Stephane Chevobbe
Albert Wang
Chritos Kolias
Marc Julien
Magnus Gerward
Bronis de Supinski
Bronis R. de Supinski is the Chief Technology Officer (CTO) for Livermore Computing (LC) at Lawrence Livermore National Laboratory (LLNL). In this role, he is responsible for formulating LLNL's large-scale computing strategy and overseeing its implementation. His position requires frequent interaction with high performance computing (HPC) leaders and he oversees several collaborations with the HPC industry as well as academia. He is also the LLNL principal point of contact for the Scientific Discovery through Advanced Computing (SciDAC) program's Institute for Sustained Performance, Energy and Resilience (SUPER), for which he leads the resilience thrust.
Prior to becoming CTO for LC, Bronis led several research projects in LLNL's Center for Applied Scientific Computing (CASC). Most recently, he led the Exascale Computing Technologies (ExaCT) project and co-led the Advanced Simulation and Computing (ASC) program's Application Development Environment and Performance Team (ADEPT). ADEPT is responsible for the development environment, including compilers, tools and run time systems, on LLNL's large-scale systems. ExaCT explored several critical directions related to programming models, algorithms, performance, code correctness and resilience for future large scale systems. He currently continues his interests in these topics, particularly programming models, and serves as the Chair of the OpenMP Language Committee.
Bronis earned his Ph.D. in Computer Science from the University of Virginia in 1998, and he joined CASC in July 1998. His dissertation investigated shared memory coherence based on isotach logical time systems. His research has covered a wide range of topics, including applications of data mining techniques to performance analysis and modeling including performance modeling through non-linear regression techniques (i.e., artificial neural networks and piecewise polynomial regression), investigations into mechanisms and tools to improve memory performance, a variety of optimization techniques and tools for MPI, and several issues with OpenMP, including its memory model and tool support.
Throughout his career, Bronis has won several awards, including the prestigious Gordon Bell Prize in 2005 and 2006, as well as an R&D 100 for his leadership of a team that developed a novel scalable debugging tool. He serves on the program committees of numerous conferences and workshops. He is a member of the ACM and the IEEE Computer Society.
Kim Branson
Dr Kim Branson, is SVP and Global Head, AI/ML at GSK, based in San Francisco. Kim oversees a global team of more than 50 engineers and machine learning researchers. The GSK AI/ML team is focused on the application and development of AI methodology at the intersection of functional genomics and human genetics for target discovery, causal machine learning and clinical applications. Kim joined GSK in 2019 from Genentech where he was Head of AI, Early Clinical Development. Kim received his PhD in Computational Drug Design from University of Melbourne.
Kim has been involved in large-scale machine learning and medical informatics initiatives for more than 15 years, over a range of ventures from computational drug design to disease risk prediction. Kim received degrees from the University of Adelaide, and a PhD from the University of Melbourne (Australia). He was a Peter Doherty fellow and received postdoctoral training at Stanford University. He then held leadership and consulting roles in the pharmaceutical and medical informatics industry, notably at Vertex Pharmaceuticals.
Following this, Kim worked extensively in online search as a founding member of Discovery Engine (acquired by Twitter in 2009) and in health informatics as the Founding Chief Scientist of Gliimpse (acquired by Apple in 2017), and the Founding Chief Data Scientist at Lumiata, a predictive health analytics company.
Alex Karargyris
Dehao Chen
Galina Grunin
I am a hands-on IT practitioner with expert knowledge and experience in deep learning, orchestration and pattern deployment, cloud computing architecture, software-defined storage, software-defined networking, adapting legacy systems for the cloud, web technologies, and application and middleware integration. My achievements in the above fields are recognized by over 40 U.S. patents in which I am a named inventor.
Prior to joining Optum, I was the lead architect/technical lead for various projects at IBM Cloud and IoT divisions. In those roles, I developed a cloud strategy and a reference architecture for cloud-based solutions; evaluated, enabled and optimized key third-party software and technology for potential partnership or acquisition; developed cognitive workloads for the new IoT edge platform; and assisted prospective and actual clients in evaluating and addressing cloud and IoT-related infrastructure, solutions and technologies.