What is this webapp for?
This webapp was built by me to host my various data science side projects.
It was a hot and boring Saturday when I suddenly realised that all my side projects are wasted sitting in my hard drive. Why not build a webpage/webapp and share it with the World? That was the beginning of this webapp!
I am realistic about this: I realise no one outside of my friends, family and fellow researchers will probably ever stumble onto this webpage. Nevertheless, I felt creating this was probably a more productive (and fun) way to spend my weekends then just sitting there watching telly. Hopefully this will also push me to do more data science/machine learning side projects!
If, by some freak accident, you are not one of my friends or family and have stumbled onto this webpage: Welcome! Stay a while! Drop me an email to say "Hi". If you are here from reading my publications, please cite me! (shameless advertising ;))
Who am I?
I am a data scientists working in De Beers Group, pricing & development unit. I am the first data scientist in the business unit and is the spearhead of an initiative to bring data driven solutions to the company. I have started, lead and finished multiple data science projects in my time at De Beers including:
- Prediction of refused goods
- Diamond price prediction
- Automated sentiment index (NLP)
- Data Science webapplication
Previously, I was a PhD student, then postdoctoral researcher, then visiting researcher who worked in the Centre for Atmospheric Sciences (Department of Chemistry), University of Cambridge. My main interests are climate dynamics, data science and machine learning. My main research topics include applying machine learning to predict tropical ozone changes, investigating the impact of El Niño Southern Oscillation (ENSO) on the Amundsen sea low (ASL) and applying machine learning techniques to predict the Northern annular mode. Further details can be found here.
