Bangladeshi PhD researcher leads AI energy study in U.S
Shaolin Jahan Eidee, a Bangladeshi engineer and doctoral researcher, is conducting advanced artificial intelligence-driven drilling research at the Colorado School of Mines.
The school is a leading U.S. engineering institution internationally recognized for research in energy, mining, and subsurface systems. The university is ranked among the top petroleum engineering programs in the United States.
Eidee is currently pursuing a PhD in Petroleum Engineering, where her research focuses on developing physics-informed machine learning frameworks for hard-rock drilling optimization and real-time prediction of drilling-bit wear and downhole failure.
Her work integrates mechanistic drilling physics, high-frequency drilling telemetry, and data-driven modeling. She is relentlessly working to improve operational reliability, reduce nonproductive time, and enhance safety in subsurface energy operations.
Her research has applications in geothermal energy development, drilling automation, and critical subsurface infrastructure systems. Her work supports broader U.S. priorities related to energy innovation, infrastructure resilience, and advanced engineering technologies by improving drilling efficiency and reducing operational risk.
Eidee’s research has been presented at major U.S. technical conferences, including the Geothermal Rising Conference and the U.S. Rock Mechanics/Geomechanics Symposium. In 2025, she received Oklahoma State University’s university-wide Master’s Phoenix Award in recognition of outstanding research achievement, academic excellence, and leadership.
A faculty researcher in petroleum engineering at the Colorado School of Mines stated: “Shaolin’s research combines artificial intelligence with drilling systems engineering to address important challenges in subsurface energy operations. Her work contributes to ongoing efforts to improve drilling efficiency, operational safety, and predictive decision-making in energy infrastructure.”
Md. Tauhidur Rahman, former Assistant Professor of Petroleum and Mining Engineering at the Military Institute of Science and Technology (MIST), commented: “Shaolin demonstrated strong technical ability, discipline, and research potential from the beginning of her academic career. Her progression from MIST to advanced research in the United States reflects her sustained commitment to petroleum and subsurface engineering research.”
Before beginning her doctoral studies, Eidee served as a university lecturer and completed graduate degrees in both petroleum engineering and applied statistics and data science, establishing an interdisciplinary background in engineering, machine learning, and data-driven modeling.
From Bangladesh to one of the United States’ leading engineering institutions, Shaolin Jahan Eidee is emerging as a researcher working at the intersection of artificial intelligence, drilling systems engineering, and energy technology. Her ongoing research aligns with growing national and industrial interest in improving the safety, efficiency, and reliability of subsurface energy operations.
