Decision systems & predictive modeling for complex engineering and manufacturing problems
### Overview I build predictive models and decision systems for problems where outcomes depend on complex interactions between process, physical or biological systems, and uncertainty. My work has been used in national...
Ai-driven statistical digital twins for engineering and product systems
This technology applies advanced statistical modeling and machine learning to build predictive “digital twin” models for complex engineering and product systems. The approach combines physics-informed modeling, modern ma...
AI/ML models for high-accuracy, faster multilayer flexible packaging identification
Advanced AI/ML models improve multilayer flexible packaging identification using existing infrastructure, targeting faster and more accurate sorting decisions. The approach aims to enhance sorting accuracy, purity, and r...
Predictive AI for protein-based food formulation
Leverage a proven digital-twin framework to optimize protein-based food recipes using predictive AI, enhancing speed, efficiency, and compliance in formulation.
Data-driven digital twin framework for adaptive process optimization
A statistical-AI framework enhancing digital twins for process optimization by integrating real-time data with physics-based simulations, improving yield and reducing trial-and-error. Proven in manufacturing, ready for c...
Explainable AI/ML and statistical design for PET container optimization
Use explainable AI/ML combined with statistical design to optimize polyethylene terephthalate (PET) container designs. The approach applies data analysis to identify design–performance relationships, supports transparent...
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