Computer Science @ Michigan State • Business Minor • Data Products • Analytics Engineering • Applied ML

I'm a Computer Science major at Michigan State building software at the intersection of data engineering, backend systems, and applied AI.

I like projects where messy data becomes something useful: ETL pipelines, PostgreSQL-backed apps, dashboards, scoring systems, APIs, automation workflows, and ML-powered tools.

Start with Argus, my most complete data product.

Market intelligence platform for researching AI, semiconductor, quantum, and data-center-linked companies.

• Tracks 53 companies across AI infrastructure themes
• Built with Python, Streamlit, PostgreSQL, SQLAlchemy, and GitHub Actions
• Uses a 33-table data model with scheduled pipelines for market data, SEC filings, earnings, news, and macroeconomic indicators
• Includes peer-relative valuation, bull/bear thesis tracking, thematic indices, watchlist alerts, and explainable opportunity scoring
• Backtests signals across 5D, 20D, and 60D forward returns and analyzes earnings and SEC-filing catalyst reactions

Local-first PDF compressor for reducing image-heavy files without redrawing their pages.

• Preserves text, vectors, links, forms, annotations, outlines, metadata, and page geometry
• Uses pikepdf/QPDF and Pillow to resize raster images based on their effective rendered DPI
• Handles shared images and images nested in Form XObjects, with a guarded macOS Quartz fallback
• Includes a configurable Finder Quick Action for right-click compression
• Tested on macOS and Linux across Python 3.11–3.13

Applied ML tool for crop suitability and nutrient recommendations.

• Built Random Forest models using soil and weather inputs
• Deployed with Streamlit
• Won Best Sustainability Track at MHacks 2024

Dockerized backend marketplace built around service separation and authentication.

• Built 5 Flask microservices
• Implemented REST APIs, JWT authentication, SQLite persistence, and Docker Compose orchestration

• Building stronger data products with Python, PostgreSQL, and Streamlit
• Deepening my backend and data engineering skills
• Improving project documentation, testing, CI, and deployment quality
• Exploring applied AI workflows that make real work faster or easier

I'm open to software engineering, data engineering, and AI engineering new-grad conversations.

• Portfolio: apurva0510.github.io
• LinkedIn: linkedin.com/in/apurva0510
• Email: appyaggarwal40@gmail.com