Dr. Ramanzani Kalule earned his Ph.D. (2023) in Engineering from Khalifa鈥疷niversity after pioneering a deep鈥憀earning digital-rock-physics-based framework for petrophysical property estimation. His PhD dissertation integrated machine learning, dynamic modeling, and optimization, along with core-flooding experiments, to enhance petrophysical analysis in complex carbonate systems. He has authored top-tier peer-reviewed journal papers in the SPE Journal, Scientific Reports, and the Arabian Journal for Science and Engineering. His research interests span artificial intelligence, machine learning, reservoir characterization, digital rock physics, enhanced oil recovery, fluid mechanics, and energy systems optimization. Outside of this, he mentors graduate students in AI鈥慸riven geoscience and presents regularly at SPE and Interpore conferences.
