Tell us a bit about yourself and your academic journey.
I started my academic journey studying Bioinformatics during my undergrad, where I developed a strong interest in the intersection of biology and technology. This passion led me to Berkeley’s MSSE Master’s program, where I deepened my technical expertise and gained hands-on experience working part time at Berkeley’s High-Performance Computing (HPC) Center. I simultaneously interned as an SWE/ML developer at Merck, tackling complex problems in pharma. After graduation I tried by hand in entrepreneurship, briefly starting a company. Currently, I’m continuing my tech journey at Google, building on my background in software engineering and machine learning.
Why did you choose MSSE?
I chose the MSSE program because I wanted to sharpen my software engineering, data science, and machine learning skills in a structured, rigorous environment. Additionally, Berkeley offered a unique opportunity to remain connected to the biotech space. The program’s balance of advanced technical training and practical biotech applications made it an ideal choice for my career goals.
What inspired your passion for scientific computing, and how has this interest influenced your studies in software engineering?
My passion for scientific computing sparked from a deep fascination with solving complex, real-world problems through software, blending analytical thinking with creativity. This interest naturally guided me towards software engineering, where I found the perfect balance between computational rigor and practical innovation. At Berkeley’s MSSE program, I sought out opportunities to tackle computational challenges, refining my technical skills while learning from peers and faculty who shared my enthusiasm. Working at Berkeley’s research facilities further enriched my experience, enabling me to apply theory directly to impactful projects. Scientific computing taught me to approach software engineering problems methodically yet creatively, shaping the way I solve problems and collaborate with others. Ultimately, it inspired me to keep pushing boundaries, merging curiosity with code.
Can you share specific projects at Google where you’ve applied your expertise in scientific computing?
At Google, my role on the YouTube team has allowed me to apply my scientific computing background directly from analyzing and optimizing recommendation models to developing data-driven experiments and utilizing large-scale computational techniques. Additionally I’ve been able to work on the robust distributed infrastructure that makes all this happen. This experience has been rewarding, as it combines analytical rigor with real-world impact, influencing how millions discover and interact with content every day.
What advice would you give yourself before you started the MSSE program?
Before starting the Masters of Software and Molecular Science (MSSE) program, I’d tell myself to fully embrace the interdisciplinary nature of the curriculum—where software meets molecular biology—and approach every course with genuine curiosity. Remember that your peers are some of your greatest resources, so build meaningful connections early and collaborate whenever possible. Seek mentorship from faculty; their insights will guide you through challenging concepts and open doors to exciting research opportunities. Take full advantage of Berkeley’s resources and pursue meaningful work experiences on campus, as they’ll greatly enhance your practical skills. Lastly, be patient with yourself through challenging moments—every difficulty is shaping you into a more thoughtful and innovative scientist. Enjoy the journey, stay curious, and trust that each experience is bringing you closer to your goals.