Work Experience

Meta – Software Engineering Intern

Menlo Park, CA • May - August 2022

Worked as a software engineering intern on the Presto team, which develops a database query engine for distributed systems. My work was centred around speeding up Velox, the back-end vectorized database acceleration library that handled execution on worker nodes, and increasing the efficiency of certain types of row filters.

Carnegie Mellon University – 15-210 Head Teaching Assistant

Pittsburgh, PA • January 2022 - May 2024

Served as a head teaching assistant for 15-210: Parallel and Sequential Data Structures and Algorithms, which is the introductory algorithms class at CMU. As head TA, I organized the staff and coordinated logistics. I also made infrastructural changes such as migrating our autograder system and setting up a new office hours queue. I also contributed to content development and homework refinement to maximize student learning. I also led recitations of 30+ students. My biggest contribution to the course was the authorship of over 100 pages of course notes, which further enhanced the student experience.

Carnegie Mellon University – 15-122 Teaching Assistant

Pittsburgh, PA • July - December 2021

Served as a teaching assistant for 15-122: Principles of Imperative Computation, an introductory programming class for first-year CS students at CMU. As a TA, I led weekly labs and recitations to teach fundamentals of the C programming language to 30+ students, and graded over 400 written assignments along with the other TAs every week.

University of Washington – Software Development Intern

Seattle, WA • June - August 2019, June - August 2020

Interned at the University of Washington Applied Physics Lab for two separate summers, working on a team investigating plane-wave ultrasound technologies and their uses in neuroscience.

The first summer, I was tasked with optimizing MATLAB code for reconstructing images from raw ultrasound scan data. By exploiting parallelism and rewriting parts of the MATLAB script in C, I was able to make reconstructions run 20 times faster while maintaining the same image quality. I also investigated and built network-attached storage systems for storing scan data.

The second summer, I ran reconstruction scripts on scan data to generate images, which were then used in publications by my research supervisor. I also created a Python tool which allowed users to click on two points within an image and find the velocity of blood flow across the blood vessel between them from the scan data.