Where data science meets genomics and markets
MarketMotif AI isn’t just a side project. It’s a showcase of how a modern data scientist thinks: from cross-domain abstraction to clean implementation. You’ll see machine learning, signal processing, and design all come together in a way that’s technically deep and visually intuitive.
MarketMotif AI is a project built around a simple but powerful idea: techniques from one domain often unlock breakthroughs in another. Inspired by the signal-processing pipelines of genomics, we translate those tools to financial data — and vice versa. The result is a unified system for discovering subtle patterns in complex time-series data.
My background is in computer science and data science — not biology. But through hands-on work in a top genomics lab, I’ve been able to build tools that bridge disciplines. MarketMotif AI is a direct result of that cross-pollination: an attempt to rethink how we discover patterns in both DNA and market signals using shared mathematical principles.
Whether you're mapping transcription factor binding or modeling market fragility, you're dealing with noisy, high-dimensional data. MarketMotif AI shows that the same pipelines — peak detection, motif discovery, statistical scoring — can reveal structure in both. This kind of thinking is what sets apart top-tier data scientists: the ability to abstract, adapt, and deploy across fields.