PA: Data Science at Scale for IoT on the Pivotal Platform

PA: Data Science at Scale for IoT on the Pivotal Platform with speakers Gautam Muralidhar, Rashmi Raghu and Srivatsan Ramanujam

NOTE: THIS MEETUP IS IN PALO ALTO at 5:45pm PDT

Schedule:
6:00-6:30 pm Food and networking
6:30-8:00pm Talk and Q&A
8:00-8:30 pm Wind down

In the age of IoT, data from sensors are typically in the form of one or higher dimensional signals or attributes. For example, in drilling for oil, various one-dimensional signals such as weight on bit, rpm, etc. are continuously recorded, while in automobiles, multidimensional GPS data are used to describe the geo-location of the vehicles. As IoT continues to evolve, the variety of the data sources is only going to grow, and applications will need to step up to be able process data of different kinds such as sensor data, images, and text.

In this meetup, we will present the capabilities of the Pivotal stack to store and process IoT data of different kinds. We will illustrate how techniques such as Kalman filter for geo-position estimation, Fourier transforms for frequency decomposition, edge detection for image processing, and window-level aggregations for time-series analyses can be realized with the Pivotal platform using open source tools and libraries. Finally using the scenario of predictive maintenance for drilling we will demonstrate how these basic atomic operations can be put together to build an application that feed off our data science models and quickly deploy it on Pivotal Cloud Foundry.

Attendees will walk away with an understanding of some of the business use cases we’ve worked on in the IoT space, some data science modeling techniques we’ve used to solve these business problems and how to communicate insights by building an application on PCF that can talk to the Pivotal Big Data Suite environment to perform data science for IoT at scale.

Srivatsan Ramanujam is a Principal Data Scientist at Pivotal where he executes Data Sciences labs for their customers, with a special focus on Text Analytics. He brings with him over 8+ years of industry experience in software engineering and data science. He received a Masters in Computer Sciences from UT Austin, completing his thesis and research in NLP where he focused on graphical models for weakly supervised sequence prediction problems. He loves mountaineering and is a native speaker of Python.

Rashmi Raghu is a Principal Data Scientist at Pivotal with a focus on the Internet-of-Things and applications in the Energy sector. She holds a Ph.D. in Mechanical Engineering with a minor in Management Science & Engineering from Stanford University. Her doctoral work focused on the development of novel computational models of the cardiovascular system to aid disease research. Prior to that she obtained Master’s and Bachelor’s degrees in Engineering Science from the University of Auckland, New Zealand.

Gautam Muralidhar is a Sr. Data Scientist at Pivotal where he helps customers derive actionable insights from big data by solving machine learning challenges for them using state of the art analytics infrastructure and tools from Pivotal's stack. His areas of expertise include machine learning, signal and image processing, and computer vision. His work has spanned the areas Internet of Things, Automotive, Logistics, and Healthcare.

Can't join us in person? No need to RSVP--you can participate via LiveStream: https://livestream.com/pemo/datascienceatscaleforiot

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