Sanjay Karunamoorthy


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About Me


Who am I?

I'm a 4th year at UVA pursuing a B.S in Computer Science, B.A in Mathmatics, and Minor in Data Science expected to be completed by Spring of 2026. I am passionate about solving problems and learning anything cool.



Skills

Languages

  • Java
  • Python
  • C
  • JavaScript
  • Typescript
  • HTML + CSS
  • SQL

Technologies/Frameworks

  • Spring
  • Django
  • React
  • OpenSearch
  • Next.js
  • Node.js
  • PyTorch
  • MongoDB
  • Express
  • Kafka
  • Git
  • REST API

Professional Experience


University of Virginia

Undergraduate Artificial Intelligence Researcher

August 2025 – Present


  • Training Reinforcement Learning Agents to collaborate with humans to improve task performance with Proximal Priority Optimization. Conducting experiments with multi-agent settings to analyze cooperation, incentives, and emergent behaviors.

GEICO

Software Development Intern

June 2025 – August 2025


  • Pioneered an MVP dashboard for a Project Development Life Cycle management system based on Shift Left methodology; created a REST API leveraging Django, PostgreSQL, TypeScript, and React; scoped to benefit 3000+ engineers.

  • Partnered with 15+ Senior Directors, VPs, PMs, Engineers and SMEs in a cross-functional team to design a product workflow optimization system with JSON integration, Redis caching, GraphQL querying, and Azure DevOps/Slack automation.

  • Implemented efficient GET/POST requests for bidirectional synchronization and timed system reloads to prevent race conditions.
  • Engineered an email automation script by pre-processing 17,000+ repositories to reach out to 2000+ system owners; utilized Power BI and Excel for data input organization and communication for stakeholders, using pandas for email sending automation.

3M

Software Engineer Intern (Contract)

May 2024 – July 2024


  • Crafted an efficient data processing solution leveraging Spring Boot and Spring Batch, handling over 2,000,000+ search data points belonging to 3M from Salesforce and Sharepoint, with thorough error handling.

  • Optimized and utilized scalable big data pipelines with Apache Airflow and Kafka, enabling real-time streaming data integration with batch processing, leading to a 6% improvement in processing efficiency for semantic search, based on time and CPU usage.

  • Utilized Amazon Bedrock for Natural Language Processing (NLP), employing Titan Text Embeddings to transform words into high dimensional vectors, enabling vectorized search for Retrieval-Augmented Generation (RAG).

  • Incorporated kNN vectors (k=5) for embedding storage with lambda functions on OpenSearch, prompt engineering Anthropic Claude API to generate context-relevant responses; leveraging Swagger for API development.

SS Technology

Full Stack Engineer Intern

December 2023 – May 2024


  • Directed a group of interns to develop a REST API, organized meetings via JIRA for agile sprint management. Worked on CI/CD pipelines for an employee management app using Docker, Kubernetes, Jenkins + Bitbucket, reducing deployment times by 30%.

  • Designed and created a secure back-end authentication system using React, Express, Node.js, and MongoDB, utilizing JWT and Bcrypt to enhance security by eliminating all major authentication vulnerabilities by replacing an insecure SHA-256 hash.

  • Automated monitoring tasks through Linux/Unix environments with Bash scripting to reduce manual setup time.


My Projects and Activities


Micrograd


  • Implementing backpropagation over a dynamically built DAG. Creating a neural network from scratch.

TensorFlow, Python, Neural Networks, Backpropagation, Gradient Descent

August 2025 – Present

SK-GPT


  • Implemented ChatGPT from scratch using neural networks with custom backpropagation and gradient descent algorithms.

TensorFlow, Python, Neural Networks

August 2025 – Present

Siblings or Dating – Facial Recognition


  • Created a Convolutional Neural Network (MobileNetV2) using transfer learning to classify preprocessed images scraped from Reddit via PRAW.
  • Achieved 80% validation accuracy distinguishing couples as either siblings or dating through hyperparameter tuning.

TensorFlow, Keras, Python, CNN, Django

March 2025

Akuna Capital Quant Trading Challenge


  • Pioneered a python-based market making quantitative trading framework integrating nonlinear optimization and stochastic modeling.
  • Implemented reinforcement learning to dynamically synthesize adaptive market intelligence.

Python, Reinforcement Learning, Nonlinear Optimization

August 2024

Poker Bot


  • Used a Monte Carlo counterfactual regret minimization algorithm to approximate a Nash Equillibrium strategy for a 2-player Khun's poker game.

Python

June 2024 – July 2024

TenantTalk


  • Built a web app for rating landlords and property management, adhering to Scrum methodology with a team of 5 other developers through sprints and weekly meetings.

Django, PostgreSQL, Heroku, AWS S3

Jan 2024 – Present

Coccidiosis Classification


  • Constructed a Convolutional Neural Network (CNN) to detect Coccidiosis signs in chicken images, with the use of over 1000 labeled images.

Python, TensorFlow, Azure

Jan 2024 – March 2024

Film Finder


  • Created using Python and Jupyter Notebook with libraries like Numpy, sci-kit-learn, pickle, and requests.
  • Integrated TMDB API for data retrieval, including plot summaries, genres, and ratings from over 5000 movies.

Python, TensorFlow

Sept 2023 – Dec 2023

EzCite


  • Lead developer of the website, utilizing React and Next.js.
  • Leveraged a mix of the Perplexity LLM and Node.js modules such as discord.js and Puppeteer.
  • Use of citation-machine to create optimal citations from an input of text.

React, Next.js, Node.js, JavaScript, HTML, CSS

Mar 2024 – Mar 2024

Natural Language Processing Application


  • Detects names, cities, states, and countries from given sentences.
  • End-to-end development of a robust NER application leveraging the Stanford CoreNLP.

Java, Spring Boot

Nov 2023 – Dec 2023

European Option Pricing


  • Developed a Monte Carlo simulation-based pricing model for European vanilla options in C++using risk-neutral pricing, Geometric Brownian Motion, and the Box-Muller algorithm, achievingresults closely matching Black-Scholes solutions.

C++

May 2024 – June 2024

EDO.ai


  • Developing and researching models to predict diabetes using extensive blood test data and other methods.

PyTorch

August 2024 – Present