The 24th International World Wide Web Conference in Florence, Italy on May 18th

   

Ramesh Johari

Bio: Ramesh Johari is an Associate Professor at Stanford University and the Cisco Faculty Scholar in the School of Engineering, with a full-time appointment in the Department of Management Science and Engineering (MS&E), and courtesy appointments in the Departments of Computer Science (CS) and Electrical Engineering (EE). He is a member of the Operations Research group in MS&E, the Information Systems Laboratory in EE, and the Institute for Computational and Mathematical Engineering. He is faculty director of the Social Algorithms Lab (SOAL). He received an A.B. in Mathematics from Harvard (1998), a Certificate of Advanced Study in Mathematics from Cambridge (1999), and a Ph.D. in Electrical Engineering and Computer Science from MIT (2004). In 2012-2013 he was on leave from Stanford at oDesk (now Elance-oDesk), first as a Consulting Scientist, then as Director of Data Products and Research. He also serves as an advisor to several startups in addition to Elance-oDesk, including Optimizely, a leading web optimization platform.

 
 
   

Alex Deng

Bio: Alex Deng is a data and applied scientist on the Microsoft Analysis and Experimentation Team(A&E). The A&E team is responsible for one of the largest and best cutting-edge online experimentation system in the industry with the mission of accelerating innovation through trustworthy analysis and experimentation. Dr. Deng finished his Ph.D. study in statistics at Stanford in 2010. Since then he has been a member of the A&E team and is currently leading a team focusing on methodological improvements of the experimentation platform. His works in this area have been published in proceedings of KDD, WWW, WSDM and JSM.

 
 
   

Scott Clark

Bio: Scott is currently running SigOpt, an optimization as a service startup that leverages techniques from optimal learning to automatically tune A/B tests, machine learning models, and complicated systems. Before that he worked on the Ad Targeting team at Yelp Inc leading the charge on academic research and outreach with projects like the Yelp Dataset Challenge and open sourcing MOE. Scott holds a PhD in Applied Mathematics and an MS in Computer Science from Cornell University and BS degrees in Mathematics, Physics, and Computational Physics from Oregon State University.

 
 
   

Filip Radlinski

Bio: Filip is an applied researcher at Microsoft, and work for Bing. He is at Microsoft Research Cambridge, in the Machine Learning and Perception group. He is also an honorary lecturer in Computer Science at UCL. His current research focuses on developing machine learning and online evaluation techniques for learning from, evaluating with, and optimizing to implicitly collected feedback from web users. He is particularly interested in applications to search both in the typical web setting and on new form factors, with a current focus on personalization, contextualization and in-situ evaluation. Before joining Microsoft in 2008, he completed his PhD in Computer Science at Cornell University.