Speaker: Anisha Nainani

Software Engineer @Paypal

Anisha has 2 plus years of experience in building big data platforms. Anisha did her Masters in Computer Science from University of Texas at Dallas in 2014 with a focus on Data Engineering. After that she joined Paypal as a Software Engineer, where she helped build a compute framework to provide unified experience to users to run SQL queries on any compute engine such as spark, presto, hive. Anisha is also the core contributor of PayPal Gimel’s HBASE & Aerospike APIs - enabling SQL & unified API for users to access HBASE & Aerospike at scale. Currently, she is working on PayPal’s Core Data Highway, which enables streaming data from Oracle to Kafka and other offline data stores in near real time.

Find Anisha Nainani 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.