I began as an Optical Engineering undergraduate 🔭, fully convinced I’d spend my life bending light to my will. Still, somewhere between Zemax optics design and too many hours staring at interferograms, I got hooked on data processing. The logic was simple: landing a job in optics looked tough, and data science felt like the shiny new frontier. So I sprinted toward it with questionable sanity and a lot of enthusiasm.
I set out to become a Data Scientist 📈, determined to predict the future with neat algorithms ✨. Then reality introduced me to deployment. That single word rerouted my life. Before I knew it, I was wrestling backend frameworks 💻, fixing pipelines, and becoming an accidental developer 🛠️. Apparently I enjoy suffering in multiple dimensions.
Eventually, monotony won the battle against my attention span, and my path twisted again. Now I’m a PhD student 🎓 in Optical Engineering, right back where the light beams live. It looks chaotic, but it isn’t. My old optical foundation and my newer machine-learning obsession finally teamed up.
These days, I use deep learning to push the limits of optical design, essentially getting photons to reveal more through my models 👑. Whether that’s brilliance or a sign of long-term commitment issues is up for debate, but the skills really do blend together 🤝.
