ABOUT

My name is Daniel Minaeian. I am currently a student studying biology. That being said, my interests do not lie solely within the field of biology. For a large portion of my life, all I would think about were computers and, quite frankly, any other technology that relates to computers (turns out there are a lot of them!). As a result, I also enjoy many forms of coding. In fact, the first time I ever encountered coding was when I was 5 years old where I learned how to create simple HTML web pages. From there, I moved on to learning about computer hardware and also started to learn to code in C and C++. Today, I mostly code in C++ and Python (alongside HTML, CSS and a sprinkle of JavaScript). So how did I end up studying biology? The answer is pretty simple: it turns out that I really loved biology as well. As my studies progress, I hope to bring computer technology and biology closer together. The current topics I am following are artificial intelligence and robotics and their medical applications.


I also love to make music. You can check out some of my work on the “Projects” page.



Oh yeah, I’m also a huge football (soccer) fan.






Music

Coding

YOUTUBE




SOUNDCLOUD





I first started coding when I was about 5 years old. My work consisted mostly of simple HTML web pages. Some years later, I started to learn C and C++ which eventually led to Python, CSS and some JavaScript. My main area of interest is artificial intelligence and its possible integration with biology. I've coded two genetic algorithms: one in C++ and one in Python.

The genetic algorithm coded in C++ is a program that creates the amino acid sequence of a protein based off of parameters given to the program. You can check out the video below:

The genetic algorithm coded in Python is a program that randomly generates a maze (difficulty can be adjusted) and the program tries to solve the maze using a genetic algorithm. You can see the program in action in the gif below:

Soon after I completed the program I realized how inefficient the algorithm is for mazes. So I decided to use a slightly modified A* algorithm instead:

Not the most efficient path, but infinitely faster than the genetic algorithm. I plan to combine the genetic algorithm with the A* algorithm in the hope that the program will find the most efficient route through the maze.