Breaking the traditional thought process of “protect the box,” this mission demonstrated concepts on how to protect the system at both fundamental and system-wide levels

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.

Digital Thread for Design℠ (DT4D℠) is an automated, AI-driven workflow process to revolutionize the design of complex industrial components and systems.

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

Innovations from diverse disciplines including wireless communications, electronics, materials science, instrumentation, embedded software, machine learning, and packaging.

Predictive Maintenance technologies aim to detect, diagnose, and predict failures and degradation in machine components prior to criticality.  The ultimate goal is to prevent downtime, identify root causes for follow-up action, and enable efficient evidence-based maintenance planning and optimization.

A Digital Twin is a digital model of an industrial asset—like a jet engine or a wind turbine. They are built by continuously collecting data off physical and virtual sensors on the asset and analyzing the data to gain unique insights about performance and operation that drive business value and outcomes.