Data Champions Search

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

I am a PhD student studying the compaction of pharmaceutical powders into tablets. My main focus is on computer simulations but I make intensive use of experimental data to parametrise and validate my models. I like combining experimental and computational results as well as developing automated analysis methods. I also have experience working with large data sets and high-performance computing (HPC). Although my current research is on granular matter, my background is mainly in colloidal chemistry.

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.