Muting Hao

Dr. Muting Hao serves as a Research Fellow at the Oxford Thermofluids Institute (OTI) and an Associate Member of Faculty in the Department of Engineering Science at the University of Oxford. Since 2024, she has held a Career Development Research Fellowship at St John's College, focusing on advancing computational fluid dynamics (CFD) to address global energy and pollution challenges in aviation technology through fundamental research and industrial collaboration.

Dr. Hao completed her DPhil in 2022 at the University of Oxford specializing in numerical methods and conjugate heat transfer for gas turbine film cooling under Rolls-Royce sponsorship. Her academic background includes BSc and MSc qualifications, though specific institutions are not detailed in available records.

Her research spans numerical methods in fluid dynamics, turbomachinery, turbine cooling, conjugate heat transfer, turbofan design, large eddy simulation (LES), turbulence, and machine learning integration. She investigates unsteady flows across gas turbines, compressors, steam turbines, and nuclear reactor coolant pumps, with current emphasis on aerospace CFD applications and AI-enhanced fluid dynamics modeling for sustainable aviation solutions.

Analysis of her publication record (2018-2023) reveals consistent focus on film cooling optimization, turbulence modeling, and advanced CFD techniques for turbomachinery. Recent work increasingly incorporates machine learning approaches and high bypass ratio turbofan design, reflecting strategic alignment with industry needs for efficient propulsion systems.

Dr. Hao's contributions have earned significant recognition:

• UKRI Computing Insight UK 2023 Jacky Pallas Award
• The Osborne Reynolds 2024 Best Poster Award

She currently leads UKRI-funded research on high bypass ratio turbofan design and maintains active collaboration with Rolls-Royce on solver development for next-generation aircraft engines. Dr. Hao mentors potential DPhil students in fundamental fluid dynamics, aerodynamics, high-order numerical schemes, and machine learning applications in CFD, emphasizing practical solutions for aviation sustainability challenges.

As a core member of OTI's CFD Methodology group, Dr. Hao operates at the intersection of academic research and industrial application, leveraging Oxford's infrastructure and Rolls-Royce partnerships to advance turbomachinery efficiency through cutting-edge computational approaches and emerging AI methodologies.