Data Champions Search

Dequn (Peter) Teng is a Ph.D. candidate supervised by Dr. Veronica Martinez in the Business Model Innovation Group at the Institute of Manufacturing. His current research area is on blockchain and machine learning integrated methods for supply chain management.
   
Dequn graduated from University of Liverpool (2+2 route) with a first class honours degree in Computer Science and Electronic Engineering. His past research experiences relate to blockchain and digital innovation, with peer reviewed conference paper publications on IEEE Xplore and EI. Additionally, He has ten invention patent applications under substantive review process, ranging from Blockchain and Mechanical Design Innovation. For industrial exposure, he has taken research internships at Deutsche Bank (Shanghai) for digital transformation research, and Unilever (UK) for PowerBI visualization. Moreover, he loves mathematical modelling and was awarded Meritorious Winner at the Mathematical Contest in Modeling.

I am a Postdoctoral Research Associate at the Scott Polar Research Institute, where I use a combination of novel satellite imaging techniques, airborne geophysical observations and climate-ocean model data to investigate the key climatic drivers responsible for controlling the rapid deterioration of the Antarctic Ice Sheet since the onset of the satellite era (~1970-present). As such, I have a range of experience in the handling, processing and visualisation of complex geospatial datasets, and have experience in the usage of several different computer programming languages to do this. My experience also includes the long-term archiving and preservation of data to support scientific reproducibility, ranging from the publication of small, project-specific datasets to institutional collections (including assisting with the recent publication of SPRI’s historical Arctic airborne radio echo sounding data archives).