Hi, I am Emmanuel, a year 2 student studying Data Science and Economics. I work across machine learning and software, building tools that are actually usable.
I'm drawn to problems that help others, especially where data drives decisions. I like digging into messy, real-world data to find otherwise unnoticeable inferences and correlations.
That curiosity is what pulls me toward hackathons and self-directed builds. I love the challenges and exposure to scenarios where I can make a difference.
What I care about most is that what I build actually gets used, not just demoed. I'm working toward a career in machine learning or data science, where that combination of rigor and usability matters most.
Usage tracking and restock forecasting for the Coffeehouse Bot, and the data cleaning and statistics pipeline behind SurveyLens.
Developed an autonomous interception decision maker focused on reducing collateral damage using imitation learning. Outperformed a naïve baseline in 82.8% of validation episodes, cutting consequence loss by 11.4%; selected as a finalist.
Inventory manager to optimise logistics tracking and reduce inventory wastage for a student interest group of 60 members. Uses data to forecast restock requirements.
Creator-specific trend intelligence prototype for finding social-media opportunities that fit a creator's niche and audience. Projet Hack & Hire 2026 winner; interview opportunity earned.
Submission for NUS Datathon 2026. Full-stack survey analysis tool that lets users upload CSV survey data and get AI-generated statistical insights, sentiment analysis and persona development from the results.
Analyzed telemarketing data to build and compare classification models predicting bank term deposit subscriptions, identifying key behavioral and macroeconomic drivers to help optimize customer targeting.