Aidan Lynde

Completed Hour of Code at age 11, after some encouragement from my elementary-school computer science teacher. The start of everything that followed.

Before I could code properly I was already obsessed with how the internet worked — building little things, reverse-engineering games, and always running some small operation on the side. Elementary school me had a trading-card hustle, sold snacks, and was constantly trying to figure out how to make something from nothing.

First formal CS classes, alongside the advanced math and economics track that shaped where I'd go next.

Designed and constructed a custom shoe by hand for my sophomore-year personal project. Not a lot of documentation survived, but it happened.

Managed daily operations for incoming school camps, tours, and demonstrations at one of Chicago's flagship institutions. A paid internship that ran like a real job — coordinating staff, guests, and programming across the floor.

Worked at a Chicago community TV station writing, shooting, and editing short films and news segments in Premiere and DaVinci Resolve. Got comfortable in front of and behind the camera, and discovered a real talent for writing and telling stories — the kind of communication skills that still show up in how I pitch and document work today.

Pivoted through several Shopify stores — merch, a bar-cart brand, tech gear, and a nasal-breathing device line — learning firsthand that brand recognition, not ads, is what actually lasts.

Sourced designer clothes, model cars, refurbished electronics, and AV equipment from garage sales and marketplaces to resell — and reinvested the profits into what came next.

Moved to Champaign to begin undergrad.

Rode a strong run and sold before a major drop — made real money and started developing a genuine understanding of how crypto markets move. Began studying the interplay between large and retail investor sentiment, macro finance, and current events, and how all of it ripples through price action.

Refocused on econometrics and machine learning — the intersection I still work in today.

Built a student organization from scratch — hosting investing workshops, teaching peers how to get started, and fostering a real community around markets and building. The club eventually wound down, but the core group stayed together and grew into a network of active investors and builders — stocks, commodities, crypto, real estate, startups. It became the foundation of my investing and startup network today.

Implemented an automated Python web scraping tool to collect, process, and structure marketing data for analysis. Built data pipelines and dashboards to deliver actionable insights for campaign and business decision-making. Collaborated on projects requiring rapid development, data quality control, and reliable reporting.

Doubled down on programming — advanced C++, distributed systems, applied ML — and set a hard goal: land a software engineering internship the next summer.

Finished undergrad with a CS minor and a machine-learning focus in the Economics department.

A production-ready authentication and database scaffold I now reuse across client and personal projects.

An explainer built to make privacy-preserving federated learning legible to non-technical investors.

A class-action litigation screener that ingests federal court filings, screens complaints through an LLM pipeline, and surfaces structured case intelligence for legal and investment teams.