Jai Jaiprakash - Data Science in Semiconductor Technology and Product Development

Jai Jaiprakash
Director, Technology and Products Data Science
Micron Technologies Inc.

Data Science in Semiconductor Technology and Product Development

Biography

Jai Jaiprakash is a semiconductor technologist and entrepreneur. Over a 25+ year career spanning F50 companies to startups, he has brought several innovative products to market. In his current role as the Director of Data Science for the Technology and Products Group at Micron Technologies inc., he is helping drive the digital transformation of leading edge memory and storage product development.

He holds an M.S. and Ph.D. in Chemical Engineering from the University of Kansas and an MBA in Strategic Management and Finance from the Wharton School of Business at the University of Pennsylvania. He is an author in several peer-reviewed journals and holds 42 Patents in semiconductor and sensor technologies.

In his leisure time, he likes to choose from hiking, skiing, practicing taekwondo, woodworking, or catching up on writings in philosophy and neuroscience.

Abstract

Data is the new economy. Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing our quality of life at the home, at the office, and on the go. In this talk, Dr. Jai Jaiprakash will share how such modern Data Science methodologies are transforming the face of product development of the memory and storage products that enable the data economy and AI revolution to unfold. In addition to AI and ML, pivotal trends driving the memory and storage industry include 5G & Mobility, IoT & Edge Compute, Virtualization, and Multimedia. Together these markets are driving a $13 Trillion global opportunity.

The semiconductor industry faces steep challenges to meet market demands. To meet this challenge, we need to cross new frontiers in research, development, and manufacturing by engaging the best talent across several disciplines including Electrical Engineering, Materials Science, and Computer Science.

Today the industry is already using advanced machine learning and modeling techniques. However, there is tremendous opportunity to use transformational solutions as decision accelerators, enable more sustainable design and manufacturing, and develop Innovative solutions that do more work with less energy per bit, As end-user applications become increasingly complex, a system-level approach to product development which integrates software, firmware, and hardware is required for achieving the highest performance.