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Developing
👨‍🍳
Developing
22 followers · 45 following

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Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw

Achievements

Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw

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thevedantmodi/README.md

Hi there 👋

I am Vedant Modi, an end-to-end developer, energetic team player, and passionate builder of large-scale, impactful products. As I build software, I adopt new problem-solving approaches and technologies. Right now, I'm focusing on building applications centered on distributed systems, machine learning, and low-level computing. With these skills, I build real-world, scalable solutions to complex problems.

I'm a recent alumnus of Tufts University, where I studied computer science and mathematics. I enjoy traveling to new places and love documenting those experiences through photos and videos.

I'm an incoming software engineer at JPMorganChase, starting in the latter half of 2026.

  • For my previous work in low-level programming, please visit my work from COMP40 at Tufts University.
  • For my notes in my theory courses, please visit my notes page from COMP160 at Tufts University.
  • For some machine learning work, please visit some projects about movie recommendations or reading level classification.
  • 📫 How to reach me: vedantmodi.com, or vedant[at]vedantmodi[dot]com

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  1. photo-maps photo-maps Public

    A personal photo gallery that visualizes over 500 images by year and location

    TypeScript

  2. framelog framelog Public

    Automatic photo import, deduplication, XMP versioning, and Lightroom sync pipeline for Mac.

    Go

  3. stand-clear stand-clear Public

    A simple REST API for New York City's MTA subway arrivals

    Go

  4. vbt vbt Public

    Vedant's Budgeting Tool

    TypeScript

  5. stand-clear-board stand-clear-board Public

    MTA arrivals board. Final project for Embedded Systems at Tufts University, Spring 2026.

    C

  6. movie-recommendations movie-recommendations Public

    Files and report for a series of LF models that recommend movies from movielens100k database to users

    Jupyter Notebook