Schedule

Reception

Location: Aula Magna → Welcome

Location: Aula Magna, Wil van der Aalst - RWTH Aachen University ⊳ “Process Mining: A Very Different Kind of Machine Learning That Can Be Applied in Any Organization”     introductory/intermediate

Location: 155-2/3, Peter Rousseeuw - KU Leuven ⊳ “Anomaly Detection by Robust Methods”     introductory

Location: Aula Magna, Rory Smith - Monash University ⊳ “Learning from Data, the Bayesian Way”     introductory/intermediate

Location: 155-2/3, Jayanti Prasad - Embold Technologies ⊳ “Big Code”     introductory/intermediate

Lunch

Location: Aula Magna, Charles Elkan - University of California, San Diego ⊳ “A Rapid Introduction to Modern Deep Learning”     intermediate

Location: 155-2/3, Diego Calvanese - Free University of Bozen-Bolzano ⊳ “Virtual Knowledge Graphs for Data Integration”     introductory

Location: 155-5/6, Lior Rokach and Bracha Shapira - Ben-Gurion University of the Negev ⊳ “Recommender Systems”     introductory/intermediate

Location: Aula Magna, Wil van der Aalst - RWTH Aachen University ⊳ “Process Mining: A Very Different Kind of Machine Learning That Can Be Applied in Any Organization”     introductory/intermediate

Location: 155-2/3, Peter Rousseeuw - KU Leuven ⊳ “Anomaly Detection by Robust Methods”     introductory

Location: Aula Magna, Rory Smith - Monash University ⊳ “Learning from Data, the Bayesian Way”     introductory/intermediate

Location: 155-2/3, Jayanti Prasad - Embold Technologies ⊳ “Big Code”     introductory/intermediate

Location: (Remote) Aula Magna, Jeffrey Ullman - Stanford University ⊳ “Big-data Algorithms That Aren't Machine Learning”     introductory

Location: 155-2/3 → Open session I

Location: Aula Magna, Charles Elkan - University of California, San Diego ⊳ “A Rapid Introduction to Modern Deep Learning”     intermediate

Location: 155-2/3, Diego Calvanese - Free University of Bozen-Bolzano ⊳ “Virtual Knowledge Graphs for Data Integration”     introductory

Location: 155-5/6, Lior Rokach and Bracha Shapira - Ben-Gurion University of the Negev ⊳ “Recommender Systems”     introductory/intermediate

Location: Aula Magna, Wil van der Aalst - RWTH Aachen University ⊳ “Process Mining: A Very Different Kind of Machine Learning That Can Be Applied in Any Organization”     introductory/intermediate

Location: 155-2/3, Peter Rousseeuw - KU Leuven ⊳ “Anomaly Detection by Robust Methods”     introductory

Lunch

Location: Aula Magna, Rory Smith - Monash University ⊳ “Learning from Data, the Bayesian Way”     introductory/intermediate

Location: 155-2/3, Jayanti Prasad - Embold Technologies ⊳ “Big Code”     introductory/intermediate

Location: Aula Magna, Charles Elkan - University of California, San Diego ⊳ “A Rapid Introduction to Modern Deep Learning”     intermediate

Location: 155-2/3, Diego Calvanese - Free University of Bozen-Bolzano ⊳ “Virtual Knowledge Graphs for Data Integration”     introductory

Location: 155-5/6, Lior Rokach and Bracha Shapira - Ben-Gurion University of the Negev ⊳ “Recommender Systems”     introductory/intermediate

Location: Aula Magna, Hanan Samet - University of Maryland ⊳ “Sorting in Space: Multidimensional, Spatial, and Metric Data Structures for Applications in Spatial and Spatio-textual Databases, Geographic Information Systems (GIS), and Location-based Services”     introductory/intermediate

Location: 155-2/3, Sanchita Bhattacharya - University of California, San Francisco ⊳ “Big Data in Immunology: Sharing, Dissemination, and Repurposing”     introductory/advanced

Location: 155-5/6, Jaideep Srivastava - University of Minnesota ⊳ “Social Computing”     introductory/intermediate

Location: (Remote) Aula Magna, Jeffrey Ullman - Stanford University ⊳ “Big-data Algorithms That Aren't Machine Learning”     introductory

Dinner with strangers

Location: 155-2/3 → Employer session

Location: Aula Magna, Wladek Minor - University of Virginia ⊳ “Big Data in Biomedical Sciences”     introductory/advanced

Location: 155-2/3, Minos Garofalakis - Technical University of Crete ⊳ “Streaming Data Analytics”     intermediate/advanced

Location: Aula Magna, Hanan Samet - University of Maryland ⊳ “Sorting in Space: Multidimensional, Spatial, and Metric Data Structures for Applications in Spatial and Spatio-textual Databases, Geographic Information Systems (GIS), and Location-based Services”     introductory/intermediate

Location: 155-2/3, Sanchita Bhattacharya - University of California, San Francisco ⊳ “Big Data in Immunology: Sharing, Dissemination, and Repurposing”     introductory/advanced

Location: 155-5/6, Jaideep Srivastava - University of Minnesota ⊳ “Social Computing”     introductory/intermediate

Lunch

Location: Aula Magna, Wladek Minor - University of Virginia ⊳ “Big Data in Biomedical Sciences”     introductory/advanced

Location: 155-2/3, Minos Garofalakis - Technical University of Crete ⊳ “Streaming Data Analytics”     intermediate/advanced

Location: Aula Magna, Hanan Samet - University of Maryland ⊳ “Sorting in Space: Multidimensional, Spatial, and Metric Data Structures for Applications in Spatial and Spatio-textual Databases, Geographic Information Systems (GIS), and Location-based Services”     introductory/intermediate

Location: 155-2/3, Sanchita Bhattacharya - University of California, San Francisco ⊳ “Big Data in Immunology: Sharing, Dissemination, and Repurposing”     introductory/advanced

Location: 155-5/6, Jaideep Srivastava - University of Minnesota ⊳ “Social Computing”     introductory/intermediate

Location: Aula Magna → UNIVPM presentation

Location: Aula Magna → Round table

Dinner with strangers

Location: 155-2/3 → Open session II

Location: Aula Magna, Amr El Abbadi - University of California, Santa Barbara ⊳ “An Introduction to Blockchain”     introductory/intermediate

Location: 155-2/3, Bamshad Mobasher - DePaul University ⊳ “Context-aware Recommender Systems”     intermediate

Location: Aula Magna, Wladek Minor - University of Virginia ⊳ “Big Data in Biomedical Sciences”     introductory/advanced

Location: 155-2/3, Minos Garofalakis - Technical University of Crete ⊳ “Streaming Data Analytics”     intermediate/advanced

Lunch

Location: 155-2/3, Nitesh Chawla - University of Notre Dame ⊳ “Learning in the Presence of Class Imbalance and Changing Distributions”     intermediate/advanced

Location: 155-5/6, Craig Knoblock - University of Southern California ⊳ “Building Knowledge Graphs”     intermediate/advanced

Location: Aula Magna, Amr El Abbadi - University of California, Santa Barbara ⊳ “An Introduction to Blockchain”     introductory/intermediate

Location: 155-2/3, Bamshad Mobasher - DePaul University ⊳ “Context-aware Recommender Systems”     intermediate

Location: Aula Magna, Jiawei Han - University of Illinois, Urbana-Champaign ⊳ “From Unstructured Text to TextCube: Automated Construction and Multidimensional Exploration”     intermediate/advanced

Location: 155-2/3, Asim Roy - Arizona State University ⊳ “Hardware-based (GPU, FPGA based) Machine Learning That Exploits Massively Parallel Computing – An Overview of Concepts, Architectures and Neural Network Algorithm Implementation”     intermediate

Location: 155-5/6, Mayte Suárez-Fariñas - Icahn School of Medicine at Mount Sinai ⊳ “Meta-analysis Methods for High-dimensional Data”     intermediate/advanced

Location: (remote) Aula Magna → Ullman

Dinner with strangers

Location: 155-2/3 → Industrial session II (see Presentations)

Location: Aula Magna, Sheelagh Carpendale - Simon Fraser University ⊳ “Data Visualization”     introductory

Location: 155-2/3, Nitesh Chawla - University of Notre Dame ⊳ “Learning in the Presence of Class Imbalance and Changing Distributions”     intermediate/advanced

Location: 155-5/6, Craig Knoblock - University of Southern California ⊳ “Building Knowledge Graphs”     intermediate/advanced

Location: Aula Magna, Amr El Abbadi - University of California, Santa Barbara ⊳ “An Introduction to Blockchain”     introductory/intermediate

Location: 155-2/3, Bamshad Mobasher - DePaul University ⊳ “Context-aware Recommender Systems”     intermediate

Lunch

Location: Aula Magna, Jiawei Han - University of Illinois, Urbana-Champaign ⊳ “From Unstructured Text to TextCube: Automated Construction and Multidimensional Exploration”     intermediate/advanced

Location: 155-2/3, Asim Roy - Arizona State University ⊳ “Hardware-based (GPU, FPGA based) Machine Learning That Exploits Massively Parallel Computing – An Overview of Concepts, Architectures and Neural Network Algorithm Implementation”     intermediate

Location: 155-5/6, Mayte Suárez-Fariñas - Icahn School of Medicine at Mount Sinai ⊳ “Meta-analysis Methods for High-dimensional Data”     intermediate/advanced

Location: Aula Magna, Sheelagh Carpendale - Simon Fraser University ⊳ “Data Visualization”     introductory

Location: 155-2/3, Nitesh Chawla - University of Notre Dame ⊳ “Learning in the Presence of Class Imbalance and Changing Distributions”     intermediate/advanced

Location: 155-5/6, Craig Knoblock - University of Southern California ⊳ “Building Knowledge Graphs”     intermediate/advanced

Location: Aula Magna, Jiawei Han - University of Illinois, Urbana-Champaign ⊳ “From Unstructured Text to TextCube: Automated Construction and Multidimensional Exploration”     intermediate/advanced

Location: 155-2/3, Asim Roy - Arizona State University ⊳ “Hardware-based (GPU, FPGA based) Machine Learning That Exploits Massively Parallel Computing – An Overview of Concepts, Architectures and Neural Network Algorithm Implementation”     intermediate

Location: 155-5/6, Mayte Suárez-Fariñas - Icahn School of Medicine at Mount Sinai ⊳ “Meta-analysis Methods for High-dimensional Data”     intermediate/advanced