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

Tracks

  • Groking Timeseries & Sequential Data

    Techniques, practices, and approaches, including image recognition, NLP, predictions, & modeling.

  • Deep Learning in Practice

    Deep learning lessons using Tensorflow, Keras, PyTorch, Caffe including use cases on machine translation, computer vision, & image recogition.

  • AI Meets the Physical World

    Where AI touches the physical world, think drones, ROS, NVidia, TPU and more.

  • Papers to Production: CS in the Real World

    Groundbreaking papers make real world impact.

  • Solving Software Engineering Problems with Machine Learning

    Anomaly detection, ML in IDE's, bayesian optimization for config. Machine Learning techniques for more effective software engineering.

  • Predictive Architectures in the Real World

    Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix.