Speaker: Eugene Kirpichov

Cloud Dataflow Staff SE @Google

Eugene Kirpichov is a Staff Software Engineer on the Cloud Dataflow team at Google, where he works on the Apache Beam programming model and APIs. Previously, he worked on Cloud Dataflow’s autoscaling and straggler elimination techniques. Eugene is interested in programming language theory, data visualization, and machine learning.

Find Eugene Kirpichov 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.