Darrin P. Johnson, Global Director of Solution Architectures, NVIDIA
Darrin is the Global Director of Solution Architecture for Enterprise at Nvidia. He and his team lead all DGX, OEM, and storage reference architecture initiatives. Darrin’s experience spans 25 years of leadership in O/S, high performance systems, networking, storage, I/O and most recently AI/Deep Learning technologies with companies such as Cray, SGI, Adaptec, Sun Microsystems, Oracle and now NVIDIA. He is a certified Deep Learning trainer for NVIDIA as well.
Matt Miller, Director of Product Marketing, WekaIO
Matt Miller is the Director of Product Marketing for WekaIO, responsible for marketing strategy and positioning. Matt has spent nearly 20 years in the storage industry in both product management and product marketing roles, for companies such as HPE, Nimble Storage, NetApp, Sun Mircosystems and Veritas.
Greg Holick, Director of Technology Alliances, Western Digital
Greg Holick is a senior technologist with over 15 years of experience in the data storage industry. Throughout his tenure, Greg has engineered software solutions, architected complex storage environments, been the product manager on private cloud solutions, and guided customers and partners on some of the most challenging storage infrastructures in the industry.
The rise of data science is often attributed to the exponential growth of data, whether structured or unstructured. While likely true, it is also true that the supporting AI infrastructure has enabled not only the growth of the data but also has become critical to extracting the value from the data explosion. The industry leaders NVIDIA, WekaIO and Western Digital will each bring their perspective to the importance of AI infrastructure to data science. Whether you are a data scientist, IT professional, or C-level decision maker you will learn how thoughtful AI infrastructure can accelerate your time to insight, time to value and increase profit for your business. You will take away techniques to overcome common challenges and barriers to successful data science in development and in production. Come ready with your questions for the panel to help accelerate your data science.