About the conference
KDD is the flagship of data mining and applied data science, distinctive for its strong Applied Data Science track where industrial deployments are first-class research contributions. Graph mining, recommender systems, anomaly detection, and scalable ML are core territory.
Papers are typically due in February for the August conference. The dual-track structure is worth exploiting deliberately: rigorous deployment stories that would struggle in a methods track are exactly what the ADS track wants.