Summary
Work History
Education
Skills
Languages
Timeline
Generic

Emma Vigy

Aiken,SC

Summary

Recent Computer Science graduate with a strong foundation in web development, user interface design, and modern frontend technologies including React, JavaScript, and CSS. Gained hands-on experience through academic projects building responsive, interactive applications using React.js and integrating with APIs and backend services. Skilled in collaborative development, version control with Git, and test-driven workflows. Eager to contribute to innovative frontend solutions with a focus on usability, performance, and clean design.

Work History

Projects

emmavigy.com — Personal Portfolio Website
Personal Project | HTML, CSS, JavaScript, GitHub Pages

  • Designed and deployed a responsive multi-page personal website (Home, Biography, Education, Hobbies) with a custom hamburger navigation system.
  • Styled with consistent typography, imagery, and section layouts to deliver a professional yet modern portfolio presence.
  • Configured custom domain emmavigy.com through Namecheap and GitHub Pages, including DNS/HTTPS setup and live deployment.


Polo Prospect — Full-Stack Horse Marketplace Website
Personal Project | React, Vite, Tailwind CSS, Supabase, GitHub Pages

  • Built a full-stack marketplace for buying and selling polo horses with responsive UI and secure user authentication.
  • Integrated Supabase for authentication, PostgreSQL with row-level security (RLS), and cloud storage for multi-photo uploads.
  • Implemented features for users to create, edit, delete, and mark listings as sold, with carousel-based multi-image display and detailed listing views.
  • Deployed site live at poloprospect.com with GitHub Actions CI/CD and DNS configuration via Namecheap.


Handwritten Digit Recognition & Optimizer Analysis
Personal Project | PyTorch, Python

  • Designed and implemented custom optimizers from scratch (SGD with momentum, Adam, AdamW), validating against PyTorch built-ins.
  • Built and trained both MLP and CNN architectures across MNIST, Fashion-MNIST, and CIFAR-10 datasets to evaluate optimizer behavior.
  • Achieved 97%+ accuracy on MNIST; demonstrated CNNs’ superior performance on more complex datasets.
  • Produced a full experimental pipeline including data preprocessing, visualization, dropout regularization, and reproducibility tools.

Education

Computer Science

University of Wisconsin, Madison
Madison, WI
08-2025

Skills

  • Friendly, positive attitude
  • Teamwork and collaboration
  • Problem-solving
  • Attention to detail

Languages

French
Native or Bilingual

Timeline

Projects

Computer Science

University of Wisconsin, Madison
Emma Vigy