◆  Charles Ling, Tenured Full and Science Distinguished Research Professor, University of Western Ontario in Canada

Keynote Topic: The 7 AI Megatrends and How to Achieve Them

Short Bio: Charles Ling is a Tenured Full Professor in the Department of Computer Science, and Science Distinguished Research Professor, at University of Western Ontario in Canada. He is a Fellow of Canadian Academy of Engineering. He obtained his Msc and PhD from University of Pennsylvania. He is a world-leading researcher in machine learning, Artificial Intelligence, data analytics and applications. He has published over 160 research papers, many in top-tier journals and international conferences, with over 6,500 citations by Google Scholars. He has received numerous awards, recognitions, and fundings for his research achievements. In addition, he is a chair professor at Soochow University, China, and Founder and CEO of GoHealthNow, which creates a platform for diabetes care using data analytics and AI.

Abstract: Pedro Domingos, the author of The Master Algorithm, proposed 5 AI Megatrends. In this talk, I added two, and discuss the opportunities, challenges, and approaches to achieve them for AI researchers.

◆  Joyce Chai, Professor, Michigan State University

Keynote Topic: Language Communication with Robots

Short Bio: Joyce Chai is a Professor in the Department of Computer Science and Engineering at Michigan State University, where she was awarded the William Beal Outstanding Faculty Award in 2018. She holds a Ph.D. in Computer Science from Duke University. Prior to joining MSU in 2003, she was a Research Staff Member at IBM T. J. Watson Research Center. Her research interests include natural language processing, situated dialogue agents, human-robot communication, artificial intelligence, and intelligent user interfaces. Her recent work is focused on situated language processing to facilitate natural communication with robots and other artificial agents. She served as Program Co-chair for the Annual Meeting of the Special Interest Group in Dialogue and Discourse (SIGDIAL) in 2011, the ACM International Conference on Intelligent User Interfaces (IUI) in 2014, and the Annual Meeting of the North America Chapter of Association of Computational Linguistics (NAACL) in 2015. She received a National Science Foundation CAREER Award in 2004 and the Best Long Paper Award from the Annual Meeting of Association of Computational Linguistics (ACL) in 2010.

Abstract: With the emergence of a new generation of cognitive robots, enabling natural communicationbetween humans and robots has become increasingly important. Humans and robots are co-present in a shared physical environment; however, they have mismatched capabilities in perception, action, and reasoning. They also have different levels of linguistic, world, and task knowledge. All of these lead to a significant disparity in their representations of the shared world, which makes language communication difficult. In this talk, I will share some recent effect to address these challenges. I will first introduce collaborative models for language processing which are motivated by cooperative principles in human communication. I will then discuss interactive acquisition of grounded verb semantics and its connection with a robot's perception and action.

◆  Cristian Danescu-Niculescu-Mizil, Assistant Professor, Cornell University

Keynote Topic: Towards an artificial intuition: Conversational markers of (anti)social dynamics

Short Bio: Cristian Danescu-Niculescu-Mizil is an assistant professor in the information science department at Cornell University. His research aims at developing computational frameworks that can lead to a better understanding of human social behavior, by unlocking the unprecedented potential of the large amounts of conversational data generated online. He is the recipient of several awards---including an NSF CAREER Award, the WWW 2013 Best Paper Award, a CSCW 2017 Best Paper Award, and two Google Faculty Research Awards---and his work has been featured in popular-media outlets such as the Wall Street Journal, NBC's The Today Show, NPR and the New York Times.

Abstract:
Can conversational dynamics---the nature of the back and forth between people---predict outcomes of social interactions? This talk will describe efforts on developing an artificial intuition about ongoing conversations, by modeling the subtle pragmatic and rhetorical choices of the participants.
The resulting framework reveals that emerging conversational patterns can point to the nature of the social relation between interlocutors, as well as predict the future trajectory of this relation. For example, I will discuss how in the context of long-lasting friendships, temporal interactional dynamics can foretell upcoming betrayal. Then I will show how this framework can be used to detect warning signs of impending antisocial behavior, signaling whether a conversation will stay on track or derail into personal attacks.
This talk includes joint work with Jonathan Cheng, Jordan Boyd-Graber, Lucas Dixon, Liye Fu, Yiqing Hua, Dan Jurafsky, Srijan Kumar, Lillian Lee, Jure Leskovec, Vlad Niculae, Chris Potts, Arthur Spirling, Dario Taraborelli, Nithum Thain and Justine Zhang.

◆  Dr. Luo Si, Chief Scientist of NLP with Alibaba DAMO institute Machine Intelligence Technologies

Keynote Topic: Natural Language Processing R&D in Alibaba

Short Bio: Dr. Luo Si is the Chief Scientist of Natural Language Processing with Alibaba DAMO institute Machine Intelligence Technologies. He leads a cross-country team in China, USA and Singapore with the focus on developing cutting edge technologies in natural language processing, machine translation, text mining and information retrieval. The work attracts hundreds of millions of users and generates millions of revenue each day. Luo has published more than 150 journal and conference papers with substantial citations. His research has obtained many industry awards from Yahoo!, Google and Alibaba as well as NSF career award. Prior to joining Alibaba in 2014, he was an Associate Professor with Purdue University. He obtained degrees in computer science from Tsinghua University and Carnegie Mellon University.

Abstract: Natural Language Processing (NLP) and related technologies are critical for the success of Internet business like e-commerce. Alibaba’s NLP R&D aims at supporting the business demands of Alibaba’s eco-system, creating new opportunities for Alibaba’s partners and advancing the state-of-the-art of NLP technologies. This talk will introduce our efforts to build NLP technique platform and machine translation (MT) platform that power Alibaba’s eco-system. Furthermore, some recent research work will be presented on product title compression with user-log information, sentiment classification with questions & answers, machine reading comprehension in real-world custom service, and cascade ranking for large-scale e-commerce search. The R&D work attracts hundreds of millions of users and generates significant business value every day.