Why Cornell?
Cornell has such an expansive community both inside and outside of the classroom. Whether you want to get involved in a research laboratory, become a full-fledged member of a club sports team, or simply find a social club to relax with, Cornell has an unparalleled flexibility and ability to meet your every interest.
Why ORIE?
ORIE is a practical, industry-oriented major with rich, deep roots in theory that allows one to delve endlessly into the inner workings of their studies. In this manner, I have come to cherish ORIE for its unique position to push the frontiers of human knowledge while affecting tangible changes to the communities and people I love.
What have you learned while pursuing this major?
Practically, I have learned so many new, diverse subjects - from mathematical programming and financial engineering to data science and beyond, I have gotten the chance to learn an innumerable amount of technical fields. Non-technically, I have developed professional skills while conducting research and undertaking semester-long projects that will inevitably prove invaluable in my future endeavors.
Any advice for students considering ORIE?
Don't be afraid to explore new subjects. ORIE offers such a breadth of topics to explore that sticking to a single subject, no matter how much you may love it, can only offer a relatively insular view of the field, and, by extension, the world. Whether it's taking a chance with optimization, data science, or any other number of subjects, don't be afraid and be willing to try new things!
Any interests outside of school work?
I play soccer at a competitive level, and have recently gotten into running half-marathons. I also love playing and practicing the piano as a way to challenge myself outside of academics.
What stands out to you about your Cornell ORIE experience?
The flexibility of the major allowed me to explore a wide array of topics I would have otherwise not gotten the chance to experience. I particularly enjoyed Cornell's ORIE flavored approach to machine learning - by viewing ML through an optimization, data science, and mathematical-based lens, I was able to develop a more holistic and appreciative view of the field.
What's next for you?
I plan on starting my PhD in Statistics at UPenn this coming fall. Eventually, I hope to become the principal investigator of a governmental, industrial, or academic lab, where I can help shape and define the role of machine learning in today's increasingly AI driven world.
Favorite quote that helps inspire you in your work/life?
"Simplicity is the final achievement." - Frederic Chopin