Speaker: Anjuli Kannan

Software Engineer @GoogleBrain

Anjuli Kannan is a senior software engineer at Google. She is a member of the Brain Team, which works to advance the field of machine intelligence through a combination of basic research, software (TensorFlow), and applications that improve people's lives. Anjuli is especially interested applications of machine learning to problems in natural language understanding. Recently she was a core member of the team that brought the Smart Reply feature to Inbox by Gmail. Launched in 2015, Smart Reply was the first Google-scale application to effectively apply recurrent neural networks in language understanding, as well as the first to leverage Google's open-source TensorFlow.

Find Anjuli Kannan 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.