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.

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

The Edison Engineering Development Program (EEDP) gave Alex the opportunity to excel and the freedom to fail.

GE Research is giving EEDP participants an intimate look at the GE technologies that are disrupting industrial ecosystems.

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:

Rodrigo Lopez Negrete obtained his BS and MSc from the Universidad Iberoamericana in Mexico City in 2005 and 2007, respectively. He obtained his PhD from Carnegie Mellon University in Pittsburgh, PA in 2011. All his degrees are in chemical engineering, specializing in process systems engineering, nonlinear programming, and controls.

Dr. Yiwei Fu is a Research Scientist in the Machine Learning team at GE Research in Niskayuna, NY. He is a reseracher with a strong and diverse background in machine learning, robotics and control & optimization, etc. His current research interests include deep learning for spatiotemporal data; reinforcement learning for control and numerical methods; applied machine learning for materials, grids and robotics, etc.