algorithms. He is currently involved with the Mont-Blanc2020 project and leads research collaborations with major companies like Intel and IBM.
AI/Machine Learning/Deep Learning
Performance Analysis and Optimization