Nathan Qiu

Computer Science at UCSB

Focused on security & detection engineering

Nathan Qiu

About

I'm a Computer Science student at UC Santa Barbara interested in cybersecurity, particularly threat and detection engineering, vulnerability research, and building practical tools. I like working on projects end-to-end -- from data pipelines to the interfaces people actually use.

Education

University of California, Santa Barbara
Computer Science, B.S. Santa Barbara, CA
  • GPA: 4.0/4.0
  • Relevant Courses: Data Structures and Algorithms, Computer Architecture, Probability and Applied Statistics, C++ Problem Solving, Intermediate Python, Vector Calculus, Differential Equations, Linear Algebra

Experience

Cybersecurity Intern
AI Institute for Agent-based Cyber Threat Intelligence and Operation Santa Barbara, CA
  • Developed a cybersecurity research framework to analyze vulnerability information leakage in public intrusion detection system (IDS) rules, using an LLM-based adversary to infer targeted CVEs from rule characteristics
  • Generated and evaluated 417 IDS rule modifications to reduce vulnerability disclosure while measuring their impact on detection behavior
  • Validated modified rules against synthetic exploit and benign network traffic, measuring detection degradation and false-positive behavior
  • Found that only 8/417 modifications (1.9%) consistently prevented correct CVE inference across three trials; among modifications that introduced false positives, 10.5% substantially obscured the vulnerability

View project on GitHub → · Open poster full-size (PDF) →

Projects

GrecoCam | Face Detecting Security Camera

  • Built a real-time smart door camera on an NVIDIA Jetson Orin Nano that detects and recognizes visitors using YOLO face detection and Facenet512 embeddings
  • Improved recognition under backlighting and rapid movement through face-region exposure metering, contrast enhancement, confidence-based triggering, and temporal voting

View on GitHub →

GrecoCam running on an NVIDIA Jetson Orin Nano with an attached camera module

ExtendAble | SB Hacks Best Hardware Winner

  • Built a voice-controlled robotic arm that detects and manipulates real-world objects using computer vision
  • Implemented an end-to-end system integrating speech-to-text, LLM-based command parsing, YOLO and OpenCV object detection, and servo-level control via a FastAPI backend
  • Developed a partition-based perception algorithm to estimate object position and execute reliable grasping

View on GitHub → · Watch demo →

ExtendAble robotic arm gripping toward an orange on a table

Chrono | Computer Vision-Based Fitness Progress iOS App

  • Built a mobile app using React Native (Expo) with Supabase for authentication, storage, and user data management
  • Designed a social media platform for lifters that allows friends and communities to share fitness progress photos with one another
  • Developed a computer vision alignment pipeline that detects body position to automatically center daily check-in photos and create clean time-lapse videos displaying progress

Download on App Store →

RedditRadar | Unwrapathon Insights Track Winner

  • Implemented a Reddit product review web app using Reddit comments scraped by Reddit's API
  • Filtered comments through OpenAI API and a Python comment credibility weighting model to produce 95 percent accurate reviews (0-5 stars) and metrics (accessibility, cost, etc.) on any product reviewed by Reddit
  • Built a full-stack system with a Next.js and Tailwind CSS frontend and a FastAPI backend and deployed the app on Vercel

Watch demo →

Skills

Languages: Python, C/C++, JavaScript, TypeScript, SQL, R

Security: Suricata, IDS Rule Analysis, Vulnerability Research, CVE/CWE Analysis, Network Traffic Analysis

ML and Computer Vision: PyTorch, TensorFlow, YOLO, OpenCV

Systems and Tools: Claude Code, Git/GitHub, Linux, PowerShell, NVIDIA Jetson Orin Nano

Backend and Web: FastAPI, Next.js, React, React Native, Supabase

Contact

+1 925-899-6476
nathanrayq@gmail.com
GitHub
LinkedIn
Resume (PDF)