Conventional Tutorials

We have a fantastic lineup of hands-on and conventional tutorials to be held in conjunction with KDD 2017.

Check back as we get closer to the conference for more detailed program information.

Title Organizers
Large Scale Hierarchical Classification: Foundations, Algorithms and Applications

Huzefa Rangwala (George Mason University)
Azad Naik (Microsoft Corporation)

Mining Entity-Relation-Attribute Structures from Massive Text Data

Jingbo Shang (University of Illinois, Urbana-Champain)
Xiang Ren (University of Illinois, Urbana-Champain)
Meng Jiang (University of Illinois, Urbana-Champain)
Jiawei Han (University of Illinois, Urbana-Champain)

Deep Learning for Personalized Search and Recommender Systems

Ganesh Venkataraman
Nadia Fawaz
Saurabh Kataria
Benjamin Le
Liang Zhang
(LinkedIn Corp.)

A/B Testing at Scale: Accelerating Software Innovation

Alex Deng (Microsoft)
Pavel Dmitriev (Microsoft)
Somit Gupta (Microsoft)
Ron Kohavi (Microsoft)
Paul Raff (Microsoft)
Lukas Vermeer (

Learning Representations of Large-scale Networks

Jian Tang
Cheng Li
Qiaozhu Mei

Network Embedding- Enabling Network Analytics and Inference in Vector Space

Peng Cui (Tsinghua University)
Jian Pei (Simon Fraser)
Wenwu Zhu (Tsinghua University)

Smart Analytics for Big Time-series Data

Yasushi Sakurai (Kumamoto University)
Yasuko Matsubara (Kumamoto University)
Christos Faloutsos (Carnegie Mellon University)

Safe Data Analytics: Theory, Algorithms, and Applications

Jun Huan (KU)

Chao Lan (KU)

Xiaoli Li (KU)

Recent Advances in Feature Selection: A Data Perspective

Jundong Li (Arizona State University)
Jiliang Tang (Michigan State University)
Huan Liu (Arizona State University)

Making Better Use of the Crowd

Jennifer Wortman Vaughan (Microsoft Research)

Time Series data Mining Using the Matrix Profile: A Unifying View of Motif Discovery, Anomaly Detection, Segmentation, Classification, Clustering and Similarity Joins

Abdullah Mueen (University of New Mexico)
Eamonn Keogh (University of California Riverside)

Data Mining in Unusual Domains with Information-rich Knowledge Graph Construction, Inference and Search

Mayank Kejriwal (USC-ISI
Pedro Szekely (USC-ISI)

A Critical Review of Online Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries

Alexandra Olteanu (IBM Research, US)
Emre Kıcıman (Microsoft Research, US)
Carlos Castillo (Eurecat, Spain)
Fernando Diaz (Microsoft Research, US)

Non-IID Learning in Big Data

Longbing Cao (UTS)
Philip Yu (UIC)
Guangsong Pang (UTS)
Chengzhang Zhu (UTS)

System Event Mining: Algorithms and Applications

Tao Li (Florida International University, USA)
Larisa Shwartz (IBM T.J. Watson Research Center, USA)
Genady Ya. Grabarnik (St. John's University, USA)

IoT in Practice: Case Studies in Data Analytics, with Issues in Privacy and Security

Albert Bifet (Telecom ParisTech)
Latifur Khan (University of Texas at Dallas)
Joao Gama (University of Porto)
Wei Fan (Baidu Research Big Data Lab)

Context-Rich Recommendation via Information Network Analysis Approach

Yizhou Sun (University of California, Los Angeles)
Xiang Ren (University of Illinois at Urbana-Champaign)
Hongzhi Yin (The University of Queensland, Australia)

Urban Computing: Enabling Intelligent Cities with Big Data

Yu Zheng (Microsoft Research)

From Theory to Data Product: Applying Data Science Methods to Effect Business Change

Danielle Leighton (T4G Limited)
Lindsay Brin (T4G Limited)
Janet Forbes (T4G Limited)

Data-Driven Approaches towards Malicious Behavior Modeling

Meng Jiang (University of Notre Dame)
Srijan Kumar (Stanford University)
VS Subrahmanian (University of Maryland, College Park)
Christos Faloutsos (CMU)

Machine Learning for Survival Analysis: Theory, Algorithms and Applications

Chandan K. Reddy (Virginia Tech)
Yan Li (University of Michigan, Ann Arbor)

Athlytics: Data Mining and Machine Learning for Sports Analytics

Konstantinos Pelechrinis (University of Pittsburgh)
Evangelos Papalexakis (University of California, Riverside)
Benjamin Alamar (ESPN)