Competition Rules

Guidelines for creating and registering your team:

• Teams must consist of 1-4 members. Solo participants are welcome.
• Team formation must be completed by September 30, 2025.
• Team members can be from different organizations, schools, or countries.
• Participants can only be part of one team.

Important deadlines and submission requirements:

• All phase wise work must be done during the hackathon period (August 4 – November 15, 2025).
• Submissions are due by 11:59 PM UTC+14:00 on submission deadline of phase 1 and 2. Late submissions will not be accepted.
• Each submission must include source code in prescribed format.
• Code must be submitted through GlacierHack platform.
• Teams must present their solution during the InGARSS 2025 if selected.

Rules regarding code, libraries, and development practices:

• Code must be written in Python with in exact format, which will be specified during release of phase I and II problem statement.
• Teams may use open-source libraries and frameworks, with proper attribution.
• Pre-written code may only be used if it is publicly available to all participants.
• Teams must build their projects from scratch during the hackathon.
• API usage is strictly prohibited.
• Teams are allowed to use language models like ChatGPT for code generation with proper citation.

Ownership and rights to the projects developed:

• Participants retain full ownership of what they build during the hackathon.
• By participating, teams grant GlacierHack organizers the right to showcase their projects for promotional purposes.
• Teams are responsible for ensuring their submissions don't infringe on existing IP rights.
• If using datasets provided by sponsors, teams must adhere to the specified usage terms.
• Open-source contributions are encouraged but not required.

Guidelines for handling data and ensuring privacy:

• Teams must handle any personal or sensitive data in compliance with relevant regulations (GDPR, CCPA, etc.).
• Use of third-party datasets must be properly cited and comply with their terms of use.
• Solutions should prioritize user privacy and data security.
• Teams must disclose all data sources used in their projects.
• Any AI models developed should be documented regarding potential biases and limitations.