Kyle Mooney, PhD, is the Director of Modeling & Optimization at Geminus, where he leads the development of advanced computational models that bring physics-informed AI into real-world operations across the energy value chain. He has more than a decade of experience in computational fluid dynamics, scientific machine learning, and engineering optimization, applying his expertise to deliver high-value digital solutions across upstream, midstream, and downstream operations. Kyle earned both his BS and PhD in Mechanical Engineering with a focus on Computational Fluid Dynamics from the University of Massachusetts Amherst. His career includes roles in academia and industry, with experience at Intel, ICON Technology & Process Consulting, GrowX Inc., and FRESH, before joining Geminus in 2020. He has published multiple peer-reviewed and conference papers, including recent work on hybrid physics and machine learning modeling for optimizing complex pipeline networks. Kyle is also a frequent speaker at industry events, presenting case studies that highlight the value of combining physics-based simulation with machine learning to accelerate decision-making and improve performance outcomes.