ICDM Invited Speakers

ICDM 2023

• Ruqian Lu (CAS), Chinese Academy of Sciences, Title: Big Data, Big Knowledge, Big Intelligence
• Leszek Rutkowski (Academia Europaea, PAS), Systems Research Institute of the Polish Academy of Sciences and AGH University of Science and Technology, Title: Stream Data Mining: From Sliding Windows to New Paradigm of Deep Neural Network Learning Methodology
• Jie Tang (F'IEEE, F'ACM, F'AAAI), Tsinghua University, Title: From GLM-130B to ChatGLM

ICDM 2022

• Vipin Kumar (F'IEEE, F'ACM, F'AAAS), University of Minnesota, Title: Knowledge-Guided Machine Learning: A New Framework for Accelerating Scientific Discovery and Addressing Global Environmental Challenges
• Cynthia Rudin (F'AAAI), Duke University, Title: Do Simpler Machine Learning Models Exist and How Can We Find Them?
• Eric P. Xing, Carnegie Mellon University, Title: On Learning, Meta-Learning, and "Lego-Learning" - Theory, System, and Engineering

ICDM 2021

• Jian Pei (F'RSC, F'IEEE, F'ACM), Simon Fraser University, Title: Towards Trustworthy Data Science: Interpretability, Fairness and Marketplaces
• Masashi Sugiyama (Japan Academy Medal), The University of Tokyo, Title: Towards Robust Machine Learning: Weak Supervision, Noisy Labels, and Beyond
• Svetha Venkatesh (F'AAS, F'ATSE), Deakin University, Title: Sample Efficient AI with Applications in Health Care and Advanced Manufacturing

ICDM 2020

• Sepp Hochreiter, Johannes Kepler University of Linz, Title: Modern Hopfield Networks
• Diane Cook (F'EEE, F'NAI), Washington State University, Title: Constructing a Human Digital Twin
• Xuedong Huang (F'IEEE, F'ACM), Microsoft, Title: XYZ-Code ¨C A Holistic Representation to Advance Integrative AI

ICDM 2019

• Ronald Fagin (NAE), IBM Research Almaden, Title: Applying Theory of Data to Practice
• Joseph Halpern (NAE), Cornell University Title: Actual Causality
• Jiawei Han (F'IEEE, F'ACM), University of Illinois at Urbana-Champaign, Title: Embedding-Based Text Mining: A Frontier in Data Mining

ICDM 2018

• Ramamohanarao (Rao) Kotagiri (F'AAS, F'AATSE), University of Melbourne, Australia
• C. Mohan (NAE), IBM Almaden Research Center, USA
• Xindong Wu (F'IEEE, F'AAAS), Hefei University of Technology, China

ICDM 2017

• Leslie Valiant (Turing Award, 2010; NAS), Harvard University, USA
• Michael J. Franklin (F'ACM), University of Chicago, USA
• Aidong Zhang (F'IEEE), State University of New York at Buffalo, USA

ICDM 2016

• Rakesh Agrawal (NAE), Data Insights Laboratories, USA.
• Yoshua Bengio (Turing Award, 2018), University of Montreal, Canada.
• Elisa Bertino (F'IEEE, F'ACM), Purdue University, USA.

ICDM 2015

• Robert F. Engle (Nobel Prize for Economics, 2003; NAS), New York University, USA
• Michael I. Jordan (NAS, NAE, AAAS, F'AAAS), University of California, Berkeley, USA
• Lada Adamic, Facebook, Inc., USA

ICDM 2014

• Wen Gao (CAE), Peking University, China
  Title: Towards Mobile Visual Search
• Johannes Gehrke, Microsoft and Cornell University, USA
  Title: Ten Research Challenges in Data Science
• Vipin Kumar, University of Minnesota, USA
  Understanding Global Change: Opportunities and Challenges for Data Driven Research

ICDM 2013

• Alexander Tuzhilin, Stern School of Business, New York University, USA
  Title: Opportunities and Challenges Facing Recommender Systems: Where Can We Go from Here?
• Joydeep Ghosh, University of Texas, Austin, USA
  Title: Predictive Healthcare Analytics under Privacy Constraints
• Jianchang (JC) Mao, Microsoft, USA
  Title: Large-scale Learning in Computational Advertising

ICDM 2012

• Bernhard Scholkopf, Max Planck Institute, Germany
  Title: On Causal and Anticausal Learning
• Jure Leskovec, Stanford University, USA
  Title: Mining Massive Online Networks: Challenges and Opportunities
• Martin Krzywinski, Genome Sciences Centre, Canada
  Title: Needles in Stacks of Needles

ICDM 2011

• Cynthia Dwork (NAS, NAE, AAAS), Microsoft Research, USA,
  Title: The Promise of Differential Privacy
• C. Lee Giles, Pennsylvania State University, USA,
  Title: Data Mining and Information Extraction for CiteSeerX and Friends
• Renie J. Miller (Royal Society of Canada), University of Toronto, Canada,
  Title: On Schema Discovery

ICDM 2010

• Christos Faloutsos, Carnegie Mellon University, USA:
  Mining Billion-node Graphs: Patterns, Generators and Tools
• Geoff McLachlan (Fellow, Australian Academy of Science), University of Queensland, Australia:
  Assessing the Significance of Groups in High-Dimensional Data
• Xindong Wu, University of Vermont, USA:
  10 Years of Data Mining Research: Retrospect and Prospect

ICDM 2009

• Stephen Boyd (NAE), Stanford University, USA
• Jamie Callan, Carnegie Mellon University, USA
• Vipin Kumar, University of Minnesota, USA

ICDM 2008

• Serge Abiteboul, INRIA Saclay and University Paris-Sud, France
• Ravi Kumar, Yahoo! Research, USA
• Harvey J. Miller, University of Utah, USA

ICDM 2007

• Joseph M. Hellerstein, UC Berkeley, USA
• Tamara Kolda, Sandia National Labs, USA
• Ian Witten, University of Waikato, New Zealand

ICDM 2006

• Ian Foster, Computation Institute Argonne National Laboratory & University of Chicago, USA.
  Service-Oriented Science: Scaling eScience Impact
• Raghu Ramakrishnan, Yahoo! Research, USA.
  Exploratory Mining in Cube Space
• Weixiong Zhang, Washington University in St. Louis, USA.
  Data Mining Methods for Modeling Gene Expression Regulation and Their Applications

ICDM 2005

• John F. Elder IV, Elder Research, Inc., USA
  "Top 10 Data Mining Mistakes"
• Raj Reddy (Turing Award, 1994; NAS; NAE; AAAS; CAE; INAS; INAE), Carnegie Mellon University, USA
  "The Million Book Digital Library Project: Research Problems in Data Mining and Discovery"
• Sunita Sarawagi, IIT Bombay, India
  "Graphical models for structure extraction and information integration"
• Arie Shoshani, Lawrence Berkeley National Laboratory, USA
  "Efficient Indexing Technology for Data Mining of Scientific Data"

ICDM 2004

• Wray Buntine, Helsinki Institute of Information Technology, Finland
  Open-source Search Engines: A Data Mining Platform
• David Hand (Fellow, British Academy), Imperial College, UK
  Deception, Distortion, and Discovery: Data Quality in Data Mining
• Thorsten Joachims, Cornell University, USA
  Learning to Predict Complex Objects
• Ming Li (Royal Society of Canada), University of Waterloo, Canada
  Faster and More Sensitive Homology Search

ICDM 2003

• Thomas G. Dietterich, Oregon State University, USA:
  Sequential Supervised Learning: General Methods for Sequence Labeling and Segmentation
  [Slides in PDF]
• Usama M. Fayyad, DMX Group, LLC, USA:
  Grand Challenges on the Road to Practical Data Mining Systems
• Heikki Mannila (Academy of Finland), University of Helsinki, Finland:
  Global Structure from Sequences
  [Slides in PS]
• Gene W. Myers (NAE), University of California, Berkeley, USA:
  Pattern Discovery for Genomics
  [Slides in PPT]
• Philip S. Yu, IBM T.J. Watson Research Center, USA:
  Real-Time Monitoring and Surveillance using Data Stream Mining

ICDM 2002

• Jiawei Han, University of Illinois at Urbana-Champaign, USA
• Satoru Miyano, University of Tokyo, Japan
• Hiroshi Motoda, Osaka University, Japan
• Stephen Muggleton, Imperial College, UK
• Steve Smale (Fields Medal, 1966), University of California at Berkeley, USA
• Jeffrey D. Ullman (NAE), Stanford University, USA

ICDM 2001

• Jerome H. Friedman (NAS, NAE, AAAS), Stanford University, USA:
  Predictive Data Mining with Multiple Additive Regression Trees
• Jim Gray (The 1999 Turing Award Winner), Microsoft Research, USA:
  The World Wide Telescope: Mining the Sky
• Pat Langley, Institute for the Study of Learning and Expertise, USA
  Knowledge and Data in Computational Scientific Discovery
• Benjamin W. Wah (2001 President, IEEE Computer Society), University of Illinois, Urbana-Champaign, USA:
  Intelligent Mining for Time Series Predictions