California Institute of Technology

In my junior year, our school's Robotics Club decided to enter the annual Robotics Challenge. From videos of past competitions, it was clear that robots could achieve some pretty amazing things, and we were eager to try our hand. I got the task of programming our robot's pathfinding, which I thought would be a cool challenge.

Initial tests, however, were not promising. Our robot, which we affectionately dubbed 'Rover', seemed to have a mind of its own, often getting lost or stuck in corners. This wasn't what I expected, and instead of feeling defeated, I got really curious. Why was our algorithm struggling?

After some deep dives online and discussions with our club advisor, I stumbled upon the A* algorithm. It was touted as one of the best for pathfinding. Many late nights were spent poring over code, making adjustments, and running trial after trial.

The moment 'Rover' smoothly navigated our test maze was unforgettable. Beyond just the success, this experience opened my eyes to how vast and complex robotics can be. It also sparked a newfound interest in AI and how machines can learn and adapt.

In a chemistry lab during sophomore year, our assignment was to synthesize aspirin. The process, on paper, seemed pretty direct, but science in practice can sometimes be unpredictable. My first result wasn't the expected pure white but had an off-white hue.

Rather than just accepting it, I was determined to understand why. Had I missed a step or mis-measured an ingredient? I turned to additional resources, beyond our classroom's scope, and delved into the intricacies of the synthesis process. I found out that there are many variables at play, from temperature control to precise measurements.

Armed with new knowledge, I approached the lab again. With more attention to detail and a better understanding of the reactions, my second attempt was markedly improved.

This wasn't just a lesson in making aspirin; it underscored how deep and layered even seemingly simple reactions can be. It made me appreciate the precision required in chemistry, especially when thinking about its implications in something as important as drug development.