Achievements

Faculty's Honors - Fall 2020, Spring 2021, Fall 2021

Winner of HackIllinois 2022, HackTech 2022, Hack WashU 2022, and Girls Hoo Hacks 2022

Recipient of the Simons Undergraduate Research Fellowship 2022-2023 to conduct research in Computational Neuroscience

Relevant Coursework

CS 1332 - Data Structures and Algorithms

CS 2051 - Honors Discrete Math

CS 2110 - Assembly and C

CS 2200 - Intro to Computer Systems and Networks

CS 2340 - Object and Design

CS 3510 - Design and Analysis of Algorithms

CS 3600 - Intro to AI

CS 4641 - Machine Learning

Prototype and evaluate different deep learning models to decode brain signals into finger movements to power a brain-machine interface that aims to restore motor function in people with upper-limb paralysis.

Implement an interactive simulator of a dexterous hand with DeepMind’s MuJoCo, using multi-threading to reduce latency from 15ms to < 0.01ms.

Develop the processing and consumer layers of an in-house node graph pipeline backed by Redis to process raw finger data and command the hand model in real time, with the capability to handle streaming data in less than 5ms intervals.

Developed a solution for caching accessible API versions across all GraphQL schemas to optimize execution time of over 2M API requests per minute, reducing version resolution time by 50%.

Proposed and evaluated approaches to migrate a pagination wrapper class built on top of a 5-year-old legacy code to a publicly supported GraphQL-Ruby model, expected to reduce maintenance overhead.

Implemented an opinionated mixin to guardrail incoming requested API version and enrich response metadata, standardizing this design pattern for all Shopify APIs.

Added 5 schema lint rules to provide compliance checks against Shopify’s API standards and expose consistent endpoints to internal teams and 3rd-party app developers.

Developed plan to migrate an existing computational model of epileptic seizures to a new MATLAB-based library to enable ML capabilities for the study.

Introduced 10+ new features and classes to the new library, added an abstraction layer for model initialization, cleaned up the codebase, and provided up-to-date documentation on GitHub.

Transformed the existing data model to support Gaussian convolution computation of neural dynamics.

Pitched a project idea to automatically interpret lung function tests to physicians using a prototype built in 2 weeks to acquire approval; gathered product requirements; and created an implementation plan.

Developed a cross-platform desktop application from start-to-finish using Python for back-end and JavaFX for front-end with features to perform data scraping/imputation, batch process raw input, generate interpretation output and aggregation statistics.

Scaled the application with self-service capability for doctors to program custom logic for new lung test parameters.

Created product user guide and collected user’s feedback to deliver better user experience, achieving adoption rate of ~80%.

Received a Youth Talent Award from the Chairman of the Pulmonary Medicine Department in October 2019. Oversaw incoming calls, assisted customers with inquiries, and passed messages to appropriate personnel.