Data Science Conference Paper Submission Form

Submit Your Data Science Research to Our Conference

Present your latest machine learning and data science research at our conference with this streamlined paper submission form. Whether you're showcasing a breakthrough algorithm, novel dataset application, or advanced model architecture, our submission process makes it easy to share your work with the research community.

This data science conference paper submission form is designed specifically for researchers, data scientists, and ML engineers who need to provide comprehensive technical details about their algorithms, training methodologies, and model performance. Built with Paperform, it captures everything from abstract and methodology to detailed performance metrics and feature importance analysis—all in one professional, easy-to-complete form.

Why Paperform is perfect for academic and conference submissions:

Conference organizers can customize conditional logic to show different fields based on research type (supervised learning, unsupervised learning, reinforcement learning), automatically route submissions to the appropriate review track, and collect all supplementary materials in one place. With Paperform's file upload capabilities, authors can attach datasets, code repositories, and supplementary figures directly within the submission.

After submission, use Stepper (stepper.io) to automate your review workflow—automatically assign papers to reviewers based on research area, send status update emails, track revisions, and notify authors of acceptance decisions. This creates a seamless end-to-end conference management experience.

For multi-track conferences or recurring annual events, Paperform's template system and Agency+ features let you duplicate and customize forms for different tracks while maintaining consistent branding across your conference series. Plus, with SOC 2 Type II compliance and data residency controls, you can ensure that research submissions and intellectual property are handled securely.