Dual-degree student at UVA studying Computer Engineering and Mathematics — building at the intersection of ML research, systems engineering, and real-world impact.
I'm a Computer Engineering and Mathematics student at the University of Virginia (GPA 3.76, Dean's List), with a minor in Philosophy and a year abroad at the University of Hong Kong. I'm drawn to work that sits at the intersection of technical rigor and real-world impact.
I've done ML research predicting material band gap properties using neural networks, built satellite testing infrastructure at ST Engineering iDirect, and shipped a first-place laser weed-removal system in an international engineering competition.
Incoming Software Engineering Intern at Appian this summer — always looking for the next hard problem worth solving with elegance and intention.
Designed and built an autonomous weed removal system under the theme "Smart and Sustainable Engineering." Used YOLOv8 for real-time object detection to identify weeds, then drove an Arduino-controlled servo motor system to target and eliminate them with a laser — calibrated for precise coordinate mapping from camera frame to physical space. Presented to a panel of industry experts alongside a multicultural team of 4 from Thailand and Hong Kong.
Comparative experiments evaluating training dynamics of gradient descent and diffusion-based methods across MLPs and 1D CNNs on a synthetic S-shaped dataset. Investigated model depth, layer width, and activation functions systematically.
Led all software initiatives for a mobile app that detects parasite eggs using a Roboflow object detection model. Built a RESTful API with Python Flask, communicated directly with the client to gather requirements, and delivered the final product demo.
Built at the UVA Women in CS Hackathon — a mobile app that lets users upload photos from their camera roll, detects foreign language text via OCR, and translates it to English in real time.
Whether you have a project in mind, a role to fill, or just want to connect — I'm always open to a conversation.