Data Champions Search

I am a Research Associate in the Department of Biochemistry, where I specialise in electron cryo-microscopy (cryo-EM). I use cryo-EM data for the reconstruction and computational modelling of antibiotic transport by bacterial tripartite efflux pumps and related membrane proteins.

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 primarily work with large-scale language datasets, using methods from quantitative and computational social sciences, as well as the digital humanities. I also teach associated research methods, like statistics, data wrangling, and visualization. 

Outside my research, I am an active science communicator, primarily via two websites that I author: Effectiviology (https://effectiviology.com/), where I write about psychology and philosophy that have practical applications, and Solving Procrastination (https://solvingprocrastination.com/), where I write about what procrastination is, why we do it, and how to overcome it. 

As a Data Champion, I focus on the use of quantitative and computational methods for working with data (e.g., for data wrangling and statistical analyses). I also deal with associated topics, like maximizing the impact of research through open research and science communication. 

I am bioinformatician who has been working in Cancer Research UK Cambridge Institute since 2017. I have a background in biology and have experience with HPC, version control, R and python, and confidential data. I work with big volumes of cancer patient data on a daily basis.

Additional areas of expertise:

High Performance Computing (HPC) - cluster.