I am a postdoctoral researcher in Mechanical and Aerospace Engineering, currently based at the University of Bath. My expertise lies in turbomachinery, experimental testing, performance modelling, and sustainable propulsion technologies. My research focuses on the development and validation of advanced energy and propulsion systems, combining rig design, instrumentation, data analysis, computational modelling, and machine learning techniques. I have worked on projects spanning turbocharger turbines, waste heat recovery, and wind-assisted propulsion, collaborating with academic and industrial partners to deliver practical engineering solutions.
Highlights
· Turbomachinery and radial turbines
· Turbocharger turbine performance measurement
· Low-fidelity and hybrid modelling
· Machine learning for turbine performance prediction
· Waste heat recovery and ORC systems
· Wind-assisted propulsion systems
· Experimental rig design, instrumentation, and testing
Activities & Awards:
- Session chair roles for GPPS and ASME Turbo Expo
2025
- Reviewer roles for ASME Turbo Expo, ORC Power Systems, and Physics of Fluids
- Teaching assistant at Trinity College Dublin and University of Cambridge
2022 – 2024
- Invited presentation at the AI for Fluid Dynamics and Turbomachinery Symposium
2024
- Best Presentation, Turbocharging Seminar
2021
- Outstanding Postgraduate, School of Energy and Power Engineering
2016
- Outstanding paper, The 2nd International Fan Academic Conference in China
2015
Education & Employment:
Postdoctoral Research Associate
University of Bath, Department of Engineering
2025 – present
Postdoctoral Research Associate
Whittle Laboratory, Department of Engineering, University of Cambridge
2023 – 2025
PhD in Mechanical & Aerospace Engineering
Trinity College Dublin, Ireland
Thesis: Wide Range Performance Measurement and Low-Fidelity Modelling of Turbocharger Turbines for Optimizing Powertrain Efficiency
2017 – 2023
MSc in Power Engineering and Engineering Thermophysics
Xi’an Jiaotong University, China
2014–2017
BSc in Power Engineering and Engineering Thermophysics
Xi’an Jiaotong University, China
2010-2014
Publications:
- Ren, P., Osborne, P., Smith, T., Bull, S., Hunter, A., Simsek, Ö., and Sell, N. “Experimental Wind-Tunnel Assessment of Reinforcement Learning Control for Wind-Assisted Propulsion Systems.” IEEE Journal of Oceanic Engineering, 2026. Under review.
- Ren, P., Cox, G., Vera-Morales, M., Watson, S., and Demargne, A. “Investigation of a Novel Low-Speed Radial Re-Entry Turbine for Small-Scale Waste Heat Recovery.” 8th International Seminar on ORC Power Systems, 2025.
- Ren, P., Stuart, C., Zhang, M., Inomata, R., Nakamura, K., Morita, I., and Spence, S. “Investigation of the Surrogate Model in an ANN-Meanline Hybrid Model for Radial Turbine Performance Prediction.” International Journal of Gas Turbine, Propulsion and System, 2024.
- Ren, P., Stuart, C., Spence, S., Inomata, R., Kobayashi, T., and Morita, I. “Using Machine Learning for Loss Prediction in a Hybrid Meanline Modeling Method to Deliver Improved Radial Turbine Performance Prediction.” ASME Journal of Turbomachinery, 2023.
- Gao, Y., Fridh, J., Morrison, R., Ren, P., and Spence, S. “Numerical Investigation of the Performance Impact of Stator Tilting Endwall Designs on a Mixed Flow Turbine.” International Journal of Turbomachinery, Propulsion and Power, 6(2), p. 14, 2021.
- Ren, P., Stuart, C., Spence, S., Inomata, R., Kobayashi, T., and Morita, I. “Using AI for Loss Prediction in a Hybrid Meanline Modelling Method to Deliver Improved Turbocharger Map Prediction.” Turbocharging Seminar, Dalian, China, 2021.
- Wen, S., Ren, P., et al. “Study of Effect on Mach Number on Performance of Centrifugal Compressor Model-Class” Chinese, Journal of Fan Technology, 2015(5), pp. 11–16.