Industry Track

Speakers

  • Towards operational transfer application of Deep Reinforcement Learning to Large Area Coverage using Earth Observation satellite scheduling
    Adrien Hadj-Salah
    IRT Saint-Exupéry; Airbus Defence & Space

  • CD-SEM image denoising with Unsupervised Machine Learning for extracting Line-Edge and Line-Width roughness
    Bappaditya Dey
    IMEC; The Center for Advanced Computer Studies (CACS), University of Louisiana at Lafayette

  • Visual Recommendations at bol.com
    Barrie Kersbergen
    bol.com

  • Finding Data Scientist Challenges in using ML Platform
    Chandramohan Meena, Rajesh Shreedhar Bhat
    Walmart Labs

  • Human-Machine collaboration in semiconductor manufacturing: Opportunities and Challenge
    Dimitra Gkorou
    ASML

  • Object identification system based on a triplet loss architecture
    Diogo Costa
    Bosch Car Multimedia Portugal S.A., University of Minho

  • Voice Assistant ASR Bootstrapping
    Manuel Giollo
    Amazon Alexa

  • The Challenges of Setting ML in Production
    Maryse Colson, Sabri Skhiri
    EuraNova

  • Intent classification in Deutsche Telekom's Hallo Magenta Voice Assistant
    Mattheus van Iterson, Ralf Kirchherr, Sofia Nikitaki, Leonard Plotkin, Andrea Schnall
    Deutsche Telekom AG

  • The Flemish AI Research Program
    Sabine Demey
    imec-UGent

  • Text Extraction from Product Images
    Rajesh Bhat
    Walmart Labs

  • Distributional Regression for Cost-Optimized Demand Forecasting in e-Grocery
    Robert Pesch
    inovex GmbH

  • Active two-phase learning for classification of large datasets with extreme class-skew
    Tarun Gupta
    Amazon

  • Normalizing our norms for Machine Learning development processes
    Turan Bulmus
    Google Amsterdam

  • IDLab: Why data are the most important assets you have
    Wouter Haerick
    IDLab, UGent-imec