I was recently asked the above question. And it's a totally valid question as SciPy is somewhat outside of what I usually write about (biological topics, sustainable topics). There is a logical connection though, and it has to do with what I do at work.
Building biological entities is difficult because unlike car design, biological entities like to "misbehave". I say misbehave but it actually only means that we don't sufficiently understand microorganisms well enough to model them perfectly.
This is where data science comes in of course. Through collection of large data sets data science and related fields can help us uncover patterns not seen before. these patterns then help make a better yeast model. Better models = faster product development. Faster product development = faster route to a sustainable business = more products with a positive impact.
So there is a link. Simple, right?
Tuesday, July 14, 2015
Sunday, July 12, 2015
Jake Van Der Plaas, one of the main contributors of anything from numpy to scipy, scikit-learn, mpld3 etc., gave the key note speech on the third day of the conference talking about the state of scientific computing in Python. As a side note, Jake is a senior scientist and Director Research at the eSciences at University of Washington. I hear that he is currently involved in developing the data analysis pipeline for the LSST as well.
Thursday, July 9, 2015
Wes McKinney held the key note speech on the second day. This talk was more of a retrospective, personal journey with a view on the future for python and the greater data science community. Interestingly, some of the tools seem to have started a "long time ago" - 2008. Wes talked about 2011 being the year when Pandas development took off again. Thinking about my own history, I joined Amyris in 2011 as part of the Enzymology department which doesn't feel that long ago. Pandas bug/design fixes, and data wrangling capabilities were implemented from June 2011 to July 2012, which is just 3 months before I joined the software engineering department, and that feels really recent.
Wednesday, July 8, 2015
This year I am attending SciPy which is a conference about Scientific Computing using Python organized by Enthought. I am really happy that I chose SciPy this year as the conference to attend because there appears to be a lot of energy at this conference. In the introduction and welcome words by the committee members, it was noted that conference attendance has been increasing from the 300s to 600 over just the past 3 years.