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Global South AI Safety Hackathon: Da Nang

lumaHosted on Luma

Fetched about 8 hours ago

Friday, June 19, 2026

to Sunday, June 21, 2026

•

2 days long

Artificial IntelligenceSocial ImpactBlockchain

Event Type

in person

14

Participants

1

Est. Projects

We're hosting a Da Nang hub for the Apart Global South AI Safety Hackathon!Build AI safety tools, evaluations, and policy research over the course of a weekend. This hackathon is not about bringing AI safety to the Global South. It is about bringing the Global South into AI safety. Find collaborators to work on real research ideasGet compute credits to work on your ideasGet feedback from expertsStand a chance to win $1000 ​Streamed talks from (but not limited to): Sang Truong: Stanford AI Lab, Google DeepMindTan Zhi Xuan: MIT, Professor at NUS Department of Computer ScienceJuan Felipe Cerón Uribe: OpenAIMark Gaffley: Global Centre on AI Governance Schedule: Friday - Virtual Kick-offSaturday - Research developmentSunday - Final developmentProject submission deadline: TBA If you want to participate at the in-person event in Da Nang, you will need to register for this Luma event. You can participate remotely by registering on the Apart website.In Hanoi instead? Check out Hanoi jam site here.In Ho Chi Minh City instead? Check out HCMC jam site here.- Cover image inspired from Polytope by Richard A Carter - https://betterimagesofai.org - CC BY 4.0

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