Speaker: Dor Kedem

Senior Data Scientist @ING Nederland

Dor has over a decade of experience developing big data products for security industries, financial markets and banking industries. His research on metric learning and cost-sensitive learning has earned him publications in NIPS, AISTATS and a monetary prize in Cha-Learn competitions. As a data scientist at ING domestic banking, he is involved with multiple projects modelling consumer and market behavior, optimizing business and IT processes.

Find Dor Kedem at

Proposed Tracks

  • Real-World Data Engineering

    Showcasing DataEng tech and highlighting the strengths of each in real-world applications.

  • Deep Learning Applications & Practices

    Deep learning lessons using Tensorflow, Keras, PyTorch, Caffe across machine translation, computer vision.

  • AI Meets the Physical World

    The track where AI touches the physical world, think drones, ROS, NVidea, TPU and more.

  • Data Architectures You've Always Wondered About

    How did they do that? Real-time predictive pipelines at places like Uber, Self-Driving Cars at Google, Robotic Warehouses from Ocado in the UK, are all possible examples.

  • Applied ML for Software

    Practical machine learning inside the data centers and on software engineering teams.

  • Time Series Patterns & Practices

    Stocks, ad tech/real-time bidding, and anomaly detection. Patterns and practices for more effective Time Series work.