I’m a seasoned computational data scientist with 20+ years of success in developing physics-based solutions across energy and environmental sectors. My expertise encompasses software development, AI (including transfer learning, CNNs, NLP, LLMs, and generative AI), and mentoring data science teams. I excel in transforming complex problems into innovative, AI-driven solutions, as demonstrated by my development of a real-time reservoir management system that yielded $100+ million NPV savings.
SKILLS
AI & Machine Learning: Deep learning, transformers, LLMs, search algorithms, reinforcement learning, Bayesian methods
Programming: Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow), MATLAB, C, R
Computational Science: Optimization, numerical methods (ODEs/PDEs), HPC
Cloud: AWS, Azure
Software Development: PyCharm, Docker, Git, Agile, ChatGPT, Bard, Copilot
Domain Expertise: Reservoir engineering, geosciences, geomechanics, electrochemistry, energy
Leadership: Team management, mentorship, adaptability, strategic problem-solving
EXPERIENCE HIGHLIGHTS
DeepCast.ai: Led development of a generative AI platform for physics-based modeling and a real-time reservoir management solution generating $100+ million NPV.
Industry/Academia Experience: Proven track record in both leading corporate data science initiatives (ConocoPhillips, Sanchez Oil & Gas) and mentoring future talent (Rice University)
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