- Opportunities for improving efficiency of clinical research and development
- Combining information technology, statistics, and data science to address challenging problems in drug development
- Integrated scientific learning approach
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Kunle Olukotun is the Cadence Design Professor of Electrical Engineering and Computer Science at Stanford University. Olukotun is a renowned pioneer in multi-core processor design and the leader of the Stanford Hydra chip multiprocessor (CMP) research project.
Prior to SambaNova Systems, Olukotun founded Afara Websystems to develop high-throughput, low-power multi-core processors for server systems. The Afara multi-core processor, called Niagara, was acquired by Sun Microsystems and now powers Oracle’s SPARC-based servers.
Olukotun is the Director of the Pervasive Parallel Lab and a member of the Data Analytics for What’s Next (DAWN) Lab, developing infrastructure for usable machine learning.
Olukotun is an ACM Fellow and IEEE Fellow for contributions to multiprocessors on a chip and multi-threaded processor design. Olukotun recently won the prestigious IEEE Computer Society’s Harry H. Goode Memorial Award and was also elected to the National Academy of Engineering—one of the highest professional distinctions accorded to an engineer.
Kunle received his Ph.D. in Computer Engineering from The University of Michigan.
Dr. Cedric Bourrasset is AI Business Leader for High Performance Computing Business Unit at Atos. He is also AI product manager for the Atos Codex AI suite, software enabling AI workloads into HPC environments as well as integrating a computer vision solution. He joined Atos in 2016 as an expert in the HPC/AI domain.
Previously, Cedric received his Ph.D. in Electronics and computer vision from the Blaise Pascal University of Clermont-Ferrand defending the dataflow model of computation for FPGA High Level Synthesis problematic in embedded machine learning applications.
Stelios heads Synopsys' AI Solutions team in the Office of the President, where he researches and applies innovative machine-learning technology to address systemic complexity in the design and manufacturing of integrated computational systems. In 2020, Stelios launched DSO.ai™, the world’s first autonomous AI application for chip design. He has more than 20 years of experience in chip design and EDA software and has founded two companies in this space. Stelios holds an M.S. Electrical Engineering from Stanford University, California.