Future of the Web Track Talks

Andrew Trister
Invited Speaker Andrew Trister
MD/Deputy Director
Bill and Melinda Gates Foundation

Andrew Trister leads the Innovative Technology Solutions team’s efforts to leverage integrated mobile technology and data systems to aid in the appropriate use and process of performing diagnostics as well as to enable high quality healthcare and wellness solutions in resource limited settings. Andrew will be leveraging advanced technologies and data science built around mobile devices as an interface to advance the goals of the foundation through internal and external partnerships.

Trister is a physician scientist passionate about leveraging technology to improve health care for all. He believes the combination of multiscale digital data from patients can impact our understanding, prevention and treatment of disease. He joined the foundation from Apple, where he led clinical research and machine learning efforts in health for the special projects team. Prior to Apple, he was the senior physician at Sage Bionetworks, where he focused on incentives for researchers and participants to collaborate on large datasets and translating those findings to clinical settings.

He completed residency in radiation oncology at the University of Washington, earned an M.D., Ph.D. in bioengineering, MSE and BSE in computer science, and a B.A. in biological basis of behavior all from the University of Pennsylvania.

Amar Subramanya
Invited Speaker Amar Subramanya
Director of Google Assistant

Amar Subramanya is a distinguished engineer at Google where he leads the Google Assistant conversational language understanding team. Prior to this he led language understanding efforts at Google Research impacting a number of Google's products.

He got his PhD in Electrical Engineering from the University of Washington, Seattle in 2009, and was a recipient of the Microsoft Research Graduate Fellowship in 2007.

Ben Zhao
Invited Speaker Ben Zhao
Professor of Computer Science
University of Chicago

Ben Zhao is the Neubauer Professor of Computer Science at University of Chicago. He completed his PhD from Berkeley (2004) and his BS from Yale (1997). He is an ACM distinguished scientist, and recipient of the NSF CAREER award, MIT Technology Review's TR-35 Award (Young Innovators Under 35), ComputerWorld Magazine's Top 40 Tech Innovators award, Google Faculty award, and IEEE ITC Early Career Award. His work has been covered by media outlets such as Scientific American, New York Times, Boston Globe, LA Times, MIT Tech Review, and Slashdot.

He has published more than 160 publications in areas of security and privacy, networked systems, wireless networks, data-mining and HCI (H-index 65). He served as TPC co-chair for the World Wide Web Conference (WWW 2016) and the ACM Internet Measurement Conference (IMC 2018), and is General Co-Chair for ACM HotNets 2020.

Gerhard Weikum
Invited Speaker Gerhard Weikum
Research Director
Max Planck Institute for Informatics

Gerhard Weikum is a Scientific Director at the Max Planck Institute for Informatics in Saarbruecken, Germany.

He co-authored a comprehensive textbook on transactional systems, received the VLDB Test of Time Award for his work on automatic database tuning, and is one of the creators of the YAGO knowledge base which received the WWW Test of Time Award. He has served on the editorial boards of ACM TODS, IEEE TKDE and ACM TWEB, and was PC chair of ACM SIGMOD and IEEE ICDE. He is an ACM Fellow and received the ACM SIGMOD Edgar F. Codd Innovations Award.

Michael Ostrovsky
Invited Speaker Michael Ostrovsky
Professor of Economics
Stanford Graduate School of Business

Michael Ostrovsky is the Fred H. Merrill Professor of Economics at the Stanford Graduate School of Business. He also serves as a co-director of the Market Design working group at the National Bureau of Economic Research.

His research is in the areas of game theory, market design, auction theory and practice, matching, industrial organization, and e-commerce platforms. Most recently, he has analyzed the economics of carpooling and self-driving cars, the properties of internet advertising auctions, information aggregation in financial markets, stability in trading networks, and voting in shareholder meetings.

Mor Naaman
Invited Speaker Mor Naaman
Associate Professor at Cornell Tech
Cornell University

Mor Naaman is an Associate Professor at the Jacobs Technion-Cornell Institute at Cornell Tech and in the Information Science Department at Cornell University. His research applies multidisciplinary methods to 1) gain a better understanding of people and their use of social tech; 2) extract insights about people, technology and society from social media and other sources of social data, and 3) develop new social technologies as well as novel tools to make social data more accessible and usable in various settings.

Previously, Mor was on the faculty at Rutgers SC&I, led a research team at Yahoo! Research Berkeley, received a Ph.D. in Computer Science from Stanford University, and played professional basketball for Hapoel Tel Aviv. He is a recipient of a NSF Early Faculty CAREER Award, research awards and grants from numerous corporations including AOL and Google, and multiple best paper awards.

Mounia Lalmas
Invited Speaker Mounia Lalmas
Head of Tech Research

Mounia Lalmas is a Director of Research at Spotify, and the Head of Tech Research in Personalization. Mounia also holds an honorary professorship at University College London. Before that, she was a Director of Research at Yahoo, where she led a team of researchers working on advertising quality for Gemini, Yahoo native advertising platform. She also worked with various teams at Yahoo on topics related to user engagement in the context of news, search, and user generated content. Prior to this, she held a Microsoft Research/RAEng Research Chair at the School of Computing Science, University of Glasgow. Before that, she was Professor of Information Retrieval at the Department of Computer Science at Queen Mary, University of London.

Her work focuses on studying user engagement in areas such as native advertising, digital media, social media, search, and now audio. She has given numerous talks and tutorials on these and related topics, including recently a WWW 2019 tutorial on "Online User Engagement: Metrics and Optimization". She is regularly a senior programme committee member at conferences such as WSDM, KDD, WWW and SIGIR. She was co-programme chair for SIGIR 2015, WWW 2018 and WSDM 2020. She is also the co-author of a book written as the outcome of her WWW 2013 tutorial on "measuring user engagement". Outside of work, she enjoys yoga and prosecco.

Raghu Ramakrishnan
Invited Speaker Raghu Ramakrishnan
Technical Fellow/CTO for Data

Raghu Ramakrishnan is CTO for Data, and a Technical Fellow at Microsoft since 2012. From 1987 to 2006, he was a professor at University of Wisconsin-Madison, where he wrote the widely used text “Database Management Systems”. In 1999, he founded QUIQ, a company powering crowd-sourced question-answering as a cloud service. He joined Yahoo! in 2006 as a Yahoo! Fellow, and served as Chief Scientist for the portal, cloud and search divisions.

Ramakrishnan has received several awards, including the ACM SIGMOD Edgar F. Codd Innovations Award, the ACM SIGKDD Innovations Award, the ACM SIGMOD Contributions Award, 10-year Test-of-Time Awards from the ACM SIGMOD, ACM SOCC, ICDT and VLDB conferences, the IIT Madras Distinguished Alumnus Award, the NSF Presidential Young Investigator Award and the Packard Fellowship in Science and Engineering. He is a Fellow of the ACM and IEEE and has served as Chair of ACM SIGMOD.

Soumen Chakrabarti
Invited Speaker Soumen Chakrabarti
Professor of Computer Science
IIT Bombay

Soumen Chakrabarti is a Professor of Computer Science at IIT Bombay. He got his PhD from University of California, Berkeley and worked on Clever Web search and Focused Crawling at IBM Almaden Research Center. He has also worked at Carnegie-Mellon University and Google.

He works on linking unstructured text to knowledge bases and exploiting these links for better search and ranking. Other interests include link formation and influence propagation in social networks, and personalized proximity search in graphs. He has published extensively in WWW, SIGKDD, EMNLP, ACL, IJCAI, AAAI, SIGIR, VLDB, ICDE and other conferences. His work on keyword search in databases got the 10-year influential paper award at ICDE 2012. He is also the author of one of the earliest books on Web search and mining.

Data Silos and Privacy in Artificial Intelligence – Advances in Transfer Learning and Federated Learning

Qiang Yang
Data Silos and Privacy in Artificial Intelligence – Advances in Transfer Learning and Federated Learning
Invited Speaker Qiang Yang
Professor of Computer Science and Engineering
Hong Kong University of Science and Technology

Qiang Yang is the head of AI in WeBank and a chair professor at Computer Science and Engineering Department at Hong Kong University of Science and Technology (HKUST). His research interests include artificial intelligence, machine learning, especially transfer learning and federated learning. He is a fellow of AAAI, ACM, IEEE, AAAS, and the founding Editor in Chief of the ACM Transactions on Intelligent Systems and Technology (ACM TIST) and the founding Editor in Chief of IEEE Transactions on Big Data (IEEE TBD).

Yang received his PhD from the University of Maryland, College Park in 1989 and has taught at the University of Waterloo and Simon Fraser University. He was the PC Chair of IJCAI-2015, KDD-2010 and has received the ACM SIGKDD Distinguished Service Award in 2017 as well as several other awards. He is a past President of IJCAI (2017-2019) and an executive council member of AAAI.

Despite its great progress so far, artificial intelligence (AI) is facing a serious challenge in the availability of high-quality Big Data. In many practical applications, data are in the form of isolated islands. Efforts to integrate the data are increasingly difficult partly due to serious concerns over user privacy and data security. The problem is exacerbated by strict government regulations such as Europe’s General Data Privacy Regulations (GDPR). In this talk, I will review these challenges and describe possible technical solutions to address them. In particular, Yang will give an overview of recent advances in transfer learning and show how it can alleviate the problems of data shortage. He will also give an overview of recent efforts in federated learning and transfer learning, which aims to bridge data repositories without compromising data security and privacy

Yoelle Maarek
Invited Speaker Yoelle Maarek
VP Research of Alexa Shopping

Yoelle Maarek is a Vice President at Amazon, heading research for Alexa Shopping. Prior to this, she was Vice President of Research at Yahoo, guiding the research teams worldwide. Prior to Yahoo, she was the first engineering hire of Google in Israel and opened the Haifa engineering office. One of the most notable features her team launched is Google Suggest, the query auto-completion service. Before Google, she was with IBM Research, first in the US then in Israel, holding a number of technical and management positions, eventually becoming an IBM Distinguished Engineer.

She has been serving in various senior roles at leading academic research conferences in the field of Web search and data mining, such as SIGIR, WWW and WSDM. She is a member of the Technion Board of Governors and was inducted as an ACM Fellow in 2013. Yoelle obtained a PhD in Computer Science from the Technion, Israel in 1989, and holds an engineering degree from the Ecole des Ponts et Chaussées, and a DEA (graduate degree) in Computer Science from Paris VI University, both awarded in 1985.