This event has ended. Visit the official site or create your own event on Sched.
Connect socially: Follow #SEAWIT20 to hear stories from sessions and to connect with other attendees. We’ll be covering all things conversational on Twitter, Facebook, LinkedIn and Instagram so please join us! Check our FAQ page for more info.
Back To Schedule
Thursday, August 20 • 1:00pm - 2:30pm
Deep Water AI and Machine Learning: All Data Scientists Aboard

Log in to save this to your schedule, view media, leave feedback and see who's attending!

Feedback form is now closed.
This technical session brings together three perspectives and the application of machine learning techniques in very different situations. Attendees will have an opportunity to learn about reinforcement learning for personalization, Bayesian techniques applied the the search for missing children, and network graph modeling in pursuit of active users.

Creating Hooking Experiences Using Reinforcement Learning and Responsible AI
Samia Khalid
Netflix, Spotify, Instagram, Xbox – you name it – personalized experiences are what keep users hooked! How do the pros tackle this complex, dynamic problem? In this session, we will first deconstruct personalization and then we will learn how you can integrate it in your scenarios as well. Since with great power comes great responsibility, we will also talk about Responsible AI.

Bayesian Optimal Search Plan Construction to Assist the Search for Missing Child
Yuchao Ma 
More than 420,000 entries for missing children were reported to National Crime Information Center each year since 2014. Considering the vast uncertainties in the circumstances surrounding the missing child, scientific methods can be used to systematically evaluate potential scenarios, suggest searching directions and allocate time resources. In this pilot study, we introduce a Bayesian framework to construct an optimal search plan that maximizes the overall probability of detection, to assist the search for missing child. It first identifies a potential search area after information gathering, and then divides it into equal-sized units for prioritization based on a programmable granularity. A prior probability of detection is computed over all search units, and a detection model is developed in line with the optimal search theory. Along with the progress of search action, the posterior probability of finding the missing child is estimated using Bayesian method, and a maximum probability search plan is constructed, which assigns search effort to the unit with the highest posterior probability, and has been proved to be optimal for a given cumulative time investment. For the purpose of validation and visualization, we have developed a web-based application to render the proposed framework on an interactive GIS map. The implementation for algorithms and web-app will be shared for open access.

avatar for Genevieve Quintin

Genevieve Quintin

Senior Supportability Program Manager, Microsoft
I listen, appreciate and love peoples strengths and passions which genuinely builds lasting relationships. I bring people together to unlock collaboration opportunities and get things done.I am a Senior Supportability Program Manager for Modern Workplace at Microsoft. I am responsible... Read More →

avatar for Sylvie Kadackal

Sylvie Kadackal

Senior Supportability PM, Microsoft
Sylvie a Senior Supportability Program Manager for Modern Workplace at Microsoft. She is responsible for gathering, analyzing, categorizing and presenting trending customers pain points. She builds customer facing solutions leveraging key learnings and insights from Machine learning... Read More →
avatar for Samia Khalid

Samia Khalid

Senior Software Engineer, Microsoft
Samia is a Senior Applied Scientist and AI Engineer at Microsoft. She is working with large-scale distributed systems to create Microsoft's next wave of intelligent experiences in Office 365 and Outlook.Samia is also an impact maker leading various diversity and inclusion efforts... Read More →
avatar for Yuchao Ma

Yuchao Ma

Applied Scientist, Amazon
Yuchao Ma is an Applied Scientist in IPC (Inventory Planning and Control) within Amazon’s SCOT (Supply Chain Optimization Technologies) team. Her current work is focused on developing model-based systems to automate and optimize inventory selection for Amazon Retail. She had a doctorate... Read More →
avatar for Ying Wories

Ying Wories

Principal Program Manager, Microsoft

Amber Plumb

Sr. Support Planner, Microsoft

Thursday August 20, 2020 1:00pm - 2:30pm PDT