Full Papers
Original, high-quality research contributions with substantial technical depth and experimental validation.
Databases/CORE A*
SIGKDD 2027
ACM Knowledge Discovery and Data Mining
KDD 2027 is the premier international conference on knowledge discovery and data mining, bringing together researchers and practitioners to present cutting-edge work in data science, machine learning, and their applications. The conference features multiple tracks including a Research Track and an Applied Data Science (ADS) Track, emphasizing both theoretical advances and real-world impact.
Key deadlines
Verified September 9, 2026Abstract registration
July 20, 2026
AoE
Full paper
July 27, 2026
AoE
Conference timeline
Submission and decisions
Abstract registrationKey deadline
July 20, 2026 · AoE
Full paperKey deadline
July 27, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short Papers
Concise presentations of novel ideas, early-stage work, or focused case studies with clear contributions.
Applied Data Science (ADS) Track Submissions
Practical, real-world applications of data science with emphasis on implementation, impact, and lessons learned.
Research areas in scope
01
Research Track Topics
Machine LearningDeep LearningReinforcement LearningGraph Mining and Network AnalysisData Mining AlgorithmsFairness, Accountability, Transparency, and Ethics in AIPrivacy-Preserving Data MiningTemporal and Spatial Data MiningNatural Language Processing and Text MiningRecommendation SystemsAnomaly DetectionScalable and Distributed Data MiningData Integration and QualityHuman-in-the-Loop Data ScienceExplainable AIAI for Science and HealthcareData VisualizationBig Data Analytics
02
Applied Data Science (ADS) Track Topics
Real-world applications of data science in industryDeployment of ML systems in productionData engineering and pipelinesOperationalizing AI/MLCase studies in data-driven decision makingData science in healthcare, finance, energy, transportation, and public policyTools, platforms, and frameworks for applied data scienceChallenges in scaling data science projectsEthical and societal impacts of deployed systems
Policies worth checking twice
- All submissions must be anonymized for double-blind review.
- Papers must not be under review at any other conference or journal during KDD 2027 review period.
- Dual submission to KDD and other venues is strictly prohibited.
- Authors must submit a statement on the use of AI-assisted tools in the preparation of the paper.
- Camera-ready versions must adhere to strict page limits (10 pages for full papers, 6 pages for short papers, excluding references).
- Author lists and affiliations cannot be changed after the submission deadline without explicit permission.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Official conference siteResearch Track: Call for PapersApplied Data Science (ADS) Track: Call for PapersDatasets and Benchmarks Track: Call for PapersAI for Sciences Track: Call for PapersFAQ for Resubmission
Last verified September 9, 2026