Speaker: Deepak Chandramouli

Analytics Tech Lead @PayPal

Deepak has over 13 years of experience in Data Engineering & 5 years of expertise building scalable data solutions in the Big Data space. He worked on building Apache Spark based Foundational Big Data Platform during the incubation of PayPal's Data lake. He has applied experience in implementing spark based solutions across several types of No-SQL, Key-Value, Messaging, Document based & relational systems. Deepak has been leading the initiative to enable access to any type of storage on Spark via - unified Data API, SQL, tools & services, thus simplifying analytics & large-scale computation-intensive applications.

Find Deepak Chandramouli 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.