Arun Subramaniyan joined Intel to lead the Cloud & AI Strategy team. Arun joined Intel from AWS, where he led the global solutions team for Machine Learning, Quantum Computing, High Performance Computing (HPC), Autonomous Vehicles, and Autonomous Computing at AWS. His team was responsible for developing solutions across all areas of HPC, quantum computing, and large-scale machine learning applications, spanning $1.5B+ portfolio. Arun founded and grew the global teams for Autonomous Computing and Quantum Computing Go-to-market and solutions at AWS and grew the businesses 2-3x.

Arun’s primary areas of research focus are Bayesian methods, global optimization, probabilistic deep learning for large scale applications, and distributed computing. He enjoys working at the intersection of massively parallel computing and modeling large-scale systems. Before AWS, Arun founded and led the AI products team at GE’s Oil & Gas division and grew the digital products business successfully. He and his team developed deep learning-augmented hybrid analytics for all segments of the oil & gas industry. Arun led the development of the Digital Twin platform for GE at GE’s Global Research Center. The platform continues to enable several thousand engineers to build advanced models efficiently. The asset specific cumulative damage modeling techniques he and his team pioneered define the standard for industrial damage modeling.

As a Six Sigma Master Black Belt, he developed advanced techniques and tools for efficiently modeling large scale systems like jet engine fleets, gas turbines in powerplants, and accelerated design times by 3-4X. Arun is a prolific researcher with a Ph.D. in Aerospace Engineering from Purdue University with 19 granted patents (54 filed), and 50+ international publications that have been cited more than 1000 times with an h-index of 13. He is also a recipient of the Hull Award from GE, which honors technologists for their outstanding technical impact.