Innovator. Creator. Technologist.
I’m Aditya Parekh, pursuing a Bachelor of Science in Computer Science and Data Science at the University of Wisconsin–Madison, with expected graduation in December 2027. I build intelligent systems and scalable software with real-world impact.
As a Software Development Engineer Intern at Amazon, I built a dashboard monitoring 530 pipelines and 40K+ daily events, helping 30+ teams cut manual status checks by 50% and resource costs by 25%. I also built MCP servers for natural-language access to pipeline metrics.
At Traders at Wisconsin Club, I worked with the former Chief Risk Officer of Two Sigma on infrastructure and backtested strategies for a $1M portfolio, achieving a Sharpe ratio of 1.2. Previously, at Hussmann, I built a Kafka-based anomaly detection system that reduced costs and repairs by 25%, and a VR application with an Azure OpenAI chatbot that accelerated support queries by 50%.
With the Wisconsin Autonomous Club, I engineered real-time perception for autonomous vehicles, contributing to 2nd place overall in the SAE Autodrive Challenge. At BooksToBorrow, I developed cloud-native features and Django APIs for a platform that reached 13K+ users within 96 hours of launch.
I’m also the co-founder of ClaimReady, a 5x award-winning AI web app that reduces insurance claim valuation time from 20+ hours to under 2 minutes. I led full-stack development and helped scale a distributed image valuation pipeline to 1K+ users, processing 4K+ images valuing $2M+ in assets.
Check it out here: useclaimready.ai.
Awards & Achievements
Recognized for technical excellence and software innovation.
1st Place MadData25 Hackathon
Won 1st place among 40+ teams and 200+ participants.
HackathonView on DevpostClaimReadyTop 3 at Midwest Startup Pitch Competition
Placed in the Top 3 among 25+ teams.
National Startup CompetitionRead ArticleClaimReadyTop 3 at Madison Startup Competition
Placed in the Top 3 at the Madison Startup Competition.
University Startup CompetitionView LinkedIn PostClaimReadyTop 5 at Fetch Defeat the Odds Competition
Placed in the Top 5 among 30+ teams.
Startup CompetitionClaimReady1st Place Ideation & Innovation Challenge
Won among 30+ participants with a VR application linked to an Azure OpenAI chatbot for technician training.
Innovation ChallengeHussmann2nd Place Overall SAE Autodrive Challenge
Contributed real-time perception for autonomous vehicles with lane, cone, and boundary detection.
Autonomous Driving CompetitionWisconsin Autonomous ClubWork Experience
Software Development Engineer Intern
Amazon
Jun 2026 - Sep 2026
Designed and built an internal dashboard monitoring latency, growth trends, and failure rates across 530 pipelines and 40K+ daily events. Used React, Java, TypeScript, and AWS to help 30+ teams reduce manual status checks by 50% and resource costs by 25%. Built MCP servers enabling natural-language access to pipeline metrics, reducing retrieval time by 35%.
Software Engineer
Traders at Wisconsin Club
Jan 2026 - May 2026
Worked with the former Chief Risk Officer of Two Sigma to design software infrastructure and backtest strategies on a $1M portfolio, achieving a Sharpe ratio of 1.2. Built with Python, Flask, Docker, and Google Cloud Platform. Researched predictive models with yfinance, regression, momentum, and statistical methods, integrating backtested strategies into a multi-strategy portfolio system.
Software Engineer Intern
Hussmann
May 2025 - Aug 2025
Reduced costs and repairs by 25% by designing a predictive anomaly detection model using Apache Kafka to stream and process 100K+ sensor events, AWS S3, SageMaker, PostgreSQL, Python, and RESTful APIs. Documented 15+ recurring failure conditions incorporated into monthly company-wide maintenance reporting. Built a VR application linked to an Azure OpenAI chatbot trained on internal refrigeration documentation, accelerating support queries by 50% and winning 1st place in the Ideation & Innovation Challenge among 30+ participants.
Software Engineer
Wisconsin Autonomous Club
Sept 2024 – May 2025
Helped achieve 2nd place overall in the SAE Autodrive Challenge by engineering real-time perception for lane, cone, and boundary detection. Optimized C++/Python, OpenCV, and machine learning models for scalable, fault-tolerant sub-100ms performance. Integrated perception into the autonomous driving pipeline with 30+ engineers through design reviews, CI/CD workflows, and SDLC processes.
Software Engineer Intern
BooksToBorrow
Jun 2023 – Aug 2023
Designed and deployed cloud-native dashboard, MFA, and OAuth features using React, React Testing Library, and MongoDB, containerized with Docker and scaled via AWS ECS. Built RESTful APIs with Django and validated endpoints with Postman to improve deployment reliability. Supported a successful platform launch reaching 13K+ users within the first 96 hours.
Education
Bachelor of Science in Computer Science and Data Science
University of Wisconsin - Madison
Expected Graduation December 2027
Coursework: Linear Algebra, Data Structures & Algorithms, Object-Oriented Programming, Machine Learning, Statistics, Artificial Intelligence, Operating Systems, Big Data Systems, Database Systems.
Skills & Technologies
The languages, frameworks, and platforms I use to build software.
Languages
Frameworks / Libraries
Developer Tools
Cloud & Databases
Featured Projects
A showcase of notable projects I've worked on.
ClaimReady
Co-founded and led full-stack development of ClaimReady, a 5x award-winning AI web app that creates complete home inventories and reduces insurance claim valuation time from 20+ hours to under 2 minutes. Scaled to 1K+ users through a distributed image valuation pipeline built with Docker, Kubernetes, AWS ECS/Fargate, YOLO11, and Google Gemini, processing 4K+ images valuing $2M+ in assets. Recognized as investor-ready by judges and acknowledged by YC partners and the UW–Madison CS Department for technical excellence.
Gordon AI
Developed Gordon AI, an AI-powered cooking assistant that leverages Google Gemini API, prompt engineering, and persona emulation to deliver dynamic, in-character responses like Gordon Ramsay. Built a full-stack web app using React/Next.js and TypeScript with Supabase for user data persistence, enabling real-time interaction and personalized recipe recommendations.