Yusuf Falola

Experience

1. Senior Technologist - Machine Learning

   Halliburton

   Aug 2024 — Present · Houston, TX, US

   Architected and deployed a Deep Reinforcement Learning (DRL)-based FDP optimization engine that maximized asset value, achieving a 2x NPV over traditional development plans- Spearheaded the creation of a reservoir-invariant deep reinforcement learning model for optimal well placement, slashing the required computational time by 98% and accelerating project timelines- Oversaw the creation of high-fidelity surrogate models for complex geo-sequestration scenarios, enabling near real-time predictions and reducing computational expense by a factor of Drove the adoption of an intelligent DRL agent to balance operational costs with carbon credit optimization, improving the overall economic viability of sequestration initiatives- US Patent Filed: Advanced Oil Field Development: A Deep Reinforcement Learning Approach with Reservoir-Invariant Transfer Learning- US Patent Filed: Seeding Reinforcement Learning with Physics-Based Expertise for Oil and Gas Field Development Planning

Education

• Rivers State University of Science and Technology

  Bachelor's degree

• Imperial College London

  Master's degree

• Texas A&M University

  PhD