Headshot of Ryan Farell, Research Scientist

Ryan Farell

I am a Research Scientist at UT leading the Dynamic Belief Games project, which develops predictive intelligent networking agents for dynamic, adversarial communication environments. My current research interests center on Scientific Machine Learning and its applications in defense systems.

Projects

I explore the intersection of machine learning and dynamic systems, emphasizing practical, open-source solutions for real-world problems. Below are some of my current undertakings:

Current Projects

  • Dynamic Belief Games

    Developing Predictive Intelligent Networking (PIN) agents capable of rapid response decision-making in dynamic, adversarial communication networks (DoD-Funded).

  • Equinor Fellowship

    Research fellowship focused on developing machine learning methods for subsurface characterization and reservoir modeling.

  • DEDRECON

    Developed deep learning algorithms for intelligent, real-time processing of hyperspectral (EO/IR) video streams from aerial vehicles, enabling wide-area persistent surveillance (DoD-Funded).

  • Reduced-Order Modeling Tutorials

    A comprehensive set of tutorials on reduced-order modeling techniques for various applications.

  • AcreTech.ai

    AcreTech AI helps customers build accurate predictions of where and how to drill. Drill smarter with AI.

  • PDEs Numerical Methods

    Implementation of numerical methods for solving partial differential equations efficiently.

  • Code Implementations

    Code implementations of various academic papers.

  • QKP Well Placement Optimizer

    A computational framework for optimizing well placement under uncertainty using Gaussian Process models and Quadratic Knapsack Problem solvers.

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