Research at PAIS focuses on developing methodologies and algorithms aimed at advancing predictive analytics and decision-making under uncertainty in applications spanning traditional manufacturing, service, and energy sectors to unique and unconventional application domains, such as space services and deep space exploration.

Industrial Analytics & Machine Learning

Digital Twin

Developing analytic algorithms specifically tailored to solve data modeling challenges in IoT-enabled industrial applications.

Service Logistics & Intelligent MRO

Service Management

Integrating analytics and optimization for service logistics and intelligent maintenance, repair and operations (MRO).

Cyber-Security & Data Privacy in IoT Systems

Block Chain

Developing modeling frameworks and architecture to enhance industrial ICS cyber-security and IoT data privacy. 

The NASA HOME Space Institute

NASA HOME logo

Developing autonomous predictive analytic for enabling self-awareness and self-sufficiency in deep space Smart Habitats.

Our Mission

Through our research, we strive to provide various industries with a vehicle for addressing related challenges through a single point of contact, while using a problem-driven approach.

Key research areas:

Our Affiliates

Georgia Tech Supply Chain and Logistics InstituteH. Milton Stewart School of Industrial and Systems EngineeringGeorgia Tech Manufacturing Institute