Wednesday, April 27, 2022
1:00 PM - 2:30 PM PDT
This event will be held remotely.
In this session you will learn how to solve and accelerate computationally and data-intensive problems that are becoming common in the areas of machine learning and deep learning using multicore processors, GPUs, and computer clusters. We will introduce you to high-level programming constructs that allow you to parallelize MATLAB applications and run them on multiple processors. We will also discuss how to take advantage of GPUs to speed up computations without low-level programming.
Highlights include:
Timothy Kyung
Application Engineer
Timothy Kyung is an Application Engineer supporting the Government and Department of Defense industry with technical focuses in deployment/interfacing with 3rd party software and parallelization. He holds a B.S. and M.S. in Mechanical Engineering with a focus in robotics from Carnegie Mellon University.
Lisa Kempler
MATLAB Community Strategist
Lisa Kempler is the MATLAB Community Strategist at MathWorks. She loves to work with communities of researchers and educators to help them collaborate on and develop shared resources, including online sites and human networks, that enable them to work more effectively and creatively. Previously, Lisa was the Director of MATLAB Product Management, establishing the PM function at MathWorks. Lisa’s experience in high-tech and working with academic organizations includes conceptualizing products and services, developing and marketing software, coaching academics, and delivering support models. She’s worked on products and systems involving data access; statistics and data analytics; geoscience and geoinformatics, parallel computing and application deployment. Prior to MathWorks, Lisa held positions at DSP Development Corporation and Bolt Beranek and Newman. Lisa holds a bachelor’s degree in Computer Science from Brown University, a master’s in Computer Information Systems from Boston University, and a high-tech MBA from Northeastern University.