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WEEX AI Hackathon Preliminary Round Forked Entry

dorahacksHosted on DoraHacks

Fetched 6 months ago

Friday, January 2, 2026

to Sunday, January 18, 2026

•

2 weeks long

Artificial IntelligenceFintechBlockchainWeb DevelopmentSocial Impact

Event Type

online

110

Participants

USD1,880,000

Prize Pool

9

Est. Projects

AI Wars : WEEX Alpha Awakens Welcome to the future of AI-powered trading! The AI Wars : WEEX Alpha Awakens organized by WEEX Labs, blends the realms of Artificial Intelligence, quantitative finance, and Web3 to spark real-world innovation in algorithmic trading. This global AI trading hackathon takes place from November 20, 2025 to March 3, 2026, based in Dubai and accessible worldwide. The event welcomes developers, researchers, professionals, and enterprises to compete for a share of 1,880,000 USDT in prizes, including a Bentley Bentayga S for the champion. WEEX AI Hackathon Preliminary Round Forked Entry is now open, offering a second chance for participants who missed the early registration deadline on December 31, 2025. The forked entry will open until January 18, 2026, at 23:59 (UTC+8), after which all eligible participants will advance to the preliminary round, running for two weeks from January 19 to February 2. Top-performing teams from the preliminary round will then progress to the finals, making this the final opportunity to join the competition before it officially begins.

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.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct