The hackathon is organised with the objective of fostering innovation, interdisciplinary problem-solving, and hands-on technical competence among students. The event provides a structured platform for participants to ideate, design, prototype, and present technology-driven solutions aligned with emerging and industry-relevant domains.

Each hackathon will be conducted for a duration of 6 hours, with separate registrations to ensure focused participation and effective mentoring. Approximately 50 teams will participate in each domain, with each team comprising a minimum of two and a maximum of three participants.

Problem Statements

Track 1: AI for Personalized & Preventive Healthcare

1. Build a lightweight AI model that predicts disease risk using simulated or publicly available health, lifestyle, or wearable datasets.

2. Develop a rule-based or ML-based personalized care or wellness recommendation system using patient profiles.

3. Create an early-warning analytics dashboard that flags potential health deterioration using time-series health data.

4. Creative: Design any computer-based AI prototype that personalizes prevention or healthcare decisions using available data.

Track 2: AI for Diagnostics & Clinical Decision Support

1. Prototype an explainable AI model that assists diagnosis using open medical imaging or tabular clinical datasets.

2. Build a simplified multimodal diagnostic system combining at least two data types (e.g., symptoms + labs, image + metadata).

3. Create a clinician-support interface that presents AI predictions with confidence scores and explanations.

4. Creative: Propose and prototype a novel software-only AI tool that improves diagnosis or clinical decision-making.

Track 3: Computational Biology & Bioinformatics

1. Develop an AI or statistical model to analyze genomic, proteomic, or biological sequence data from public repositories.

2. Build a computational pipeline that integrates multi-omics or biological datasets to extract disease-related insights.

3. Use AI or simulations to model a biological pathway, interaction network, or cellular behavior.

4. Creative: Create a software-based computational biology solution that translates biological data into healthcare insights.

Track 4: AI in Drug Discovery & Biotechnology

1. Prototype an AI model for virtual drug screening, target prioritization, or molecule scoring using open datasets.

2. Build a computational drug-repurposing model that links existing drugs to new disease indications.

3. Create a data-driven simulation or dashboard that improves clinical trial design or patient selection.

4. Creative: Design a computer-only AI prototype addressing any biotech or drug discovery challenge.

Track 5: Human Performance, Biohacking & Longevity

1. Analyze wearable or biosignal datasets to generate insights or recommendations for performance or health improvement.

2. Build a simple aging or longevity risk model using publicly available biomarker or lifestyle data.

3. Create a software-based AI tool for mental health, stress detection, or cognitive performance monitoring.

4. Creative: Propose a novel biohacking or longevity-focused AI concept that runs entirely on a computer.

Track 6: Healthcare Systems, Privacy & Responsible Bio-AI

1. Prototype a privacy-preserving ML workflow (e.g., federated learning simulation, anonymization, synthetic data).

2. Build an AI model or dashboard that improves hospital operations, scheduling, or resource allocation using sample data.

3. Create an explainability or bias-detection tool for healthcare AI models.

4. Creative: Design a responsible, software-only Bio-AI solution that improves accessibility, efficiency, or trust in healthcare systems.

Hackathon Constraint

• This is a 6-hour, computer-only hackathon.

• All solutions must be software-based and demonstrable using code, simulations, public, or synthetic datasets.

• Any hardware, sensors, or physical devices must be arranged independently by participants.

• Hardware usage will not be provided or supported by organizers.