Important Links
Problem Statement
Raw DOCX to Publication-Ready Manuscript Automation
Background
In academic publishing, authors frequently submit raw .docx manuscripts without proper formatting. Editorial teams then spend considerable time manually converting these files into final, publication-ready documents, leading to delays, higher operational costs, and formatting inconsistencies.
The Challenge
Design an AI-driven software tool or application that converts an author’s unformatted DOCX manuscript into a fully formatted, publication-ready final copy using predefined journal or conference templates, with minimal or no manual intervention.
Key Requirements
The solution should:
- Accept raw DOCX uploads
- Automatically format title, author details, abstract, headings, and paragraphs
- Correctly handle tables, figures, captions, and references
- Apply page layout rules (margins, headers/footers, page numbering)
- Export the final output as formatted DOCX (PDF optional)
Deliverables
Participants should submit:
- System workflow and architecture
- Formatting logic or template rules
- Prototype or wireframes (preferred)
- Sample before–after manuscript output
Goal: Reduce manual formatting effort and deliver fast, accurate, consistent, and scalable publication-ready manuscripts using AI-driven IT solutions.
Round 1
Team Registration & Domain Selection (PPT Saved as PDF to submit)
Hackathon Submission Window: 02.01.2026 - 31.01.2026
Round 1 PPT Submission : 02.01.2026 - 31.01.2026
Round 1 Presentations : 07.02.2026 - 08.02.2026
Round 1 Results : 11.02.2026
Round 2
Submission & Showcase (PPT Presentations)
