Personal profile

Academic Biography

Dr Kin Wai Cheah obtained his MEng (Hons) degree in Chemical Engineering from the Department of Chemical and Environmental Engineering, University of Nottingham (Malaysia Campus) in 2014. In late 2019, he completed his PhD degree in Chemical Engineering from University Technology PETRONAS (UTP), Malaysia under the supervision of Prof. Ir. Dr Suzana Yusup. He also completed a 6-month Erasmus placement in the European Bioenergy Research Institute (Aston University) under the supervision of Prof. Anthony Bridgwater and Dr Georgios Kyriakou. Upon graduation, Dr Kin joined the Energy and Environmental Institute of University of Hull, United Kingdom and worked as a Postdoctoral Research Associate (PDRA) for two years, where he was actively involved in several THYME funded industrial biomass to energy research projects and working closely with several international industrial chemical companies in UK and Malaysia including Malaysia Palm Oil Berhad (MPOB), PETRONAS Malaysia, CPI, NEPIC, TVCA, Ensus Limited, Croda, Surfachem, and Unilver.

Presently, Dr Kin is a lecturer in Chemical Engineering at the School of Computing, Engineering and Digital Technologies of Teesside University. His research interest primary lies in the area of thermochemical conversion of biomass to renewable biofuels.  Much of his work has been on upgrading underutilized biomass waste to liquid and gaseous fuels via various thermochemical conversion technologies including pyrolysis, gasification, hydrodeoxygenation and catalytic cracking processes. He has vast experiences in conducting techno-economic feasibility and life cycle assessment studies for biomass thermochemical conversion technologies. As of May 2022, he has published over 30 peer-reviewed publications including three book chapters with a h-index of 13. He is very keen in expanding his research knowledge and expertise into other research areas including catalysis, green chemistry, and advanced predictive analytics in chemical manufacturing including neural networks and deep learning.


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