Abstract: Recent advances in Artificial Intelligence (AI) and Machine Learning (ML) have relied on access to modern computing hardware, massive quantities of data, and advanced algorithms that leverage high-performance computing centers such as the MIT Lincoln Laboratory Supercomputing Center (LLSC). While AI will play in important role in many organizations, rapid adoption of AI is often limited by legacy hardware, siloed and messy data, and sparse/unsupervised ML algorithms in data starved application domains. As a world-leader in developing high-performance computing (HPC) tools that are easy-to-use without compromising performance, the LLSC has been developing a number of novel technologies that aim to overcome these technical hurdles that restrict easy adoption of AI. This research in “Fast AI” is pillared on modern computing, big data management, and interfaces & algorithms. In this talk, I will discuss the AI landscape; highlight a few AI adoption challenges; provide an overview of research that simplifies AI adoption; and discuss novel AI applications to cybersecurity and video recognition.
Bio: Dr. Vijay N. Gadepally is a Senior Scientist at MIT Lincoln Laboratory. Vijay holds M.Sc. and PhD degrees in Electrical and Computer Engineering from The Ohio State University and a B.Tech degree in Electrical Engineering from the Indian Institute of Technology, Kanpur. In 2011, Vijay received an Outstanding Graduate Student Award at The Ohio State University. In 2016, Vijay received MIT Lincoln Laboratory’s Early Career Technical Achievement Award and in 2017, Vijay was named to AFCEA's inaugural 40 under 40 list. Vijay’s research interests are in high performance computing, machine learning, artificial intelligence and high-performance databases. Vijay is a Senior Member of the IEEE.
Vijay Gadepally, PhD
Senior Scientist | Massachusetts Institute of Technology, Lincoln Laboratory