Course Description

 

Keynotes

  • Courses



  • Maria Girone
    (European Organization for Nuclear Research) [-]
    Big Data Challenges at the CERN HL-LHC


    Lisa Schurer Lambert
    (Oklahoma State University) [-]
    Research Methods as a Lens: How We Know What We Know


    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


    Michael X. Cohen
    (Radboud University Nijmegen) [introductory]
    Dimension Explosion and Dimension Reduction in Brain Electrical Activity


    Ramez Elmasri
    (University of Texas, Arlington) [intermediate]
    Spatial, Temporal, and Spatio-Temporal Data


    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


    Christopher Hogue
    (Ericsson Inc.) [introductory/intermediate]
    Applied Information Theory for Scalable Database Schema and Query Templates


    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


    B.S. Manjunath
    (University of California, Santa Barbara) [introductory]
    Digital Media Forensics


    Wladek Minor
    (University of Virginia) [introductory/Advanced]
    Big Data in Biomedical Sciences


    José M.F. Moura
    (Carnegie Mellon University) [introductory]
    Graph Signal Processing


    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


    Karsten Reuter
    (Max Planck Society) [introductory/intermediate]
    Machine Learning for Materials and Energy Applications


    Ramesh Sharda
    (Oklahoma State University) [introductory/intermediate]
    Network-based Health Analytics


    Steven Skiena
    (Stony Brook University) [introductory/intermediate]
    Word and Graph Embeddings for Machine Learning