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.

After completing my undergraduate degree in psychology, I spent several years working within the NHS and the charity sector, before moving into clinical research (Department of Oncology) in 2011. During this tenure I worked as a research assistant and latterly senior data manager, working across a variety of research and clinical systems (including OpenClinica, Achiever Medical and EDGE), gaining valuable experience in data approaches to research and governance. During this time I also completed a MSc in Psychological Research Methods. My knowledge and understanding of NHS systems was furthered during a secondment to the eHospital team, which facilitated the transition of Cambridge University NHS Foundation Trust to a fully electronic medical health record system (EPIC), the first of its kind in the UK.
   
   I joined the Department of Clinical Neurosciences in 2020, bringing a wealth of experience in the collection and management of clinical data from my time in Oncology. I currently work with the clinical and laboratory teams and external stakeholders to design, create and deliver streamlined methods for the prospective collection of high quality clinical and sample data.