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Michael Pyrcz is a professor in the Hildebrand Department of Petroleum and Geosystems Engineering at the University of Texas at Austin, holding the B. J. Lancaster Professorship. His research interests include Geologic Carbon Storage, Integrated Reservoir Characterization, Unconventional Resources, Petrophysics, and Pore Scale Processes. Dr. Pyrcz's current focus is on enhancing spatial subsurface modeling with new data science methods, including machine learning, to improve resource management—involving mineral, hydrocarbon, and water resources—while minimizing environmental impacts. He emphasizes developing subsurface data science that merges engineering and geoscience through uncertainty analysis and optimal decision-making. Dr. Pyrcz has received numerous awards for teaching excellence and research contributions, including the Lockheed Martin Award for Excellence in Engineering Teaching and recognition as a Distinguished Lecturer from the International Association of Mathematical Geosciences. He also actively shares educational resources online, contributing to the field through various platforms including YouTube and GitHub.
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