Academic Division: Manufacturing and Management
Research group: Manufacturing Systems
- Predictive Maintenance
- Machine Learning
- Digital Twin
- Internet of Things (IoT)
- Distributed System Architectures
- Predictive maintenance under limited data availability (PhD research project)
- Digital twin research platform development in collaboration with Centre for Digital Built Britain, Bentley Systems, Topcon, GeoSLAM and RedBite
Gishan joined DIAL in October 2017 to pursue an EPSRC funded PhD, under the supervision of Dr Ajith Parlikad. His main area of research interest is predictive maintenance. In his PhD, he is researching on how to develop a distributed generative learning-based technique for predicting likelihood of machine failure under limited data availability. And how such improved prediction of the likelihood of failures be exploited to develop optimised predictive maintenance policies.
Before starting the PhD, he completed a master’s degree in Computer Science and Artificial Intelligence from the University of Nottingham. As part of his master’s program, he worked with Prof Dario Landa-Silva on the COSLE (Collaborative Optimisation in a Shared-Logistics Environment) project and developed a computer vision-based freight measuring solution. Gishan has also completed internships at Roller Agency and JP Morgan during his undergraduate degree.
He also worked as a software developer and later as a senior software architect and involved in designing and implementing software systems for patient health management and disaster monitoring for companies such as GSK, Novartis, MyZone and HelpAge International.