leads a team of digital twin developers
and helps build physics-based models
that can be combined with machine-learning algorithms.
Sahika Genc, another dual scien-
tist, developed systems for ICU alarms
before transitioning to GE’s machine-
learning lab in 2014. Genc is now a
machine-learning scientist who uses
deep learning and reinforcement learn-
ing to make GE’s energy management
systems more efficient. One of her
recent projects applied machine learning and heat transfer theory to identify how
building energy is dissipated and stored. The forecasts will help GE customers
reduce their energy consumption.
These hybrid researchers could be GE’s best shot at remaining relevant for
another century as the company looks for growth opportunities in such competitive and mature industries as turbines, jet engines, and locomotives.
Parris, the software research leader, admits that some of GE’s 2,000 research-
ers still regard certain aspects of the new approach as a “passing fad.”
But scientists who don’t make the leap may get left behind. In January, the
company laid off researchers in areas deemed peripheral to GE’s “digital indus-
trial” strategy. That’s after creating 100 new research jobs related to AI and robot-
ics in 2016.
Digital replicas of jet engines help GE’s aviation customers save money by predicting exactly when they will
need maintenance. Here a GE engine sits at an overhaul facility in Rio de Janeiro, Brazil.