Applied Data Science Invited Speakers

The Applied Data Science Invited Talks will provide a venue for leading experts in the world of applied data mining and knowledge discovery. These invited talks will feature highly influential speakers who have directly contributed to successful data mining applications in their respective fields. The talks and discussions will focus on innovative and leading-edge, large-scale industry or government applications of data mining in areas such as finance, health-care, bio-informatics, public policy, infrastructure, telecommunications, social media and computational advertising.


Keynote: Romer Rosales-Delmoral

Romer Rosales-Delmoral

LinkedIn

Product Ecosystem Optimization at LinkedIn

Artificial Intelligence (AI) is behind practically every product experience at LinkedIn. From ranking the member’s feed to recommending new jobs, AI is used to fulfill our mission to connect the world’s professionals to make them more productive and successful. While product functionality can be decomposed into separate components, they are deeply interconnected; thus, creating interesting questions and challenging AI problems that need to be solved in a sound and practical manner. In this talk, I will provide an overview of lessons learned and approaches we have developed to address these problems, including scaling to large problem sizes, handling multiple conflicting objective functions, efficient model tuning, and our progress toward using AI to optimize the LinkedIn product ecosystem more holistically.


Romer Rosales is a Sr. Director of Artificial Intelligence (AI) at LinkedIn. His team focuses on machine learning and optimization to make LinkedIn consumer products more personalized and safer, provide higher member value, and ultimately create economic opportunity. He has published over 60+ articles in Machine Learning, Data Mining, and Computer Vision journals and conferences, and holds 20+ issued US patents in these fields. He has served as organizer and senior committee member for various conferences in the machine learning field and as guest editor in various machine learning and data mining journals. Romer received a Ph.D. in Computer Science from Boston University and worked as Research Associate at the University of Toronto and the Massachusetts Institute of Technology. Since 2005 he has held various scientific positions in industry and has also help founding a consumer healthcare start-up as chief scientist.

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