3rd Position – RoboMania AI Hackathon
Spearheaded an AI-powered stock market prediction engine to secure 3rd place among 100+ multi-campus engineering teams.
Competition Overview & Experience
RoboMania AI Hackathon was an intensive inter-college hackathon that brought together more than 100 competitive engineering teams from campuses across the region. The challenge demanded building an intelligent, production-grade AI system within an intense sprint. As Team Leader, Udit directed the architectural conception, data engineering pipeline, model selection, and frontend interface for StockAI — an intelligent time-series forecasting platform designed to predict equity market trends. Under strict deadlines, Udit coordinated task delegation across dataset preprocessing, feature engineering, and live API deployment. During the final presentation before a jury of industry machine learning practitioners and academics, Udit demonstrated the real-time inference latency and accuracy metrics of the model, earning a podium finish and a cash award.
The Core Challenge
Developing a time-series forecasting engine with low latency inference that could process real-time financial market data while preventing over-fitting on volatile price movements.
Engineered Solution
Engineered a hybrid predictive architecture integrating moving-average feature transformations with an interactive Next.js dashboard, enabling live interactive parameter tuning during jury demonstrations.
Key Leadership & Technical Highlights
Secured 3rd Position and cash prize among 100+ participating engineering teams from across the state.
Served as Team Leader, orchestrating project roadmap, Git workflows, and task assignments under tight 24-hour sprint constraints.
Delivered a live, crash-resilient technical demonstration of the stock prediction model to the evaluation jury.
Engineered an intuitive frontend visualization layer allowing non-technical judges to explore prediction confidence intervals.
Milestone Details
Skills & Proficiencies
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