Grace Tao
Passionate Full Stack & Deep Learning Engineer with expertise in scalable software development and GPU optimization. Currently pursuing MS in Computer Science at Stevens Institute of Technology while conducting cutting-edge research in Graph Neural Networks.
Developing AI and Web systems
About Me
Passionate about leveraging cutting-edge technology to solve complex problems in deep learning and software development
Research Publication
“DR-CircuitGNN: Training Acceleration of Heterogeneous Circuit Graph Neural Network on GPUs”
Published in ICS 2025 - Achieved 4.8× training speedup through custom CUDA kernel optimization
Education
Master of Science in Computer Science
Stevens Institute of Technology
Bachelor of Engineering in New Media Technology
University of Shanghai for Science and Technology
Recent Role
Deep Learning Research Assistant
Stevens Institute of Technology
Leading GPU optimization research for Circuit Graph Neural Networks, developing custom CUDA kernels, and publishing cutting-edge research in top-tier conferences.
Featured Projects
A collection of projects that showcase my skills in full-stack development, from concept to deployment.
DR-CircuitGNN: GPU-Accelerated Circuit Graph Neural Network
Cutting-edge research project optimizing Circuit Graph Neural Networks with custom CUDA kernels, achieving 4.8× training speedup.
Key Features:
- 4.8× training speedup achieved
- Custom CUDA kernel optimization
Travel Companion Web Application
A comprehensive travel planning and companion web application built with modern web technologies.
Key Features:
- Travel planning interface
- Companion matching system
ConHub Web Application
A modern social media platform for discovering conventions, showcasing your art and hobbies, and connecting with like-minded communities.
Key Features:
- Create, publish, and manage convention details
- Engage with fans via posts and updates
Publication Display Web Application
A professional ASP.NET web application designed to showcase academic research, publications, and team achievements. Comprehensive portal for research dissemination and academic collaboration.
Key Features:
- User Authentication System
- Research Publication Showcase
Pipeline Video Recognition & Defect Detection System
Complete end-to-end video recognition pipeline with real-time defect detection capabilities. Features deep learning-based ResNet18 architecture, CUDA acceleration, and comprehensive ML workflow from dataset processing to deployment.
Key Features:
- 82.4% detection accuracy with ResNet18
- Real-time video processing & defect detection
Technical Skills
Comprehensive expertise across the full technology stack, from low-level GPU optimization to high-level application development
Programming Languages
AI/ML Technologies
Backend & Cloud
Tools & Optimization
Expertise Overview
My Professional Journey
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Grace Tao
Full Stack & Deep Learning Engineer
Experience
Deep Learning Research Assistant
Stevens Institute of Technology
Sep 2024 – Present
Full Stack & Deep Learning Engineer
EarthView Image Inc.
Jul 2023 – Jun 2024
Education
Master of Science in Computer Science
Stevens Institute of Technology
Sep 2024 – May 2026
Download Resume
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Last updated: August 2025 • PDF Format • 1 page
Quick Overview
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