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Aryan Thodupunuri

Explore my projects, skills, and experiences to learn more about my journey in tech.

CS Student at UVA | Data Science & Software Development | Problem-Solver at the Intersection of Tech & Business

About

CS & Business Student at the University of Virginia
  • Email: aryan20544@gmail.com

  • Phone: +1 571 442 7810

  • City: Ashburn, VA

    Hi, I’m Aryan Thodupunuri — a second-year Computer Science student at the University of Virginia, minoring in Data Science and General Business. I’m passionate about building impactful software and solving problems that sit at the intersection of technology, data, and business strategy.

    I’ve built a strong foundation at UVA through courses like Data Structures & Algorithms II and Machine Learning, which have sharpened my technical thinking and deepened my understanding of scalable systems and predictive modeling. This summer, I’m interning at Booz Allen Hamilton as a Federal Technology Consulting Intern, working on projects that leverage automation tools, data analytics, and procurement systems to improve federal contract tracking and supplier diversity efforts.

    Previously, I interned at UVA’s Link Lab, where I helped optimize a CNN-RNN hybrid model in Python using TensorFlow to enhance real-time flood forecasting accuracy. I also lead data projects at BioKind Analytics, using predictive modeling to support nonprofit initiatives. Outside of class, I serve as the VP of Academic Excellence for Delta Upsilon Fraternity, volunteer as a basketball coach, and enjoy playing roller skate hockey in my free time.

    I’m always excited to explore new opportunities in software engineering, data science, and tech consulting—especially ones that create real-world impact. Feel free to check out my projects and reach out!

Resume

Summary

Aryan Thodupunuri

I am an effective student committed to building skills in data science, software development, and finance. With a strong foundation in these areas, I excel in both academic and practical applications. Known for excellent communication and a proven ability to accomplish objectives in a timely manner, I am dedicated, responsible, and eager to grow my abilities while contributing to operational success. Through my academic journey and various projects, I have developed a deep understanding of data analysis, programming, and project management, making me a versatile and valuable asset to any team.

Education

B.A Computer Science & Minor in DS/General Business

  • University of Virginia, Charlottesville

  • Aug 2023 - May 2026

  • Relevant Coursework: Algorithms & Systems Design, Cloud Infrastructure & Enterprise Solutions, Machine Learning & Predictive Analytics, Software Engineering & Agile Development, Database Systems & Intelligent Data Processing, Tech Strategy & Digital Transformation

  • Extracurriculars: Research @ Floodwatch.io, BioKind Analytics (Predictive Analytics Consultant), Business & A.I Club (Project Analyst), Virginia Data Science & Analytics Club (VDSAC), & Delta Upsilon Fraternity (VP of Academic Excellence)

Advanced Diploma

  • Stone Bridge High School/Academy of Engineering and Technology, Ashburn, VA

  • Relevant coursework: AP Macroeconomics (5), AP Microeconomics (5), AP Calculus AB (5), AP Calculus BC (4), AP Statistics (5), AP Computer Science A (5), AP Physics C: Mechanics (4)

  • Stone Bridge Investment Fund (Founder and President), Speech and Debate Club (President), Stone Bridge CyberPatriot (Vice President), Stone Bridge Varsity Hockey Team

Experience

Incoming Summer 2025 Federal Technology Consultant, Booz Allen Hamilton, McLean, VA

Summer 2025

At Booz Allen Hamilton, I will work on analyzing and optimizing federal contract data to improve procurement efficiency and supplier diversity tracking. My role involves leveraging automation tools like iValua SBCMS, Power BI, and workflow automation to enhance reporting accuracy on $1M+ in federal contract awards. I will be responsible for evaluating and visualizing key procurement metrics, tracking Small Business (SB) and Small Disadvantaged Business (SDB) participation, and ensuring compliance with government subcontracting regulations (FAR, CPARS). Additionally, I will collaborate with cross-functional teams to develop data-driven insights that support federal procurement strategy and operational improvements.

Machine Learning Researcher, UVA Link Lab, Charlottesville, VA

May 2024 - August 2024

As a Machine Learning Researcher at UVA’s Link Lab, I collaborated with a PhD student to develop and optimize hybrid CNN-RNN models in Python and TensorFlow, enhancing real-time flood prediction by reducing computation time by 95%, from 3 hours to under 10 minutes. Through hyperparameter tuning and cross-validation, I increased predictive accuracy by 15%, integrating environmental factors such as topography and rainfall patterns to improve model performance. I worked extensively with satellite imagery and time-series data, implementing advanced feature extraction techniques to support flood risk management. Our work contributed to local flood management discussions and strategies, making a measurable impact on predictive capabilities in environmental monitoring.

Propel Intern, Capital One, Charlottesville, VA

December 2023 - January 2024

During my internship at Capital One’s Propel program, I partnered with a team of four to devise a solution aimed at increasing Capital One Shopping users and addressing specific marketing challenges. I utilized advanced data visualization techniques in Excel and Tableau to present performance metrics and findings to Capital One judges, helping improve decision-making processes. This experience strengthened my ability to collaborate effectively on data-driven projects and communicate insights clearly to stakeholders.

Data Analyst, BioKind Analytics, Charlottesville, VA

August 2024 - Present

At BioKind Analytics, a competitive, student-led data analysis group at UVA, I collaborate with nonprofits to drive impactful, data-driven projects. Currently, I am analyzing over $100,000 in donations for the Agape Pregnancy Center of Loudoun, automating the separation of monetary and asset donations using Python and R. This work has improved data consistency by 40% through custom scripts and statistical modeling. Additionally, I’ve developed machine learning models, including Random Forest and XGBoost, to predict high-value donors with 85% accuracy, and I’m using time series analysis in R to forecast event-based revenue with a mean absolute percentage error (MAPE) of 5%.

Software Development Intern, Triviappolis Treasures, Ashburn, VA

December 2021 - June 2022

During my internship at Triviappolis Treasures, I enhanced a city trivia game app by developing a dynamic tier system (bronze, silver, gold) based on users' correct answers. This feature fostered engagement and incentivized continued participation. I collaborated within a team to elevate the mobile application, utilizing React Native for the frontend and Django for the backend. Additionally, I implemented AWS Beanstalk for seamless deployment, ensuring efficient delivery of features and improved scalability. One of my key achievements was successfully transitioning advertisement deployment functionality from AdSense to Google AdMob, optimizing ad delivery and revenue generation for the app.

Code Coach, The CoderSchool Ashburn, Ashburn, VA

June 2022 - August 2023

As a Code Coach at The CoderSchool Ashburn, I customized individualized lessons in 1-on-1 training sessions, adapting content and pace to match students' proficiency levels in diverse programming languages, thereby fostering their skill development and mastery. I provided hands-on guidance and support to students as they embarked on diverse project endeavors aligned with their chosen programming language. These projects ranged from simple animations to complex applications featuring functional user interfaces, empowering students to apply and refine their skills effectively.

Portfolio (Click for Details)

NBA Win Prediction Neural Network

The Future Of Artificial Intelligence in Weather Forecasting

Traffic Sign Convolutional Neural Network


Stock Price Prediction Using K-Nearest Neighbors (KNN)

Microservice Food Ordering System

Course Picker Web App

Fake News Detection

Taiwan Bankruptcy Prediction