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One of the results I'm most proud of from my machine learning work — four high-performing cardiovascular classification pipelines evaluated across multiple metrics.
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Kairos - FIFA World Cup 2026 Tournament Analytics Dashboard
Kairos is a tournament analytics dashboard designed for analysts and broadcasters who need every match, venue, and performance metric visible in one place built for the scale of a World Cup.
𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗮𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻 𝘄𝗮𝘀 𝗴𝗶𝘃𝗲𝗻 𝘁𝗼:
- Live alerts covering pitch conditions, VAR, ticket sales, and security;
- Tournament facts - 48 nations, 16 venues, 5M fans expected;
- Cinematic match card
- 89 total goals tracked across 32 matches with open play vs set piece split;
- 2.17M attendance across USA and MX+CA venues;
- AI qualification predictions
A dark, data-rich dashboard that makes tournament-scale complexity feel completely in control
Looking to design a sports analytics or live data platform? Let's build it together
#dashboard #uidesign #analyticsdashboard
Day 4 of learning and creating with AI.
Today, I created a UGC-style product campaign for AURA PRO, a fictional wireless earbuds brand.
The goal wasn't just to make the product look good. I wanted the video to feel natural, relatable, and believable — like a real person sharing why they chose the product.
From the product concept to visuals → AI model → storytelling → video, everything was built with AI.
Still experimenting. Still learning. Still getting better.
Day 4/30.
What do you think?
AI Engineer Adobe IllustratorChatGPTGoogle FlowaivideocreationugccreatoraiproductphotographyAI Video ProductionUGC Creation
The focus on believability is exactly right for UGC. A polished render is easy to notice, but natural pacing and human context are what make a product story feel trustworthy.
About This Work
I worked on a Python-based data processing and machine learning workflow focused on turning raw data into clean, reliable, and usable insights. The work involved cleaning and transforming data, handling missing or inconsistent values, validating data quality, and preparing meaningful features for analysis and machine-learning workflows.
I focused on making the workflow structured and reproducible so that the resulting data could be used confidently for downstream analysis and model evaluation.
Skills: Data Processing & Cleaning · Machine Learning · Data Analysis & Validation
Tools: Python · Pandas · Scikit-learn
