Track: Predictive Architectures and ML

Day of week: Monday

AI systems are ubiquitous in today’s world and help us become more efficient and productive. Whether it is sifting through large amounts of information for faster decision making (eg., Twitter, Netflix, Spotify, LinkedIn), Financial portfolio optimization, ridesharing or automation.

In this track we will learn what it takes to build an AI system at scale! Big Data Engineering is often the foundation of these systems and AI/ML helps develop deeper personalization. AI systems typically exploit past user behavior, user similarities and item similarities to generate a list of information items that is personally tailored to an end-user’s preferences. In addition to learning the state of the art in this field, the track will also aim to discuss topics around fair representation, security and privacy in building such systems.

Track Host: Hema Raghavan

Senior Manager & Heading AI for Growth and Communication Relevance @LinkedIn

Hema Raghavan heads the team that builds AI and ML at LinkedIn solutions for fueling the professional social network’s growth. Prior to that, she was a Research Staff Member at IBM T.J Watson. Hema started her career in the industry in Yahoo Labs. Her interests span the broad area of applications of AI and her experience spans a spectrum of products she has built in the areas of Search, Advertising, Question Answering and Recommendations. She has published in several conferences like WWW, SIGIR, ACL and COLING.

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