Varshith.V

Software Developer with a Passion for Quant

About Me

Portrait of Varshith Vajinapelli

Hey! I'm Varshith Vajinapelli, a second-year Computer Science student at the University of Minnesota. I love coding and enjoy taking on new programming challenges just as much as I love playing cricket.

My interest in quantitative trading started with my dad's experiences trading commodities. Inspired by his journey, I’ve been trading forex, commodities, and dabbling a bit in options. This passion has led me to explore the world of quant trading, where I get to mix technology with finance to build smart trading solutions.

When I'm not coding or analyzing market data, my younger brother loves to annoy me or play with me (all in good fun, of course!). I also spend a lot of time with my parents and hang out with my close friends, balancing my studies and hobbies with some quality downtime.

In my free time, I’m learning to play the piano and always enjoy listening to old Telugu music. Whether it's hitting the keys or grooving to classic tunes, these activities help me relax and stay creative.

"Real Human does Real things, I am a real human."
~ Varshith

Skills

Programming Languages

  • Python
  • C/C++
  • JavaScript
  • OCaml
  • Java

Frameworks & Technologies

  • PyTorch
  • FastAPI
  • OpenCV
  • NumPy & Pandas
  • HTML, CSS, Tailwind CSS

Tools & Platforms

  • Git & GitHub
  • Docker
  • PostgreSQL

Ongoing Learning

  • Go (Golang)
  • gRPC
  • Protocol Buffers

Projects

Find Waldo Project

Find Waldo: A FastAPI-Powered Object Detection System

This project utilizes PyTorch and OpenCV to develop a YOLOv5-based model that accurately detects Waldo in complex images. Accessible via a FastAPI REST API, users can upload images and receive real-time detection results.

  • Deep Learning: Fine-tuned YOLOv5 model for precise object detection.
  • API Integration: User-friendly FastAPI REST API for seamless interaction.
  • Image Processing: Efficient preprocessing with OpenCV to optimize images for inference.
  • Documentation: Automated API documentation using Swagger for easy testing and usage.

Key Skills:

  • Programming Language: Python
  • Frameworks & Libraries: PyTorch, FastAPI, OpenCV, NumPy, Pandas, Matplotlib, pytest
  • Tools: Swagger
Python PyTorch FastAPI OpenCV NumPy Pandas Matplotlib pytest
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DocuQuery Project

DocuQuery: Smart Document Assistant

DocuQuery is a web-based application that allows users to upload PDF files. The system automatically extracts text and enables users to query the document's content using OpenAI's advanced language models, making information retrieval from large or technical documents easier and faster.

  • Automated Text Extraction: Utilizes PyPDF2 to extract text from PDF files.
  • Real-Time Querying: Powered by OpenAI’s API for accurate and intelligent responses.
  • Secure File Handling: Ensures data privacy and secure management of uploaded documents.

Key Skills:

  • Programming Language: Python
  • Frameworks & Libraries: Flask, PyPDF2, OpenAI API, HTML/CSS, JavaScript, Bootstrap
Python Flask PyPDF2 OpenAI API HTML/CSS JavaScript Bootstrap
View Project

Ongoing Projects

Trading Signal Generator CLI Project

Trading Signal Generator CLI

A command-line application developed using C# and .NET Core designed to process real-time market data and generate trading signals based on predefined algorithms. This tool assists financial analysts and traders in identifying potential trading opportunities by analyzing live data streams from financial APIs.

  • Data Ingestion from APIs: Connects to financial data APIs (e.g., Alpha Vantage) to fetch real-time market data for selected financial instruments.
  • Signal Generation: Implements trading algorithms to analyze incoming data and generate buy/sell signals based on moving averages and trend indicators.
  • Logging: Utilizes NLog for structured logging of market data, generated signals, and system events to facilitate monitoring and debugging.
  • Export Capabilities: Allows users to export generated signals to CSV files for easy review and integration with other analytical tools.
  • User Configuration: Provides configurable settings through command-line arguments and a configuration file, enabling users to customize trading strategies and data sources.

Key Skills:

  • Programming Language: C#
  • Frameworks & Libraries: .NET Core, NUnit
  • APIs & Integration: RESTful APIs, HTTP Client
  • Data Processing: LINQ, Data Structures
  • Logging: NLog
  • File Handling: CSV Export using CsvHelper
  • Version Control: Git
C# .NET Core NUnit RESTful APIs HTTP Client LINQ NLog CsvHelper Git
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Market Data Dissemination Simulator Project

Market Data Dissemination Simulator

A client-server application developed using Go (Golang) and gRPC designed to simulate real-time market data distribution for financial instruments. This tool allows clients to subscribe to specific instruments and receive live updates of order book snapshots and incremental changes.

  • Real-Time Data Streaming: Utilizes gRPC for efficient, bi-directional streaming between server and multiple clients, ensuring low-latency data dissemination.
  • Order Book Management: Maintains and updates order books for various financial instruments, simulating trading events like adding, updating, and removing price levels.
  • Client Subscription Mechanism: Enables clients to subscribe or unsubscribe to specific instruments, receiving initial snapshots followed by continuous updates.
  • Configuration Management: Employs YAML files to define instrument specifications and order book depths, allowing easy customization.

Key Skills:

  • Programming Language: Go (Golang)
  • Frameworks & Libraries: gRPC, Protocol Buffers
  • Configuration Management: YAML
  • Concurrency: Goroutines, Channels
  • Logging: Logrus
  • Testing: Go's built-in testing framework
  • Version Control: Git
Go gRPC Protocol Buffers YAML Goroutines Channels Logrus Git Testing
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Professional Experience

Teaching Assistant - Python Course CSCI 1133

University of Minnesota | Sept 2023 - Present

Assisted 35 students in lab sessions by helping them troubleshoot issues and explaining approaches to solving Python programming problems. Focused on clarifying concepts and guiding students through debugging and problem-solving strategies.

Student Service Fee Committee Member

University of Minnesota | Sept 2022 - Present

Deliberated on and allocated over $2.85 million to student organizations, large-scale events, and collaborative initiatives that enhanced student engagement, campus life, and academic opportunities over a two-year period.

Housing Residential Chair Member

University of Minnesota | Sept 2023 - Jan 2024

Provided strategic recommendations for the management of 10 residential halls, including enhancements to the fire alarm systems in Centennial Hall and the implementation of new turnstiles in all buildings, rolling out this year. Deliberated on a fair lottery system for students wishing to continue living in residential buildings after their freshman year, ensuring equitable housing allocation.

Office Assistant

University of Minnesota Twin Cities | Sept 2023 - Ongoing

Solved residential issues, managed key access and security protocols, and collaborated with various departments to ensure smooth operations and effective communication.

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