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.
~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.
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.
Marissa Brennan is an Edison Engineer at GE Research that specializes in creating new materials and material processing capabilities. The durable innovations Marissa has been a part of creating contribute to substantial impacts in the aviation industry enabling safer, energy efficient, advanced technologies for flight.
Xin Li is a research scientist in the Radiation Imaging lab. Xin's work aims at pushing the limits of industrial inspection and metrology using X-ray and CT. The work is important to products and services in aviation, power, oil & gas, and advanced manufacturing.
Xin holds degrees in Engineering Physics and Electrical and Computer Engineering and has broad research experiences in imaging system design and optimization, image quality evaluation, image quality improvement, and image analysis.
