Mr Max Malyi

Max Malyi is a renewable energy engineer and PhD Candidate at the Institute for Energy Systems, School of Engineering, University of Edinburgh. His research is situated at the intersection of renewable energy, data science, and control engineering, with a primary focus on enhancing the reliability and operational lifetime of wind turbines.

His work involves developing data-driven, health-aware control strategies that balance power generation with component longevity, particularly for wind turbine electrical subsystems. This is achieved by applying advanced machine learning and natural language processing techniques to analyse large-scale operational data from SCADA systems and maintenance records. The insights from this analysis are then used to inform and validate physics-based aeroelastic simulations in environments like OpenFAST and Simulink.

Through an industrial studentship and active collaboration with industry partners, his research aims to deliver practical, cost-effective solutions that contribute to a more sustainable and resilient energy future.

• Doctor of Philosophy (PhD), Engineering, The University of Edinburgh (2023–Present)
• Master of Engineering (MEng), Wind Power Systems, North China Electric Power University (2017–2020)
• Bachelor of Engineering (BEng), Renewable Energy Systems, Dnipro University of Technology (2013–2017)

As a Teaching Assistant at the School of Engineering, I have contributed to the following courses as a tutor, marker, and/or lab demonstrator:

• Wind Energy
• Python Programming Skills for Engineers
• Professional Development for Engineers
• Power Systems

• Health-aware and multi-objective control for wind turbines
• Reliability and lifetime extension of wind turbine electrical subsystems
• Operational data analysis using SCADA and maintenance records
• Applications of machine learning and large language models in renewable energy
• Predictive maintenance and anomaly detection for wind farms
• Physics-based modelling and digital twins for wind energy systems

My doctoral research is supported by a studentship agreement with one of the leading wind farm operators in Europe. I actively collaborate with industry to ensure my work addresses real-world challenges in wind farm operation and maintenance.

Recent Work:

• Malyi, M., Shek, J., & Biscaya, A. (2025). Exploratory Semantic Reliability Analysis of Wind Turbine Maintenance Logs using Large Language Models. arXiv preprint arXiv:2509.22366.
• Malyi, M., Shek, J., McDonald, A., & Biscaya, A. (2025). A Comparative Benchmark of Large Language Models for Labelling Wind Turbine Maintenance Logs. arXiv preprint arXiv:2509.06813.