What is Nirpy Research
In early 2017 I started my first blog on the pages of my consultancy business Instruments & Data Tools. My aim was to be able to explain technical content involving data analysis in an easy and relaxed way. Having spent years of my previous career writing research papers, I felt I needed some fresh air (and some writing practice) with technical content in an informal setting.
I used the blog to muse about image analysis, tomography and near-infrared chemometrics, all of it done using the Python programming language. Short snippets of code to explain ideas in data processing. As my professional spectroscopy activity grew, the blog started to morph into a channel to present chemometrics ideas in Python.
Now, for those of you who are not familiar with the terminology, chemometrics is essentially data science applied to chemical analysis (well, broadly speaking). The thing is chemometrics existed long before data science was even a thing, and practitioners in many fields used regression techniques to make sense of their spectroscopy data decades before everybody would get obsessed with machine learning.
However, as data science and machine learning developed to the level of dominance we see today, chemometrics applications became essentially niche. So these very practitioners – and many learners – have found increasingly difficult to find online resources that would “speak” the chemometrics language in the ocean of data science concept written for computer scientists.
So, quite unexpectedly, my blog became a place where practitioners of good old chemometrics could find a place to read about data science concepts in their language. My blog grew in popularity in this community so that I was struggling to keep up with requests for help, for more data, for more tutorials.
NirPy Research was born out of that struggle.
NirPy Research is an educational space dedicated to Python chemometrics, where we take data science concepts down to the language of spectroscopic science. As the focus is on education and learning, we always keep the language simple and accessible, suitable for beginners and practitioners alike, and the examples quite cogent for the scientific and technical community.
I hope you enjoy reading the posts, you can learn from it and you can spread the knowledge far and wide.
I am a physicist, data scientist and entrepreneur. I started my career in quantum optics, to move towards x-ray optics and synchrotron imaging science. I have been working in fields related to x-ray imaging for about a decade in Germany first, then in Australia. For a list of my research papers, take a look at my Google Scholar.
Since 2015 I have decided to pursue consulting and R&D activity as an entrepreneur.
I currently run Instruments & Data Tools working at the interface of sensors and mobile data acquisitions (with occasional excursions back to optical development).
I am also the founder and CEO of Rubens Technologies, the intelligence system for the fresh fruit industry, which you should definitely check out.