Explain the pattern.
Applied mathematics gives complicated systems a language—from Fourier series to financial models and image reconstruction.
Beirut · AI systems · applied mathematics
Leith Uwaydah is an AI builder at Local Service Spotlight. He turns complex ideas into visual models, then tests those models in working systems.
Leith UwaydahBeirut, LB
Find the hidden structure. Make it visible. Put it to work.
A yield curve, a basketball dribble, an image, and a marketing workflow look unrelated until you ask the same question of each: what pattern is underneath?
Leith’s published work explores the models. His work in AI explores what happens when those models become useful tools.
The story so farOne practice, three lenses
Applied mathematics gives complicated systems a language—from Fourier series to financial models and image reconstruction.
Movement is data. One published study turns the rhythm of a basketball dribble into a periodic signal that can be modeled.
AI becomes valuable when it leaves the demo and enters a real workflow—clearly mapped, tested, documented, and improved.
Featured field note
A whiteboard walkthrough of how a marketing system fits together—part explanation, part build log, and a starting point for what comes next.
Research, 2024–2026
The subjects move from periodic signals and quantitative finance to computer vision. The method stays consistent: make a difficult system legible.
View all publicationsThe working loop
Start with the real system, not the fashionable abstraction.
Map the variables, relationships, and failure points.
Turn the model into a tool someone can actually use.
Show the work, gather feedback, and make the next version better.
The channel is just getting started