Mar 15–18, 2020

Personalization powered by unlocking deep product and consumer features

2:35pm3:15pm Wednesday, March 18, 2020
Location: 210 E

Who is this presentation for?

  • Data scientists, software engineers, and technical managers




Digital brands focus heavily on personalizing the experience of the consumers at every single touchpoint. In order to engage with consumers in the most relevant ways, brands need to personalize for each consumer’s behavior rather than grouping them into segments. Data scientists at Lily AI have leveraged the huge amounts of data that brands carry around their products and consumers to create a deep taxonomy for each of those. More than 15,000 attributes are extracted using deep learning, which then feeds into applications like recommendation systems.

Sowmiya Chocka Narayanan explores the lessons learned building AI-powered personalization for fashion across a wide range of environments—from high-end luxury brands to large thrift stores—by unlocking deep product and consumer features. You’ll learn about deep learning-based feature extraction and modeling, scaling the training pipeline, and the system design required to support it.

Prerequisite knowledge

  • A basic knowledge of deep learning and recommender systems

What you'll learn

  • Learn how to work backwards from the customer’s problem to identify the right dataset or approach required to fix it
  • Understand practical considerations and guidelines for feeding deep neural networks that can deliver high-quality data to power personalization
Photo of Sowmiya Chocka Narayanan

Sowmiya Chocka Narayanan

Lily AI

Sowmiya Chocka Narayanan is the cofounder and CTO of Lily AI, an emotional intelligence-powered shopping experience that helps brands understand their consumers’ purchase behavior. She’s focused on decoding user behavior and building deep product understanding by applying deep learning techniques. Previously, she worked at different levels of the tech stack at Box, leading initiatives in building SDKs, applications for industry verticals, and MDM solutions, and was also an early engineer at Pocket Gems, where she worked on the core game engine and built acquisition and retention strategies for the number one and number four top-grossing gaming apps. Sowmiya earned her master’s degree in electrical and computer engineering from The University of Texas at Austin.

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