Jaise Kuriakose

University of Manchester



Current position
Jaise Kuriakose is a Lecturer in Climate Change at the Tyndall Centre for Climate Change Research, University of Manchester. He contributes to undergraduate/postgraduate teaching on Renewable Energy and Clean Technology, Renewable Energy and Sustainable Waste Management. Jaise is an electrical engineer with 10 years of industrial experience including development of a microgrid system integrating renewable generation and battery storage, renewable energy systems and power distribution systems up to 110 kV. He completed his PhD in Environmental Engineering at Tyndall Manchester examining how smart grid technologies could be utilised to address the challenges of operating a decarbonised electricity grid. 

Jaise has previously worked under the EPSRC Resilient Electricity Networks for Great Britain (RESNET) project which analysed the reliability of the UK electricity system in the context of climate change and developed tools for quantifying the value of adaptations that would enhance its resilience. He has since expanded his research profile on low carbon energy systems that are resilient to climate change impacts, future changes in weather patterns due to changing climate and how that will impact the renewable generation and demand. His research expertise covers energy generation modelling, electricity dispatch model, carbon budgets and emissions pathways. 

Jaise has undertaken consultancy projects with the Electricity Northwest and Greater Manchester Combined Authorities. He was selected as an expert into the academic panel on Climate Research for UK India Education Research Initiative (UKIERI) which is funded and supported by the UK and Indian governments. He regularly gives public talks about climate change and sustainability, and engages with policy-makers. Jaise has published diverse interdisciplinary research through peer-reviewed articles, responses to Government inquiries and conference papers.


Research Interests Renewable Energy, carbon budgets, energy modelling, smart grids, energy storage, resilience of energy systems