Apple

Software Engineering Intern

Seattle, WA

Jun 2022 - Sep 2022

Coming back to Apple for my third internship, in the 2022 summer I interned with the Siri Information Intelligence team. My team was responsible for handling all Siri requests related to the "information domains." This encompasses queries such as weather, sports, music, general knowledge, etc. and not personal queries such as sending messages, making phone calls, setting timers, etc.

Siri has been making a large effort to migrate as much logic on-device as possible, and my work involved building three new features related to personalization. While I am not allowed to talk about the details, I can talk about how this internship contrasted from my previous positions. This role was eye-opening to me in that building the new features required coordination across at least five different teams, who each played a role in the success of the features. Moreover, much of the responsibility was placed upon me to make the significant design decisions since I was the one with the clargest visibility across all the teams.

Curious Cardinals

Computer Science Tutor

Stanford, CA

Jan 2021 - Jun 2022

Since a young age, one of my passions has been teaching. I love passing on the torch and seeing others learn and grow as they pick up new concepts. Curious Cardinals has allowed me to continue my passion through one-on-one computer science tutoring. I helped a high schooler prepare for USACO Silver, and I taught Python fundamentals to middle and high schoolers.

Citadel

Software Engineering Intern

New York, NY

Jun 2021 - Aug 2021

I spent my 2021 summer in New York at Citadel. I redesigned the recovery mechanism between market gateway and market connector nodes on Citadel’s internal trading platform. Although their communication was built on top of TCP, which is itself reliable, their servers were extremely resource-constrained, causing the nodes to drop information within the servers, not over the network. Thus, it was necessary to build in additional redundancies to recover from high-volume situations to make sure every market trade was accounted for.

My work involved devising a failproof mechanism using persistent storage that would allow crashed servers to resume execution in the exact same state. The rebooted servers also had to communicate with other nodes the last information it had received before crashing.

Throughout the summer, I also responded to four urgent production issues, collaborating with traders to push patches as quickly as possible.

Apple

Algorithms R&D Intern | Advanced Computation Group

Portland, OR (remote)

Oct 2020 - Jan 2021

For the 2020 fall quarter, I worked as an Algorithms R&D Intern for a new team at Apple while enrolled in five units at school. The team was investigating applications to take advantage of the LiDAR sensor introduced in the iPhone 12 product line, particularly with regards to photo and video.

One such application was to detect "interesting" motion in Live Photos, which would allow for more intelligently suggestions for Live Photo effects (loop, bounce, or long exposure). Motion in a Live Photo can largely be classified into one of two categories. The first category is motion caused by a moving camera (i.e. photographer had a shaky hand), and this motion results in "uninteresting" Live Photos. The second category is motion caused by subjects moving in the real world (i.e. person doing a cartwheel), which typically results in "interesting" Live Photos.

In order to distinguish between these two types of motion, my project involved quantifying the amount of parallax in a given video. By computing per-pixel parallax values for each frame in a video, I could predict with certain confidence which category of motion was present in a video if any. The computation involved combining depth data from the LiDAR camera with camera translation data from the gyroscopic sensors. Along the way, I implemented a homography estimation algorithm to help identify outliers in parallax computations. To aide in presentations and demos, I developed visual representations using Matplotlib and OpenCV.

Machine Learning Intern | Platform Triage Team

Cupertino, CA (remote)

Jul 2020 - Sep 2020

In the summer of 2020, I worked (remotely) on a machine learning project for Apple. My task was to improve the performance of a model that clusters duplicate crash log files together. The tool is now used internally by triage engineeers to reduce the high volume of manual labor on their plates. The ML pipeline utilizes a Scikit-learn function called AgglomerativeClustering.

After three months of development and testing on live data, I achieved cluster efficiency ARIs of 84-89% for two new panic signatures on three platforms (iOS, macOS Apple Silicon, and macOS Intel).

Quadric

Software Engineering Intern

Burlingame, CA

Jul 2019 - Sep 2019

I spent my summer of 2019 working for Quadric, a fast-paced startup developing a highly parallelized edge-computing chip with a revolutionary hardware architecture.

At Quadric, I spent most of my time implementing the backend for six convolutional neural network layers using a C++ based intermediate language designed for optimal performance on the Quadric Processor. Specifically, I designed the ReLU, ReLU6, Maxpool, Conv 3x3, Global average pool, and Softmax layers; together, they comprised all of the essential components of ResNet-18. My work allowed Quadric to run a full neural network on their hardware for the first time. In designing these layers, I analyzed compile-time optimizations and run-time optimizations, digging down deep into the compiled assembly instructions.

In the latter portion of my internship, I studied the post-training quantization of neural net models, a technique that allows for improved performance during inference through severe reduction of compute while maintaining high accuracy.

Techlab Education

Software Engineering Intern

Saratoga, CA

Jul 2016 - Sep 2017

While a high school student, I interned at Techlab Education, an after-school program teaching a variety of tech skills to middle school and high school students.

As part of my internship, I worked in a four-person team to develop a mobile app that stabilized video footage. Additionally, I instructed groups of 20 high school students in Java, Arduino, Internet of Things, and more.

Project SEED

President

Saratoga, CA

2015 - 2018

Throughout high school, I was a member and eventual president of Project SEED. Our platform involved collecting used cooking oil from local restaurants and selling the oil to recycling plants, which turned it into biodiesel fuel (a renewable, biodegradable fuel). We donated the proceeds - which had reached upwards of $13,000 by 2018 - to underfunded departments at Saratoga High School. For instance, we purchased a 3D printer for our school’s Engineering Department.