After 9 months of silence, I am back again to my weblog. It is hard to explain why I was not around in one post, since past few months were full of ups and downs at least for me. To be short, after many years being in academia, either as a student or researcher, I started a position as a R&D in one of my favorite topics on the intersection of mathematics and computation while working with real world examples, i.e., as a machine learning data scientist. That by itself is a good reason to be away for a few months. However, in my case this was not the only thing.
The other thing that I have realized is the fact that, after being away for a few months, it is hard to come back, as there are many things to say and you basically don’t know where to start. To choose one particular out of many, I just quickly write about why I partially left academia, at least for the moment.
First of all, it is almost clear to everyone who is already engaged in academic activities that the whole subject of “academic interest” does no longer exist. By academic interest, I do not mean a useless scenario that people came up these days to publish a few more papers. No, I really mean to spend time and energy on something for the sake of curiosity. I can’t say that there is no one doing that, but I can certainly say that the new generation of scientists, are either businessmen or engineers. (Nothing wrong is with being businessman/engineer, just they should practically be different from scientists, and now they merged somehow. )
Second, again those who have been involved in academic setting are realizing that, for many reasons, creativity is kind of discouraged. Most of the times finding a more creative solution is not desired. During these many years, I came across many important subjects worth studying, which were dismissed because they considered HARD to do in a few months or seemed irrelevant.
Thirdly, computer science in north america has cast a shadow on many professions, and academia is not excluded. Hence, everybody tries to codify some mathematical problems and in the best case scenario bring it close to experiments. I should say that, I do not discourage this activity, the point is theoretical studies should be different from computational studies, but theory almost cease to exist these days. Finally, not to mention the fact that, academic fields are tightly narrowed these days that even in one particular fields, it is very hard to move around. Part of it is due to the fast growth of science, but it is mostly due to the crowdedness of the environment! Indeed, this list goes on, but I guess these are the main reasons.
Putting altogether, I realized for people like me who are interested in wide breadth of research on different aspects of life, data science seems a way to go. I reserve the right for me to change the above statement as time goes on!