Dr. Ghaemi received the Ph.D. degree in electrical engineering and the M.S. degree in mathematics from University of Michigan in 2010 and 2009 respectively. He was a visiting scholor at ETH in 2008. From 2010 to 2012 he was a post-doctoral associate in the Mechanical Engineering department at MIT, researching supervisory control of order-preserving systems and stochastic analysis of biological systems.

Working on 3- year, $4.1 million project from the U.S. Department of Energy to develop automated cyber protection solution for commercial building energy management systems

Putting optimal back on the table for real applications using Quantum as an accelerator

Matthew Seidel graduated from Clarkson University with a B.S. in Electrical Engineer and Physics. After graduating, Matthew has gained over 5 years of embedded system design experience in both the commercial and defense sectors. His areas of specialization are in FPGA design, high speed digital board design, and embedded programming.

Currently, Matthew is helping in the areas of hardware cyber security, machine learning, and high speed image acquisition. 

Keeping workers safe through analytics derived from sensor data fusion & aggregation and delivered through pervasive connectivity & real-time visualization

GE researchers awarded DARPA project to develop new VERDICT tool for assessing and strengthening cyber protections for military and other industrial systems

GE Research teams up with NYSID and the Center for Disability Services in Albany to supply 400 face shields to Albany Medical Center.

~10 years' wet & solid-state chemistry experience. Strong synthetic, characterization, and processing skills for both inorganic and organic materials. Areas of expertise:

Dr. Naresh Iyer is a Principal Scientist in the AI and Machine Learning group at GE Research. He has 20 years of experience in the research and application of machine learning to a variety of industry problems, including asset life prognostics, surrogate modeling, multi-objective optimization and decision making under uncertainty. He has developed solutions for a diverse range of industrial applications using methods in supervised, unsupervised, semi-supervised learning and evolutionary soft computing. 

What you Need to Know: