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.
