Shifting Roads, A New Milestone From Data Science Internship to Quantum Computing
The road is still too faraway, anyway
Finally, got my first job
Two months ago, I announced starting-up my career as an intern in data in this linkedin post. It got highest views and comments I had ever on any social media platform. For the past year, Not only I have been studying traditional statistics and data-science but also highly intriguing subjects like cognitive science and computational emotions. It is really so curious when computing take the role of mathematical modeling in characterizing some phenomena accurately, As is the case in cognitive science. Whatever your expertise-knowledge is, It is worth to check how AI transformed our understanding of the human’s mind. Anyway, After reaching this great milestone as an intern in the sexiest job of the 21st century, I announce here that I shall shift my roads to a totally different field of study, yet still mind-blowing and disruptive. Namely, Quantum Computing.
What are you going to do with that weird quantum computing?
The critical difference here is that I shall be alike a mathematician than being alike an empiricist. Data science is based on experimentation in which we hypothesize some model, falsify it up against data, then polish our model back again. However, Note that, many researchers consider data science as a forth paradigm of science. Anyway, As a computer scientist, quantum computing for me is not an engineering endeavor in which I strive to build a real-life wise feasible solution. Rather, It is a pure math theorem. Validity of math-theorems are based on logic not empirical experimentation as is the case in data science. Particularly, I hope to delve into the fundamental theorems like computational complexity theory and information theory. For instance, are there problems solved efficiently by a quantum computer but not efficiently solved by a traditional computer? That is a hot research area of study called quantum supremacy, a term coined by the legend John Preskill.
As Richard Feynman said, the more fundamental, the more interesting it is. Besides the pure mathematical elegance, The curiosity of working out a fundamental pure math theorem is alike setting-out the ground for an engine which would disrupt the whole civilization. Obviously, It is hilariously challenging. Usually, It does not happen that a fantasy like that occur. Even if I knew priori that I would achieve such a fantasy, The journey of pursuing and solving a fundamental problem, in its own rights is worth taking. I still love cognitive science. Even-though Bayesian models in cognition provide a good falsifiable model, computational complexity and information theory elegance are far more captivating. By the way, There is a hot research intersection between quantum computing and cognitive science. However, I am not sure exactly whether I shall contribute to it.
Why shifting from data science?
Besides cognitive science curiosity, My work in data science had a clear goal for me which is to achieve something and start-up my career. Someone whom I highly appreciate advised me not to be an ideast but rather to have an impact. Exploring highly ambitious topics without producing an achievement like a research paper or a piece of code is a pitfall I admit I had fallen in. I realized we learn best when we pick-up the simplest possible problem, solve it to the end, then iterate picking-up a tougher one. Pushing into the end of someone’s ambition and exploring totally inaccessible problems is not fruitful at all. Even if programming is not what I am ultimately aspiring for, Achieving something is a step. Now that I got my first job and made couple of programming projects, I am more ready to tackle tougher challenges.
(laugh..) As if quantum computing going to gain you money
Obviously, It is murderously challenging to gain funding in a field of studies like quantum computing, computational complexity theory, information theory, ..etc. However, I believe I could produce an achievement which paves the road to my end ambition. I hope to do standard programming job but from the perspective of math and algorithms complexity. Code profiling and optimization seem for me the most promising candidates for the next phase of my life. Code profiling is a common term in software engineering which means analyzing the program in terms of time and memory space it consumes. It aims to spot the parts of code which are the most expensive computationally. Afterward, An algorithmist aids programmers and software engineering in producing a more efficient code. While that has nothing to do with pure math, a part-time job in it alongside a hobbyist pure-math based projects might allow me to gain a reasonable fund in academia. Cryptography and cryptocurrencies investing_ might be good alternatives, as well.
So, What is that pure-math hobbyist project I shall be working on? Most probably, It shall be a new proof-based programming-technique for some category of problems. You might think of new problems and techniques introduced in competitive programming contests like ACM’s prestigious ICPC. In addition, I guess it shall be based on a quantum computing simulator, like LIQUi simulator made by Microsoft and Quantum Computing Challenge made by Topcoder. However, as I look at my past and how phenomenally I changed up my mind, I lose any confidence in ensuring you how my project shall look like.