This hackathons is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.
Event Type
in person
This hackathon brings together senior tech leaders, builders and students to work for 24 hours on real world challenges, using AI first development and vibe coding principles. Registration is done by the team leader. As a team leader, you will: – lead a small, cross functional team through a full build cycle (maxium 5) – make real prioritization and tradeoff decisions under time pressure – work hands on, not as a reviewer or judge – collaborate with partners on concrete business and societal use cases. By the end of the hackathon, each team is expected to deliver: – a working demo – a clear problem framing and value proposition – a shared learning experience across seniority levels. The event is sponsored by Stripe and Sameday, supported by the Swedish Embassy and powered by Lovable. If you believe leadership is something you practice by building with your team, this is your invitation ☕️. Disclaimer: Tracks per Team will be allocated by the organizers to ensure coverage of all areas and balanced teams. We will take your preferences into account, but we cannot guarantee them 100%.
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.