User:Adam Chekhar

I was born in 1993 in London, where I currently live and study. I recall that at an early age I had a fascination with mathematics, before the age of 10 I would spend large amounts of time writing out times tables which would extend well into the thousands. During my mid-teenage years I would sporadically delve (foolishly) into attempts to prove famous unsolved problems such as Goldbach's conjecture.

Similarly, I developed a deep interest in physics when I encountered evidence for mass-energy equivalence, namely pair production and annihilation. This later prompted me to read into general relativity, which quickly lead me to read into Lagrangian mechanics, which in turn lead me to the calculus of variations, the OpenCourseWare made available by MIT, and logic and foundations of mathematics.

As a child I also had a somewhat superficial interest in computer science, writing some (embarrassingly horrific) code in several variants of C. More recently I have been learning several languages in tandem with attempting problems listed by Project Euler.

In my mid-teens I was conflicted between pursuing a career in business (centred around software design) or a career in a medical field (centred around my rapidly growing interest in the human brain).

I ultimately decided to go against my natural disposition for numbers, equations, and algorithms, and settled on studying biomedical science (also known as medical biosciences).

Since my teenage years, I have progressively become obsessed with an ever expanding list of topics in neuroscience and mental health; such as neurodegenerative diseases (such as Alzheimer disease) and neurodevelopmental disorders (such as autism), their aetiology, early diagnostics, and prophylactic treatment.

My current area of interest is computational neuroscience. What can we learn about the human brain from artificial neural networks? How can we improve artificial neural networks and machine learning from studies of the human brain? How can computational methods be used to design pharmaceuticals and study endogenous molecules? How can diagnostic techniques become more robust and economically viable through applications of mathematics and machine learning? Computational neuroscience (seemingly) offers the means of getting closer to the answers.

It is with these (and other) goals in mind that my interest in mathematics, physics, and computer science are promised outlets. What can I learn from logic, recursion theory, statistical physics, and a myriad of other sub-fields, which hold promising applications in computational neuroscience? What can be learned from a community of dedicated individuals such as that which calls Citizendium their home? And what can I give back to that community?