Dr Ajit Pillai

Ajit’s research is focused on the development and deployment of optimization algorithms to aid in the design of offshore renewable energy devices and arrays. From 2021 he is a Royal Academy of Engineering Research Fellow developing new techniques to integrate numerical physics-based models with targeted, dynamic measurement campaigns using autonomous vessels to reduce offshore uncertainty and develop a new framework for spatial data.

While at the University of Exeter he has worked on several projects applying optimization and machine learning techniques including:

• EPSRC SuperGen UK Centre for Marine Energy Research (UKCMER) on the integration of multi-objective optimization approaches in the design of offshore renewable energy devices and subsystems.
• EPSRC Supergen ORE Hub Flexible Fund Project Accounting for Current in Wave Buoy Measurements where the team are developing a novel optimization-based framework for considering the impact of currents on wave buoys
• ERDF funded Marine-I working to support SMEs working in marine engineering in Cornwall
• Interreg France (Channel) England supported EUROSWAC project exploring sea water cooling systems
• EPSRC Supergen ORE Hub Flexible Fund project Machine Learning for Low-Cost Offshore Modelling (MaLCOM) exploring the use of machine learning to improve wave forecasting methods
• ERDF funded Cornwall FLOW Accelerator supporting the development of floating offshore wind in the South-West of the UK
• EPSRC funded Mooring analysis and design for offshore WEC survivability and fatigue (MoorWEC) developing new hydrodynamic approaches for modelling mooring systems
• InnovateUK KTP with Imetrum Ltd. where the team explored long-term structural health monitoring using vision-based sensing and digital image correlation. 
• InnovateUK KTP with Hydrostar where the team are exploring AI and machine learning based control for hydrogen electrolysers. 
• EPSRC Supergen ORE Hub Flexible Fund project NextGen Anchor Design: Harnessing the Potential of Probabilistic Surrogates and Seabed Evolution Modelling developing a machine learning surrogate model to optimise whole-life anchor design for floating offshore renewable energy
• EPSRC Supergen ORE Hub Flexible Fund project EnviroClass: Pioneering Innovative Environmental Conditions Classification to Unlock Standardisation and Mass Manufacturing of Floating Offshore Wind Turbines project developing a methodology to define standard environmental classes to enable mass manufacturing of floating offshore wind turbines

Ajit also teaches on numerous programmes at the University of Exeter, including BEng Renewable Energy Engineering and MSc Renewable Energy Engineering.

Prior to joining the University of Exeter, Ajit obtained an EngD in offshore renewable energy through the Industrial Doctoral Centre for Offshore Renewable Energy (IDCORE); a partnership between the Universities of Edinburgh, Exeter, and Strathclyde with the Scottish Association for Marine Science, HR-Wallingford, the ETI, and the EPSRC. His EngD research, completed in partnership with EDF Energy R&D UK Centre, led to the development of a methodology and tool for the optimization of offshore wind farm layouts considering the sites and constraints relevant for future gigawatt scale wind farms in European waters.

Ajit also holds an MSc in Sustainable Energy Systems from The University of Edinburgh and a BSc in Mechanical Engineering from Columbia University.