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
4
Participants
0
Est. Projects
About Binary Hacks 4.0:
Binary Hacks 4.0 is a 36-hour offline hackathon organized by The Binary Club, Department of Computer Science & Engineering (CSE). It is designed to bring together students, developers, designers, and innovators to collaborate, solve real-world challenges, and build impactful technology solutions.
Participants will work in teams, receive mentorship from industry experts, and showcase their ideas before a panel of judges. Whether you're a beginner or an experienced hacker, Binary Hacks 4.0 offers an excellent opportunity to learn, network, enhance your skills, and compete for exciting rewards.
Event Details:
Duration: 36 Hours
Dates: 21–22 September
Venue: CRC Hall 1 & Hall 2
Mode: Offline
Organizer: The Binary Club, Department of Computer Science & Engineering (CSE)
Perks:
Exciting Cash Prizes
Certificates for All Participants
Expert Mentorship
Networking Opportunities
Swag & Goodies
Hands-on Learning Experience
Opportunity to Build Innovative Solutions
Get ready for 36 hours of innovation, collaboration, coding, and creativity. Bring your ideas to life, challenge yourself, and be a part of one of the most exciting hackathons on campus!
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.