Data Champions Search

Additional areas of expertise:

Neuroscience data

My research focuses on the applications of machine learning to problems in structural biology and drug discovery.

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.

Elizabeth has an MPhil in HPS from Cambridge and has worked for the Newton Project Canada. She has worked for the Darwin Correspondence Project for more than fifteen years, and assisted in the conversion of the Project's core files to TEI XML, and is now developing and implementing strategies to ensure the quality, robustness, interoperability, and long-term viability of our electronic data. She is a co-founder of Epsilon, a nineteenth century science letters platform and has been a guest lecturer at the Digital Humanities at Oxford Summer School.