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

2019 Tracks

  • Groking Timeseries & Sequential Data

    Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.

  • Deep Learning in Practice

    Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.