Picture of Aayush Agnihotri

Hey, I'm Aayush.


About Me

I am currently a student at Cornell University, pursuing a Master of Engineering degree in Computer Science. I have experience in software engineering, primarily in full stack development and machine learning.


I aim to leverage technology and data to build innovative products that help people.


Aside from school and programming, I enjoy working out at the gym 🏋️, listening to music 🎵, or playing soccer ⚽.

Projects

AI Dev Image

AI Dev

TypeScript
React
Next.js
MongoDB
Firebase
Docker
GCP

An internal AI tool and platform enabling AI features and interactions with a finetuned organizational model coupled with RAG.

Eatery Image

Eatery

Python
Django
PostgreSQL
AWS
Docker

Eatery is a Cornell Dining app with 40,000+ downloads, allowing 10,000+ students and facility to track menu items and schedules for dining halls and resturants.

MusicMaster Image

MusicMaster

React
Flask
PostgreSQL

MusicMaster is a music recommendation engine built on the Spotify API and song dataset which utilizes machine learning and content-based filtering to recommend songs. Users can login with their Spotify account to add recommended songs to their playlists.

Volume Image

Volume

TypeScript
Python
MongoDB
GraphQL
AWS
Docker

Volume is a cross-platform open-source Cornell student publication app with 1,000+ users, facilitating the exploration, sharing, and saving of content and the amplifcation of student voices.

NJoy Image

NJoy

React
Firebase

NJoy is the go-to trip-advising app created for the Garden State, providing information about New Jersey's favorite places and activities. NJoy allows users to plan their next trip, read and add reviews about locations, get directions, and much more.

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TownMate

Java
Airtable

TownMate is a cross-platform app that gives newcomers to a community information about restaurants, shopping malls, public transportation, and more. Awarded 3rd place for TSA National Software Development Competition.

Technical Experience

Languages

Python logo

Python

Programming Language

JavaScript & TypeScript logo

JavaScript & TypeScript

Programming Language

Java logo

Java

Programming Language

C & C++ logo

C & C++

Programming Language

Frameworks

React logo

React

Frontend UI Library

Express & Node.js logo

Express & Node.js

JavaScript Runtime

Django logo

Django

Backend Framework

Spring Boot logo

Spring Boot

Backend Framework

Databases

PostgreSQL logo

PostgreSQL

Relational Database

MongoDB logo

MongoDB

NoSQL Database

GraphQL logo

GraphQL

API Query Language

MySQL logo

MySQL

Relational Database

DevOps

Docker logo

Docker

Containerization Platform

Jenkins logo

Jenkins

CI/CD Platform

AWS, Azure, GCP logo

AWS, Azure, GCP

Cloud Services

Git logo

Git

Version Control

Machine Learning

PyTorch logo

PyTorch

ML Framework

TensorFlow logo

TensorFlow

ML Framework

Scikit-Learn logo

Scikit-Learn

ML Toolkit

NumPy logo

NumPy

ML Toolkit

Work & Leadership Experience

September 2023 - Present

  • Lead all development and delivery for an open-source team of 60+ students building apps with 15,000+ users
  • Collaborate with iOS, Android, Backend, Design, and Marketing teams using Agile to create and maintain apps
  • Taught weekly sessions to 100+ students focusing on client-server architecture, database design, and DevOps
  • May 2025 - August 2025

  • Built a synthetic benchmark generator in Python utilizing critique agents, reducing benchmark creation time by 95%
  • Integrated an autorater evaluation framework within a RAG system, leading to a 39% increase in generation quality
  • Developed an agentic AI system to generate LLM prompts, resulting in an 8x increase in prompt engineering output
  • June 2024 - August 2024

  • Implemented a CNN in Python with TensorFlow to classify ephemeral text within media with 94% accuracy
  • Utilized parallel computing via Spark and Jupyter Notebooks to train neural networks, reducing train time by 80%
  • Deployed microservice on AWS Lambda and Jenkins using CI/CD pipelines, processing 9,000+ media hours yearly
  • May 2023 - August 2023

  • Developed a RAG LLM in React, LangChain, and Django with 10,000+ users, achieving annual savings of $20,000+
  • Applied NLP algorithms to create text-based vector embeddings, optimizing document semantic search by 70%
  • Integrated Milvus vector database to store/retrieve embeddings and single sign-on (SSO) through Microsoft Azure
  • September 2022 - December 2023

  • Spearheaded design and implementation of a full-stack GUI application in React and Node.js with Express, enabling transmission of robot state
  • Coordinated with an 8-member team to build robot field visualization software in Python using Numpy
  • Simulated traversal algorithms and finite-state machine paths to optimize robot navigation strategies
  • Contact Me

    Feel free to shoot me an email or schedule a coffee chat through Calendly below.

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    Aayush Agnihotri © 2025