Tracing the Covid-19 Curve

Covid-19 came as a surprise to many of us. We now find ourselves working in very different ways and not in our normal lab environment. Social distancing restrictions are limiting our access to labs and this situation will remain in place for the foreseeable future. These restrictions will not only affect our research progress, milestone delivery and research outputs, but also the completion of postgraduate studies.

So, we would like to introduce a new computational research approach, which will not only have less dependency on the laboratories but will also provide a new dimension to our research capabilities.

The UNSW Materials and Manufacturing Futures Institute is organising a series of virtual townhall workshops and tutorials for Postgraduates and Research Associates. The series will bring to life buzz words such as Data Science, Density-Functional-Theory and Machine Learnings and, by showing some quick and simple demos, we hope it will encourage students and ECRs to pick up some basic programming skills that will bring their data-competencies to a new level.

As Scientists, the one thing we are all trying to do is to figure out how to make the data speak more.

The subject of the first free workshop will be:

You have probably seen enough covid-19 curves that trace daily cases country-by-country and they look fantastic (don’t get me wrong, I don’t mean the numbers but the artistic appearance!). Some even offer interactive tools for you to explore the data and, given that there are 195 countries in the world, and we are nearly 6 months into the pandemic, there is a lot of data out there!

How can people make tracing the curve so informative? How can I attempt to visualize my research data? In this virtual tutorial, we’ll show you how to cover a few basics by using Python:

• Jupyter notebook
• Basic data handling with Python programming
• Plotting static data with Matplotlib, and quick tricks to make your graphs instantly look better!
• Bringing interactive tools with Bokeh package, and finally
• Machine-Learnings – How can you start with just less than ten lines of code!

Who are we dealing with?

Dr Jack Yang (School of Materials Science and Engineering). Jack is a computational material scientist, who applies high-throughput simulations and machine-learnings to understand how materials work!

Does he know how to code?

Yes! Sometimes his brain is going through the code he’s planning to write the next day while sleeping. He claims that he lives for his programming...

I have no prior coding experience or I just don’t like programming! Don’t worry, all you need is a bit of curiosity. Jack used to swear to himself that he will NEVER EVER program again after he did a C course in computational physics as an undergrad. It’s much easier these days with Python!

For more information, please contact Dr. Jianliang (Jack) Yang on  jianliang.yang1@unsw.edu.au