Maria Girone (European Organization for Nuclear Research) - Big Data Challenges at the CERN HL-LHC
Paolo Addesso (University of Salerno) [introductory/intermediate] Data Fusion for Remotely Sensed Data
Thomas Bäck & Hao Wang (Leiden University) [introductory/intermediate] Data Driven Modeling and Optimization for Industrial Applications
Paul Bliese (University of South Carolina) [introductory/intermediate] Using R for Mixed-effects (Multilevel) Models
Altan Cakir (Istanbul Technical University) [intermediate] Big Data Analytics with Apache Spark
Edward Chang (Stanford University) [intermediate] Artificial Intelligence for Disease Diagnosis and Precision Surgery
Michael X. Cohen (Radboud University Nijmegen) [introductory] Dimension Explosion and Dimension Reduction in Brain Electrical Activity
Ian Fisk (Flatiron Institute) [introductory] The Infrastructure to Support Data Science
Michael Freeman (University of Washington) [intermediate] Interactive Data Visualization Using D3 + Observable
David Gerbing (Portland State University) [introductory] Derive Meaning from Data with R Visualizations
Yifan Hu (Yahoo Research) [introductory/advanced] Data Visualization and Machine Learning
Rafael Irizarry (Harvard University) [introductory] Data Science for Statisticians (tidyverse, ggplot, wrangling)
Wagner A. Kamakura (Rice University) [intermediate] Advanced Business Analytics using Excel Addins
Ravi Kumar (Google) [intermediate/advanced] Clustering for Big Data
Victor O.K. Li (University of Hong Kong) [intermediate] Deep Learning and Applications
Panos Pardalos (University of Florida) [intermediate/advanced] Optimization and Data Sciences Techniques for Large Networks
Valeriu Predoi (University of Reading) [introductory] A Beginner's Guide to Big Data Analysis: How to Connect Scientific Software Development with Real World Problems
Alexandre Vaniachine (VirtualHealth) [intermediate] Open-source Columnar Databases
Sebastián Ventura (University of Córdoba) [intermediate/advanced] Supervised Descriptive Pattern Mining
Xiaowei Xu (University of Arkansas, Little Rock) [introductory/advanced] Deep Learning for Text Mining