The summit will be focused on Dialogue Systems, Chatbots, Visual Dialogue, and Intelligent Agents. Over two days we will take deep dives into some of Facebook's current research in these areas and hear talks from leading experts working in the field. The two days will be a mix of plenary sessions, break-out workshops and demos. Specifically we are looking forward to sharing some insights and future plans for projects: ParlAI, Visual Q&A, and CommAI.
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Please note that this a private event, that is invite-only. Space is limited, so please do not RSVP unless you were invited directly from a Facebook Researcher.
Yann is the Director of AI Research at Facebook since 2013 as well as a Silver Professor at NYU on a part-time basis, mainly affiliated with the NYU Center for Data Science and the Courant Institute of Mathematics. He is the co-director of the Neural Computation and Adaptive Perception Program of CIFAR and co-lead of the Moore-Sloan Data Science Environments for NYU.
Rebecca is a Professor of Cognitive Neuroscience in the department of BCS and an associate member of the McGovern Institute. She received her BA from Oxford University, and her PhD from MIT. Before joining the faculty, she was a Junior Fellow in Harvard’s Society of Fellows. She has authored more than 60 peer-reviewed papers on the cognitive neuroscience of social cognition, Theory of Mind, and moral judgment. Her TED talk has been viewed over a million times. She was recently named a Young Global Leader by the World Economic Forum.
Antoine is a research scientist at Facebook Artificial Intelligence Research. Prior to joining Facebook in 2014, he was a CNRS staff researcher in the Heudiasyc laboratory of the University of Technology of Compiegne in France. He received his PhD in machine learning from Pierre & Marie Curie University in Paris. He received two awards for best PhD from the French Association for Artificial Intelligence and from the French Armament Agency, as well as a Scientific Excellence Scholarship awarded by CNRS in 2013.
Sanja is an Assistant Professor at the University of Toronto and her work is in the area of Computer Vision, mainly 2D and 3D object detection. She was a Research Assistant Professor at Toyota Technological Institute at Chicago and was visiting Prof. Trevor Darrell's group at UC Berkeley and ICSI. She is also interested in the interplay between language and vision: generating sentential descriptions about complex scenes, as well as using textual descriptions for better scene parsing
Jason has been a Research Scientist at Facebook for over 3 years. He earned his PhD in machine learning at Royal Holloway, University of London and AT&T Research in Red Bank, New Jersey. He has authored papers in the areas of machine learning, NLP, speech, vision and bioinformatics, including best paper awards at ICML and ECML.
Raquel is an Associate Professor at the Institute for Logic, Language & Computation where she leads the Dialogue Modelling Group. Her research is mostly concerned with linguistic interaction. She is co-president of the SemDial Board overseeing the SemDial Workshop Series and one of the founding and managing editors of the open-access journal Dialogue & Discourse.Â
Aaron is an Assistant Professor in the Department of Computer Science and Research Operations (DIRO) and a member of MILA. His current research interests focus on the development of deep learning models and methods. He is particularly interested in developing probabilistic models and novel inference methods.Â
Joelle is a Research Manager in Engineering at Facebook as well as an Associate Professor and William Dawson Scholar at McGill University where she co-directs the Reasoning and Learning Lab. Her research focuses on developing new models and algorithms for planning and learning in complex partially-observable domains. She serves on the editorial board of the Journal of Artificial Intelligence Research and the Journal of Machine Learning Research and is currently President-Elect of the International Machine Learning Society.
Oliver is a Professor of Computer Science at Heriot-Watt University, Edinburgh, and Director of their Interaction Lab, which focuses on machine learning approaches to spoken dialogue systems as well as Human-Robot Interaction. He was previously a research fellow at Stanford and Edinburgh universities and has a PhD from Edinburgh. He has led several national and international research projects and is a Faculty Advisor for one of only 3 teams which will compete in the Amazon Alexa Challenge final in November 2017.
Percy is an Assistant Professor of Computer Science and Statistics. His research is to develop trustworthy agents that can communicate effectively with people and improve over time through interaction. He broadly identifies with the machine learning (ICML, NIPS) and natural language processing (ACL, NAACL, EMNLP) communities. Agents need to be able to "understand natural language."Â
Mohit is an Assistant Professor in the Computer Science department at UNC Chapel Hill. Prior to this, he was a Research Asst. Professor at TTI-Chicago (and got his PhD from UC Berkeley). His research interests are in multimodal, grounded, and embodied NLP (i.e., language with vision and speech, for robotics), human-like language generation and dialogue, and interpretable deep learning. He is a recent recipient of the 2017 DARPA Young Faculty Award, and has received the 2017 ACL Outstanding Paper Award and the 2014 ACL Best Paper Award Honorable Mention.
Devi is an Assistant Professor in the School of Interactive Computing at Georgia Tech, and a Research Scientist at Facebook AI Research (FAIR). She has held visiting positions at Cornell University, University of Texas at Austin, Microsoft Research, MIT, and Carnegie Mellon University. Her research interests include computer vision and AI in general and visual recognition problems in particular. Her recent work involves exploring problems at the intersection of vision and language, and leveraging human-machine collaboration for building smarter machines.
Brenden is an Assistant Professor of Psychology and Data Science. He builds computational models of our everyday cognitive abilities, focusing on problems that are easier for people than they are for machines. The human mind is the best known solution to a diverse array of difficult computational problems that people seem to solve every day: concept learning, object recognition, scene understanding, language acquisition, speech recognition, question asking, amongst many others.
Dhruv is an Assistant Professor in the School of Interactive Computing at Georgia Tech and a Research Scientist at Facebook AI Research (FAIR). He was an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech, where he lead the VT Machine Learning & Perception group and was a member of the Virginia Center for Autonomous Systems (VaCAS) and the VT Discovery Analytics Center (DAC). Research from his lab has been featured in Bloomberg Business, The Boston Globe, MIT Technology Review, Newsweek, WVTF Radio IQ, and a number of popular press magazines and newspapers.
Marco is a research scientist on the Facebook Artificial Intelligence Research (FAIR) team. He joined the faculty of the University of Trento (Italy) in 2006, as associate professor at the Center for Mind/Brain Sciences. His work there focused on general methods for natural language understanding that rely on raw input data, such as large amounts of text and images. His work was partially supported by a Google Research Award and an ERC Starting grant.Â
Tomas is a research scientist at Facebook AI Research. Previously he was a member of Google Brain team, where he developed and implemented efficient algorithms for computing distributed representations of words (word2vec project). He obtained his PhD from Brno University of Technology (Czech Republic) for his work on recurrent neural network based language models (RNNLM).
Germán is a a postdoctoral researcher at Facebook. He obtained his PhD at the University of Trento under the direction of Marco Baroni where he worked in the area of distributional semantics, understanding the strengths and limitations of distributional models when trying to account for the richness of human conceptual knowledge.
You will be asked to sign an NDA upon arrival. Please ensure you have booked your travel with Facebook. Confirmation codes and further information will be emailed to you the week prior to the event. If you have questions, please reach out to Kelly: kbeccaria@fb.com right away.Â
Facebook Artificial Intelligence Researchers (FAIR) seek to understand and develop systems with human level intelligence by advancing the longer-term academic problems surrounding AI. Our research covers the full spectrum of topics related to AI, and to deriving knowledge from data: theory, algorithms, applications, software infrastructure and hardware infrastructure. Long-term objectives of understanding intelligence and building intelligent machines are bold and ambitious, and we know that making significant progress towards AI can’t be done in isolation. That’s why we actively engage with the research community through publications, open source software, participation in technical conferences and workshops, and collaborations with colleagues in academia.