GE's non-invasive SMS-EIT prototype system provides higher signal-to-noise ratio and greater sensitivity to continuously image pulmonary perfusion and ventilation.

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

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

Tube Watch is GE Healthcare’s predictive solution that is designed to remotely monitor and predict X-ray tube failures before any disruption occurs.

In 1990 Dr. Tu joined Sony Research in Tokyo Japan, where he developed a number of computer vision algorithms for man-machine interfaces. While at Oxford University, his research was devoted to the development of computer vision methods for the autumatic analysis of seismic imagery.

Dr. Al-Kofahi brings 15 years of experience in developing Artificial Intelligence (AI) and computer vision solutions for a variety of healthcare and industrial applications. He received his Ph.D in Computer Systems Engineering from Rensselaer Polytechnic Institute in 2009. During his PhD and industrial work prior to GE, he developed algorithms to analyze 2-D and 3-D biomedical images and integrated them into products used by clinical laboratory professionals and life scientists.

Developing cutting edge technologies in machine architectures, energy sources, sensing and controls for step-change in build size and speed, while assuring part quality.

Tools for noninvasively modulating neural signaling in peripheral organs to advance the study of nerves and their effect on homeostasis and disease.

The future of aviation lies in disruption stemming from digitization. At GE, that future starts with a Digital Twin for every aircraft engine, tracking and understanding its operational effectiveness, health, and fleet role - from manufacturing to retirement. Dr. Paul Ardis leads the research portfolio to make this happen, working across capabilities and business units to make the most of GE's best scientists and engineers.

Functional demonstrations of Blockchain technology applied to real world industrial ecosystems.