Contact Dr Ravi Pandit
- Tel: +44 (0) 1234 758471
- Email: Ravi.Pandit@cranfield.ac.uk
- Twitter:
Background
Dr Ravi Pandit is currently a Lecturer in Instrumentation and AI at the Centre for Life-cycle Engineering and Management within the School of Aerospace, Transport and Manufacturing, Â鶹´«Ã½AV. Prior to that, he held several academic posts such as Research Fellow (the University of Exeter, 2020-2021), Research Associate (the University of Strathclyde, 2016-2020), Visiting Researcher (UCLM Spain, 2018), Visiting Researcher (Wood plc Scotland, 2016-2017), Assistant Professor(Electronics and Instrumentation Engineering, Jadavpur University. 2014-2016), Assistant Professor(School of Electrical Engineering, VIT Vellore, 2011-2014) respectively. During his professional career, he received a number of prestigious and highly competitive research awards/fellowships, for example, Travel Grant (US$3.5k), Marie Curie Fellowship (of value £224,325.00), Erasmus Mundas (of value ~ 129,000). As of now, has published numerous papers in highly ranked journals (mostly in Q1 & Q2) and have presented my research at several international conferences and workshops in these areas. Overall, he has more than 10 years of academic and research experience; with various reputed academics and industries through a number of interdisciplinary projects.
Research opportunities
Dr Ravi Pandit is interested in supervising PhD, and MSc students with a research interest in:
Data analytics and Machine Learning for clean energy technologies (e.g., wind and solar)
Data analytics and Machine Learning for railways
Descriptive, predictive and prescriptive analytics
Online condition-based monitoring
Big data statistical analysis: feature analysis, computation, modelling (time-series)
Digital twins and the Internet of Things (IoT) for Offshore wind
Please get in touch if you would like to collaborate or work on these areas.
Opportunities
Dr Ravi Pandit is currently recruiting for PhD (self-funded) and Post-Doc (through fellowship scheme e.g., RAEng, UKRI, etc) in these above areas. A highly motivated top-quality candidate (both home and international) requested to send a detailed CV and your top 1-2 papers (for post-doc) for discussion.
Current activities
Ravi's main research interests include offshore wind energy covering predictive maintenance, digital twins, Internet of Things (IoT), online condition monitoring, SCADA and vibration data analysis and remaining useful life (RUL) estimation. With a background in data analytics and machine learning and clean energy technologies, he is interested in understanding the digitalisation aspect of clean energy technologies and how state-of-art digital technologies can improve decision management, automate the process and reduce overall costs.