January 19th SFASA Seminar
Speaker: Christian Posse, Principal Data Scientist and Product Manager, LinkedIn www.linkedin.com/in/christianposse
Title: LinkedIn's Recommendations: Mining the Troves of a Large Professional Network
Location: Stanford University, Li Ka Shing Center (LKSC) Building, 291 Campus Drive, Room: LK 209 Seminar Classroom
Time: Thursday, January 19th, 4:30 p.m. – 6:30 p.m.
From 'People You May Know' to 'Groups You May Like', from 'Jobs You May Be Interested In' to Today (LinkedIn News), recommendations have emerged as a critical component of LinkedIn's mission to connect the world's professionals to make them more productive and successful.
This success results from the building of a highly scalable infrastructure that can churn effortlessly through terabytes of data every day as well as the development of powerful algorithmic approaches that leverage the rich content, social graph and behavior data generated by LinkedIn's professional network. Together, they provide every week more than 100 billion personalized and contextualized recommendations in real time on members to connect with, news articles to read, talents to hire, jobs to apply to, groups to join, companies to follow, ads to show and many more.
In this talk I will describe some of the inner workings of our recommendations as well as discuss some of the challenges associated with them.
Dr. Christian Posse is Principal Scientist at LinkedIn Inc. where he leads the development of recommendation solutions as well as the next generation online experimentation platform. Prior to LinkedIn, Dr. Posse was a founding member and technology lead of Cisco Systems Inc. Network Collaboration Business Unit where he designed the search and advanced social analytics of Pulse, CiscoŐs network-based search and collaboration platform for the enterprise. Prior to Cisco, Dr. Posse worked in a wide range of environments, from holding faculty positions in US universities, to leading the R&D at software companies and a US National Laboratory in the social networks, biological networks and behavioral analytics fields. His interests are diverse and include predictive analytics, search and recommendation engines, social networks analytics, computational social and behavioral sciences, computational linguistics, and information fusion. He has written over 40 scientific peer-reviewed publications and holds several patents in those fields. Dr. Posse has a PhD in Statistics from the Swiss Federal Institute of Technology, Switzerland.
Please click on the following link to see a campus map that shows the location of the LKSC Building on StanfordŐs campus:
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