Build. Trade. Win $500. Ready to put your AI trading skills to the test? Join us for an exciting hackathon where you'll build autonomous trading agents for Turbine.
What You'll Do Build an AI-powered trading agent that can autonomously trade on Turbine's prediction markets. Whether you're into reinforcement learning, market-making strategies, or predictive analytics, this is your chance to showcase your skills and compete for serious prizes. The Challenge Design and deploy a trading agent that maximizes PnL (Profit & Loss) on Turbine. The agent with the highest returns takes home the grand prize. Prizes 1st Place: $500 - Highest PnL wins Why Turbine? Turbine is designed for speed, efficiency, and sophisticated trading strategies. This hackathon is your first look at what's possible when you combine prediction markets with autonomous agents. Who Should Join? AI/ML engineers and data scientists Quant traders and market enthusiasts. Developers interested in prediction markets. Anyone excited about autonomous trading systems.
What You'll Learn: How to build autonomous trading agents Prediction market mechanics and strategies Working with Turbine's API and infrastructure Market-making and risk management techniques Event Details Bring your laptop, your trading ideas, and your competitive spirit. We'll provide the platform, the data, and the challenge. You bring the innovation. Let's see who can build the smartest trading agent. See you there! Sponsors Turbine – High-performance DeFi prediction markets built for speed and sophisticated trading strategies. Trustware – Universal deposit and routing layer for cross-chain transactions across 70+ blockchains. Recently launched SDK enables deposits and dynamic routing into dApps from any asset on any chain.
Judge Accessibility
Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10
Top signals
Organizer email available
Student-run event
Actively looking for judges
Organizers
Alex Johnson
alex@example.org
Jamie Rivera
jamie@example.org
Sam Chen
sam@example.org
Estimated Audience
Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech
Technical Focus
AI95%
Web80%
Mobile25%
Industries
Healthcare
Education
Climate
Technologies
Python
React
OpenAI
Why this estimate
• Hosted by a university
• Open to students
• MLH member event
Estimate inferred from event metadata, not actual attendee data.