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Varun Chitturi

varchi [at] seas [dot] upenn [dot] edu

I'm currently a student at the University of Pennsylvania pursuing a BSE and MSE in Computer Science with a concentration in AI. My interests span distributed systems, machine learning, optimization, web/mobile development, and more. I am also a D1 athlete on the varsity squash team. In my free time, I like to do photography.

Relevant Coursework

  • CIS 1200: Programming Languages and Techniques
  • CIS 1600: Discrete Mathematics
  • CIS 1210: Data Structures and Algorithms
  • CIS 2400: Computer Systems
  • CIS 2620: Automata Computability, and Complexity
  • CIS 5200: Machine Learning
  • CIS 5300: Natural Language Processing
  • ESE 2000: AI Lab
  • ESE 4020: Statistics for Data Science
  • ESE 5140: Graph Neural Networks
  • MATH 1400: Single-Variable Calculus
  • MATH 1410: Multivariable and Vector Calculus
  • MATH 2400: Linear Algebra and Differential Equations

Work Experience

  • May 2024-Present

    Philadelphia, PA

    • Independently devised comprehensive solutions for machine learning labs, including Variational Autoencoders, Variational Diļ¬€usion Models, Actor-Critic Reinforcement Learning, and Large Language Models.
    • Authored in-depth explanations accompanying solutions, ensuring clarity and rigor by integrating detailed mathematical proofs. Some explanations were published in notes.

    July 2022-May 2023

    Madison, WI

    • Managed cloud infrastructure, CI/CD pipelines, and DevOps services for datachat.ai, optimizing deployment processes and enhancing system reliability.
    • Designed a novel microservice architecture to handle machine learning tasks concurrently, improving system scalability and reducing request dead locks.
    • Transferred our entire AWS Kubernetes deployment from UI-based to IAC (Infrastructure as Code) using Terraform, while automating infrastructure updates through CircleCI, Docker Compose, and AWS.

Projects

  • Generative Diffusion Model for Video

    Jun 2024-Aug 2024

    • In collaboration with researchers from Google Deepmind and ASU, helped develop a generative diffusion model for video using the DDPM algorithm, implementing it from scratch using UNets.
    • Automated data collection in Unreal Engine using the Unreal Python API, generating 2D projections, depth maps, and normal maps to create a comprehensive dataset for model training.
  • Aug 2021-May 2022

    • Created Rift, an iOS application built with SwiftUI, offering students an enhanced in-app experience for managing their academic journey.
    • By reverse-engineering the Infinite Campus API, Rift provides students with seamless access to vital information such as grades, homework assignments, and messages, all within a user-friendly interface.
    • Currently being maintained for over 15,000 middle and high school students.
  • Jan 2021-May 2022

    • Developed and launched easeattendance.com during the pandemic. Ease Attendance is a web platform designed to seamlessly integrate with Zoom meetings, streamlining the way educators manage attendance.
    • Offers real-time attendance tracking, comprehensive statistical insights, and user-friendly features.
    • Currently being maintained for a community of over 4,000 educators.
  • Mar 2021-Jun 2021

    • Developed a headless server for automated options day trading, integrating a TradingView-hosted algorithm with the Ameritrade API. Utilized RSI (Relative Strength Index) to optimize trading positions.
    • Performed backtesting to check algorithm performance. Realized a 30% gain in 3 months of using the algorithm.

Research

    • Co-authored a research paper focused on leveraging deep learning computer vision techniques for predicting poverty levels in various global regions using overhead satellite imagery.
    • Addressed the challenge of limited reliable economic data in developing areas, offering a more cost-effective alternative to traditional surveys.
    • Explored the impact of data quantity and augmentation on network performance in order to improve the model.

Awards