I am a senior at Columbia University studying computer science and physics. I am seeking full-time roles in machine learning engineering.

I have deep expertise in applied and theoretical machine learning with particular emphasis on deep learning, statistical machine learning, and algorithm design. I currently perform research on deep metric learning under the supervision of Prof. Nakul Verma. I am also a teaching assistant for COMS 4771 Machine Learning, Columbia’s graduate-level introduction to machine learning. See, for instance, a problem I wrote on random forest classifiers.

Most recently, I was a machine learning intern at Oleria Security. There, I was part of a three-person team that brought AccessGPT, a novel security-oriented GPT, from a limited scope proof of concept to alpha release.

Previously, I was part of the Materials Science Division at Lawrence Livermore National Laboratory, where I utilized a variety of image and signal processing techniques to understand the turbulent physical processes that govern laser drilling. That work was published in APL. I’ve also worked on condensed matter physics research in Columbia’s Pasupathy Lab and volumetric light-sheet imaging at the Laboratory for Functional Optical Imaging at Columbia’s Zuckerman Mind Brain Behavior Institute.

I graduated from Interlake High School in Bellevue, WA in 2021. During my senior year, I interned with Prof. Tom Quinn at the University of Washington’s Department of Astronomy, where I worked on particle simulation codes. I was also heavily involved in policy debate, for which I was squad captain my senior year.

Some of my other interests include badminton, science outreach, my cat, philosophy, writing (both of the creative and nonfiction sort), cookies (both consuming and creating), and slowly improving my Chinese fluency.

Publications

S. Gorgannejad, A. A. Martin, and B. Chen et. al. In situ x-ray imaging to understand subsurface behavior during continuous wave laser drilling. In Applied Physics Letters, 2024. doi.org/10.1063/5.0207380

Fun facts

• My :Fischer number is 2.
• I once ran a marathon on a month of training … it was painful but absolutely worth it.
• I love solving and creating all sorts of logic puzzles. I co-authored the Fermi Questions test for Columbia Science Olympiad, which you can try for yourself here (solutions here.)

Contact me

The best way to reach me is via email: bc2924@columbia.edu. Social media also works great! Please do not hesitate to reach out.

:x fischer

The “Fischer Number” is an idea invented by Christian Hesse based on the famous “six degrees of separation” concept. Bobby Fischer was the 11th World Chess Champion and considered by many as the greatest chess player of all time. One’s “Fischer number” is calculated as such: Bobby Fischer himself has Fischer number 0. If you have beaten Bobby Fischer in a tournament, your Fischer number is 1. If you have beaten someone with a Fischer number 1, your Fischer number is 2, etc. Some famous chess players’ Fischer numbers are as follows: Garry Kasparov, 2; Magnus Carlsen, 3; Deep Blue, 3; etc.

My Fischer number is 2, due to an extremely fortune series of circumstances. When I was young, I used to play at the Seattle Chess Club. One of the stalwarts of this little club was a man named Viktor Pupols. At this point he clearly played only for fun, but still retained a rating above master strength. In 2016, I managed to beat him in a tournament game.

It turns out that Pupols himself in fact beat Bobby Fischer, in the US Junior Championship 1955 (some sixty years prior). This was supposedly one of only two games Fischer ever lost on time.