Barbara Collura
David Sable
Johannes Langguth
Johannes Langguth is a research scientist at Simula reseach laboratory, Oslo, Norway. He received his PhD in computer science from the University of Bergen, Norway in 2011, and master degrees in computer science and economics from university of Bonn, Germany. After a postdoctoral appointment at ENS Lyon, France, he joined Simula in 2012. His research focuses on the design of discrete algorithms for irregular problems on parallel heterogeneous architectures such as multi-core CPUs and GPUs, and their applications in scientific computing, graph analytics, machine learning, computational social science, and high-performance codes for cardiac electrophysiology.
Bruno Raffin
Bruno Raffin is Director of Research at INRIA Grenoble Rhône-Alpes and leader of the DataMove team. Bruno Raffin has a PhD from the Université d’Orléans on parallel programming language design (1997). After a 2 years postdoc at Iowa State University he refocused his research on high performance interactive computing. He led the development of the FlowVR middleware for large scale data-flow oriented parallel applications, used for virtual reality, telepresence and computational steering. He recently retargeted FlowVR at in-situ analytics for large scale parallel application. He also worked on parallel algorithms and cache-efficient parallel data structures (cache oblivious mesh layouts, parallel adaptive sorting), strategies for task-based programming of multi-CPU and multi-GPU machines. He initiated and steered the multi-camera Grimage platform to develop real-time full-body 3D interactions and 3D telepresence. Today he is refocusing is research activity on high performance computing. He leads the INRIA Integrated Project Lab focused on the convergence between HPC, AI and Big Data. Bruno Raffin accounts for more than 60 international publications, advised 16 PhD students. He was responsible for INRIA of more than 15 national and European grants, was the co-founder of the Icatis startup company (2004-2008), and transferred several codes to other companies. Bruno Raffin has been involved in more than 30 program committees of international conferences. He is the head of the steering committee of the Eurographics Symposium on Parallel Graphics and Visualisation.
Olivier Beaumont
Olivier Beaumont, Ph.D. holds a senior researcher position (Directeur de Recherche) at Inria since October 2008. He defended his PhD thesis in 1999 and his Habilitation in 2004. His main interests are in scheduling, load balancing, HPC and memory optimization and parallelization of training. He served as PC Chair (Algorithm Track) for many HPC conferences (SuperComputing, IPDPS, ICPP, HIPC,...) and he is acting as Associate Editor in Chief of JPDC (Journal of Parallel and Distributed Computing). He is the author of more than 90 papers in international journals and conferences.
Michael Resch
Since 2003, Prof. Michael Resch has been the Director of the High-Performance Computing Center Stuttgart, home of one of the fastest civil computing systems in Europe.He also manages the Institute of High Performance Computing.
Born in Graz, Austria in 1964, Prof. Resch studied technical mathematics at the Technical University in Graz. Work for the Joanneum Research Association in Graz was followed by employment as a technical assistant and department and team head at the Computing Center of the University of Stuttgart and the High-Performance Computing Center Stuttgart until 2001. In 2002, he became assistant professor at the University of Houston, Texas, USA.
Prof. Resch has received numerous awards, including the Award for High Performance Distributed Computing of the National Science Foundation, the HPC Challenge Award, and the Microsoft Early Contributor Award. He has also received honorary doctorates from the Technical University at Donezk, Ukraine and the Russian Academy of Sciences. Prof. Resch is an honorary professor of the Russian Academy of Sciences.
Dirk Van Essendelft
Dr. Van Essendelft is the principle investigator for the integration of AI/ML with scientific simulations within in the Computational Device Engineering Team at the National Energy Technology Laboratory. The focus of Dr. Van Essendelft’s work is building a comprehensive hardware and software ecosystem that maximizes speed, accuracy, and energy efficiency of AI/ML accelerated scientific simulations. Currently, his work centers around building Computational Fluid Dynamics capability within the TensorFlow framework, generating AI/ML based predictors, and ensuring the ecosystem is compatible with the fastest possible accelerators and processors in industry. In this way, Dr. Van Essendelft is developing NETL’s first cognitive-in-the-loop simulation capability in which AI/ML models can be used any point to bring acceleration and/or closures in new ways. Dr. Van Essendelft sits on the Technical Advisory Group for NETL’s new Science-Based Artificial Intelligence/Machine Learning Institute (SAMI) and holds degrees in Energy and Geo-Environmental Engineering, Chemical and Biochemical Engineering, and Chemical Engineering from the Pennsylvania State University, University of California, Irvine, and Calvin College respectively.
Recent publications:
Rocki, K., Van Essendelft, D., Sharapov, I., Schreiber, R., Morrison, M., Kibardin, V., Portnoy, A., Dietiker, J. F., Syamlal, M., and James, M. (2020) Fast stencil-code computation on a wafer-scale processor, In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp pp 1-14, IEEE Press, Atlanta, Georgia.
Dhireesha Kudithipudi
In Fall 2019, I started as a professor with joint appointment in the Department of Electrical and Computer Engineering and Department of Computer Science at the University of Texas- San Antonio.
Before that, I enjoyed 13 years in the Department of Computer Engineering at Rochester Institute of Technology, where I was the founding director of the Center for Human-Aware AI.
My research interests are in neuromorphic computing, brain inspired AI algorithms, novel computing substrates (e.g.: memristors), energy efficient machine intelligence, and AI-Platforms. I offer consulting services to startup firms and other agencies in Neuromorphic AI field.
Shreyansh Daftry
Shreyansh Daftry is a researcher, technologist and consultant in the fields of Artificial Intelligence (AI) and Space Technology. He is interested in pushing the boundaries of technology with innovation in the fields of Computer Vision, Machine Learning and Autonomous Robotics - Drones, Self-Driving (or Flying) Cars, etc. His lifelong ambition is to promote both the exploration of space and improvement of sustainable living on Earth.
Shreyansh received his M.S. degree in AI and Robotics from School of Computer Science, Carnegie Mellon University USA in 2016, and his B.S. degree in Electronics and Communication Engineering in 2013. Currently, he is a Research Scientist at NASA Jet Propulsion Laboratory (JPL) in California, working on AI technologies for robotic exploration of Earth, Mars and beyond!
Are Magnus Bruaset
Are Magnus Bruaset is Director of Research at Simula Research Laboratory. He is also Professor of Scientific Computing at the University of Oslo. Previously, he has been an entrepreneur in the software industry, specialised in software environments for numerical simulations based on partial differential equations. His research is concentrated on software development for large-scale simulations, in particular for applications in geoscience.