Computational Engineering & Reliability Laboratory (CERL)
CERL develops fundamental methodologies to enhance the reliability and resiliency of complex engineering systems through the application of artificial intelligence and machine learning (AI/ML) techniques, probability and statistics theories, and physics-based computational simulations.
All models are wrong!-George E. P. Box
But some are useful! We develop methods and tools to create models that are useful for risk-informed decision-making under uncertainty .
Uncertainty
Uncertainty is inevitable in design, analysis, and operation of engineering systems.
Reliability
Assess the reliability of engineering systems using simulations and data by considering uncertainty.
Design Optimization
Optimize engineering systems under uncertainty to meet reliability and resilience requirements.
Digital Twins
Coupling digital model with physical system for real-time updating and decision making.
Multi-disciplinary Research
We conduct multi-disciplinary research that sits at the intersection of Statistics, Machine learning, and Computational engineering.
Close Collaboration with industry
Located in Detroit area and as neighbor of Ford Motor Company, we collaborate closely with industry partners, federal agencies, and renowned researchers in academia. We develop fundamental methodologies and address practical engineering challenges.
Solving challenging but Impactful Engineering Problems
Some example projects are shown below.
Off-Road Autonomous Ground Vehicles
Large Civil Infrastructures
Aerospace Structures
Hydrology Systems
[email protected]
2250 Heinz Prechter Engineering Complex | 4901 Evergreen Road | Dearborn, MI 48128
