I often describe my first independent research project as something I stumbled into rather than set out for. It began not with a grand plan, but with curiosity and a small act of following up. During a university hackathon, I was working on a fish detection tool for farmers when I crossed paths with one of my university's grad student—now an assistant professor—who was struggling with the application of some machine learning algorithms. Once he explained the challenge, I couldn’t resist diving deeper into his thesis problem.That four-week collaboration opened the academic door for me—both into the world of high-dimensional data challenges and to Prof. Dilip Kumar Sharma, who would later become my mentor.

When I eventually designed my own study with professor, I wasn’t just motivated by algorithms or results. What kept me going was the thrill of trying to bring structure to the dataset's complexity—how to balance accuracy with interpretability, speed with reliability— that question kept me going. I had only modest coding and ML skills when I began, but this project pushed me to grow. Nights of debugging, endless revisions of the thesis, and all those sleepless nights shaped not just my research, but my patience and resilience.

Looking back, the publication is just a small part of the journey that still lies ahead of me. What truly mattered was learning how to ask the right questions and how to keep moving despite setbacks. It would have been easy to give up—it wasn’t part of my curriculum—but I carried on simply for the sake of learning and to answer the questions I asked before I started. And in the end, that made all the difference.