Growing up in a small town in Iran, where construction was the top-notch industry, and civil engineers were the epitome of building and creating, civil engineering was a natural choice for me when I entered college. However, a serendipitous encounter with Python during my first year opened my eyes to a different kind of building — not with concrete, but with code. Unlike the Fortran courses that preceded mine, Python’s simplicity and the engaging challenge of making a turtle move across the screen sparked a joy in programming that has stayed with me.

My first software engineering role was an internship in a Civil Engineering company building an Intelligent Bidding Proposal (IBP) software for automated generation of bidding proposal documents using C#, Telerik, and MySQL. It took a summer and a junior software engineering intern to make an ordeal process in an organization into an enjoyable one. That was the moment when I learned “You can poke life, and that if you push something in, something will pop out the other side.” I have been poking and building ever since, one line of code at a time.

As I explored the computing world further, my interests evolved. I discovered a passion for automation. The concept that a few thousand lines of source code has the potential to fully automate a task that might have taken a human lifetime a century ago was mesmerizing. From my perspective, the most elegant software (and I tend to use the word “software” in its broadest sense) operates invisibly in the background. It streamlines mundane or repetitive tasks so seamlessly that it becomes challenging to envision working without its assistance.

I find myself drawn to the unique blend of abstraction and practicality that software engineering offers. It struck me as the perfect balance that has ever since resonated with me. Besides this, the open-source culture is incredibly empowering, allowing one to collaborate with brilliant minds to solve complex problems. It’s a continuous learning journey, and I find great satisfaction in the process.

I am excited about the potential of AI and machine learning to solve complex problems in the next few years. I see machine learning as a new form of software where the programmer doesn’t need to implement logic manually but learns it from data. That is why I pursued my Master’s degree in Computer Engineering specializing in Computer Vision, Machine Learning, and Algorithms. Throughout my career, I have experienced first-hand how tricky and overwhelming the process of crafting software or extracting insight from data that solves a business problem can be. I have developed a genuine appreciation for the agile methodologies emphasizing teamwork, communication, and incremental progress.