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PHILLY – Data Analytics Distinguished Lecture Series
December 4, 2018 @ 4:30 pm - 6:00 pmFree
Tuesday, December 4, 2018: 4:30-5:30 pm Presentation and Q&A; 5:30-6 pm: Networking/Light Refreshments
Distinguished Speaker: Dr. Jan Neumann, Director of the Comcast Applied Artificial Intelligence Research Group
Title: How AI allows Comcast to Reinvent the Customer Experience
Comcast uses AI and Machine Learning in many of its products from the Emmy winning voice remote for the X1 entertainment product, to anticipating the needs of the customer in the digital home. We will show how machine learning is an essential part of our content discovery platform to help our customers find the content they love, and how it allows our smart media analytics solutions to enable a richer navigation and search experience. We will also talk about a major recent effort by Comcast to reinvent the customer service experience for its customers using artificial intelligence. We will explain how Comcast uses deep learning to build virtual assistants that allow its customers to contact the company with questions or concerns and how it uses contextual information about customers and systems in a reinforcement learning framework to identify the best actions that answer these customers’ questions or resolve their concerns.
Jan Neumann leads the Comcast Applied Artificial Intelligence Research group with team members in Washington, DC, Philadelphia, Chicago, Denver and Silicon Valley. His team combines large-scale machine learning, deep learning, NLP and computer vision to develop novel algorithms and product concepts that improve the experience of Comcast’s customers such as the X1 voice remote and personalization features, virtual assistants and predictive intelligence for customer service, as well as smart video and sensor analytics. Before Comcast, he worked for Siemens Corporate Research on various computer vision related projects such as driver assistance systems and video surveillance. He has published over 20 papers in scientific conferences and journals, and is a frequent speaker on machine learning and data science. He holds a Ph.D. in Computer Science from the University of Maryland, College Park.