Portfolio

Scrapp - Waste Classifier

Won Fourth Place in the Congressional App Challenge against ~12,682 teams nationwide
Developed an app to classify waste and eliminate confusion when disposing of items - live at scrapp.app
The user photographs or uploads an image of an item, receives structured disposal guidance (material, disposal route, confidence, and caveats), and finds nearby drop-off locations on an interactive map - including ~690 curated battery drop-off sites across Southern California
Built the backend and AI: a Flask API using GPT-4o-mini vision classification, with a fine-tuned YOLO (You Only Look Once) object detection model available as an additional detector
The frontend is a Next.js app installable as a mobile-first PWA (and can be viewed on screens of any size)
Featured in the San Diego Union-Tribune

Research conducted with Prof. Hajar Homayouni, San Diego State University

Compared Symmetric vs. Asymmetric Cross-Modal Attention architectures on the VQA v2 benchmark, using frozen & unfrozen CLIP-L/14 and RoBERTa encoders with a trainable ~307M-parameter fusion module
Symmetric architecture reached ~72% validation accuracy vs. ~67% for the asymmetric architecture; the asymmetric model’s training accuracy kept climbing (~71%) while its validation accuracy plateaued, a widening train/val gap pointing to overfitting
Diagnosed a structural gradient imbalance behind the gap and proposed fixes (differential learning rates, extended epochs, warm-starting)
Built and managed the full GCP training pipeline (L4/A100 VMs, GCS data pipeline, Papermill + tmux for headless runs)
Ranked in the top 150 out of 550 teams (top ~27%) on the VQA Challenge leaderboard on EvalAI
Paper submitted to WACV 2027 (IEEE/CVF Winter Conference on Applications of Computer Vision, ICORE A-ranked) - currently under review

Independent Research Project

Classifying Marine Mammals using Convolutional Neural Networks

Authored under the mentorship of Arpit Jasapara of UCLA (a Masters student researcher), and discusses an EfficientNetB5 + ArcFace ensemble as well as several other models. These models were then used to classify individual whales and dolphins in the Happywhale dataset on Kaggle and achieved a rank in the top 11%. An ensemble of models presented in the manuscript ranked in the top 5% out of 5 thousand teams on Kaggle. After undergoing a 3-month peer review proccess, the manuscript has been published in the National High School Journal of Science.

CyberAegis - Cybersecurity Competitions

Captain, Linux lead, and MVP of a six-person team competing in AFA’s CyberPatriot and the SoCal Cyber Cup, two of the nation’s leading high school cybersecurity competitions.

Placed within the top 30 of 6,000+ teams for five consecutive years; CyberPatriot XV National Finalist (1st in Networking, 2nd Overall out of 6,000+ teams)
Won first place at the SoCal Cyber Cup (out of 200 teams) and placed in the top five three times, defending a live server against attacks from security professionals in the finals
Applied cryptography, reverse engineering, password cracking, log analysis, and web app exploitation in CTF-style rounds
Built practice Linux virtual machines and taught cybersecurity fundamentals to 120+ peers; also taught cybersecurity basics to elementary schoolers through Del Norte High’s CyberCEO outreach program

AI-Assisted Oral Health Scanner (Provisional Patent)

Independently invented and prototyped an at-home oral health scanner that screens for tooth decay and gum disease without needing an X-ray.

Sole inventor on a provisional patent filed with the United States Patent and Trademark Office
Designed a 3D-printable housing with ultraviolet fluorescent lighting, paired with a camera and a custom per-tooth AI detection model

Open Coding Society | Project Lead & Scrum Master

As Project Lead and Scrum Master for Del Norte High’s Computer Science program, directed and contributed to several full-stack projects using Agile methodologies.

Directed development of a facial-recognition bathroom pass system for student safety, and facilitated the build of a student-teacher chat platform now used daily by 100+ students
Led a team of 6 building iMop: backend (Flask) with machine learning models predicting areas of San Diego needing maintenance, and frontend (Jekyll + Tailwind) displaying the results
In the program’s CS Capstone, hosted AI models to expand equitable access to coding education and presented progress to industry professionals for feedback
Organized work with a Kanban board

Served as deployment admin for a team of 6 during the development of a full-stack social media application for AP Computer Science.

Developed a full-stack application with JWT authentication, features to gain insights on users’ interests, and a deployed backend using AWS.
Managed user account data and information in SQL databases, and deployed a Jinja site that used session tokens for authentication.
Used Agile Methodologies, maintained a Kanban board, a Frontend, and a Backend.

UC Irvine x Gifted and Talented Institute: Game Science Entertainment Technology

Learned about Gaming Computer Science, Game-based learning, and Game Research
Participated in lectures led by UCI professors and industry professionals
Developed a game in a group of 4 and pitched it to potential investors and judges

FlipGun Project and Pitch

Leadership & Activities

Beyond software and research:

Eagle Scout, Troop 685 - As Assistant Senior Patrol Leader, led weekly troop meetings for 120+ scouts and organized logistics for multi-day camping trips. For my Eagle Scout project, led a team of three to build a park reservation and newsletter app for the Del Sur Community HOA, replacing a manual, email-based booking process
Co-founder, Del Norte AI Club - Grew the club from 8 to 20+ members; taught machine learning fundamentals (regression, image classification) through weekly challenges like Titanic survival and NBA game predictions
USACO Silver Division (2025) - Solved algorithmic problems in timed Python contests, self-taught via YouTube and the USACO Guide