The second annual West Coast NLP (WeCNLP) Summit is an opportunity to foster discussion and collaboration between NLP researchers in academia and industry. The event will include talks and a panel from research leaders on the latest advances in NLP technologies. The day will conclude with a poster session where attendees can learn from each other in an informal setting. The event will take place at Facebook, Menlo Park, on September 6th.

News

The videos for the invited and lightning talks are up! You can also check last year's videos.
Registration is now full, but you can still register and you will be put on a waiting list. Please contact us (click on "Contact the organizer") if you are unable to attend.
You can now follow @WeCNLP on Twitter and the WeCNLP page for updates on the event!
July 23 2019 - Applications for the travel grant are now open!
June 7 2019 – Abstract submissions are open! The deadline has been extended to July 11 (UTC-12). If you are a student, please check below the travel grant section as primary author students with an accepted abstract will be eligible for a travel grant.
April 30 2019 – Registration is open!

Important Dates

June 30, 2019 – Poster abstract submission deadline
July 22 2019 – Notification of abstract acceptance
September 6 2019 – WeCNLP Summit

Steering Committee

Jeff Dean

Emily Fox

Zoubin Ghahramani

Dilek Hakkani-Tur

Yann LeCun

Chris Manning

Invited Speakers

Zhou Yu

Talk Title: "Building dialog systems with less supervision"

Zhou is an Assistant Professor at the Computer Science Department in UC Davis. She received her PhD in Carnegie Mellon University. Zhou's research centers on dialog systems and language generation. She was recently featured in Forbes as 2018 30 under 30 in Science. Her team won Amazon Alexa Prize 2018 with $500,000 award in building a social chatbot. (https://developer.amazon.com/alexaprize) She was also a recipient of Rising stars in EECS in 2015. Zhou's website. http://zhouyu.cs.ucdavis.edu/

Marc'Aurelio Ranzato

Title: “What is the effect of place in machine translation?”

Marc'Aurelio Ranzato is a Research Scientist at Facebook AI Research lab in New York City. His research interests are in the area of unsupervised learning, continual learning and transfer learning, with applications to vision, natural language processing and speech recognition. Marc'Aurelio has earned a PhD in Computer Science at New York University under Yann LeCun's supervision. After a postdoc with Geoffrey Hinton at University of Toronto, he joined the Google Brain team in 2011. In 2013 he joined Facebook and was a founding member of the Facebook AI Research lab.

Heng Ji

Heng Ji is Professor of Computer Science at University of Illinois at Urbana-Champaign. She received her Ph.D. in Computer Science from New York University. Her research interests focus on Natural Language Processing, especially on Information Extraction (IE) and Knowledge Base Population. She is selected as "Young Scientist" and a member of the Global Future Council on the Future of Computing by the World Economic Forum in 2016 and 2017. The awards she has received include "AI's 10 to Watch" Award by IEEE Intelligent Systems in 2013 and NSF CAREER award in 2009. She is the associate editor for IEEE/ACM Transaction on Audio, Speech, and Language Processing. She served as the Program Committee Chair of many conferences including NAACL2018.

Louis-Philippe Morency

Talk Title: “Multimodal AI: Understanding Human Behaviors”

Louis-Philippe Morency is Leonardo Associate Professor in the Language Technology Institute at Carnegie Mellon University where he leads the Multimodal Communication and Machine Learning Laboratory (MultiComp Lab). He was formerly research faculty in the Computer Sciences Department at University of Southern California and received his Ph.D. degree from MIT Computer Science and Artificial Intelligence Laboratory. His research focuses on building the computational foundations to enable computers with the abilities to analyze, recognize and predict subtle human communicative behaviors during social interactions. He received diverse awards including AI’s 10 to Watch by IEEE Intelligent Systems, NetExplo Award in partnership with UNESCO and 10 best paper awards at IEEE and ACM conferences. His research was covered by media outlets such as Wall Street Journal, The Economist and NPR. He is currently chair of the advisory committee for ACM International Conference on Multimodal Interaction and associate editor at IEEE Transactions on Affective Computing.

Aylin Caliskan

Aylin Caliskan is an assistant professor of computer science at George Washington University. Her research interests include the emerging science of bias in artificial intelligence, fairness in machine learning, and privacy. Her work aims to characterize and quantify aspects of natural and artificial intelligence using a multitude of machine learning, language processing, and computer vision techniques. In her recent publication in Science, she demonstrated how semantics derived from language corpora contain human-like biases. Prior to that, she developed novel privacy attacks to de-anonymize programmers using code stylometry. Her presentations on both de-anonymization and bias in machine learning are the recipients of best talk awards. Her work on semi-automated anonymization of writing style furthermore received the Privacy Enhancing Technologies Symposium Best Paper Award. Her research has received extensive press coverage across the globe. Aylin holds a PhD in Computer Science from Drexel University and a Master of Science in Robotics from University of Pennsylvania. Before joining the faculty at George Washington University, she was a postdoctoral researcher and a fellow at Princeton University's Center for Information Technology Policy.

Jason Williams

Talk Title: “Recent work on language understanding at Siri”

Jason Williams manages the language understanding group for Siri, at Apple. Before joining Apple, he was a Research Manager at Microsoft Research, where he led the Conversational Systems Research Group and the Redmond Reinforcement Learning Group. Prior to Microsoft, he was Principal Researcher with AT&T Labs – Research. He has published about 60 peer-reviewed papers on dialog systems and related areas, and has received five best paper/presentation awards for work on statistical approaches to dialog systems, including the use of POMDPs (partially observable Markov decision processes), reinforcement learning, turn-taking, and empirical user studies. In 2012 he initiated the Dialog State Tracking Challenge series, in 2014 he shipped components of the first release of Microsoft Cortana, in 2015 he launched Microsoft’s Language Understanding Service, and in 2018 he launched Microsoft’s Conversation Learner Service. He is President of SIGDIAL, and an elected member of the IEEE Speech and Language Technical Committee (SLTC) in the area of spoken dialogue systems.

Jingjing Liu

Talk Title: "Multimodal Intelligence"

Jingjing Liu is a Principal Research Manager at Microsoft, leading a research group in Conversational AI. Her current research interests center on Vision + Language Multimodal Intelligence, such as Visual QA/Dialog, Visual Reasoning, Dialog-based Image Synthesis, and Story Visualization. Dr. Liu received her PhD degree in Computer Science from MIT EECS in 2011, with a research focus on Spoken Dialog Systems. She also holds an MBA degree from Judge Business School at University of Cambridge. Before joining MSR, Dr. Liu was a Research Scientist at MIT CSAIL and Director of Product at the unicorn startup Mobvoi Inc.

Emily Bender

Emily M. Bender is a Professor in the Department of Linguistics and Adjunct Professor in the School of Computer Science & Engineering at the University of Washington. She is also affiliated with UW's Tech Policy Lab and Value Sensitive Design Lab. Her primary research interests lie in multilingual grammar engineering, the incorporation of linguistic knowledge in NLP, computational semantics, and ethics in NLP. She is the author of Linguistic Fundamentals for Natural Language Processing: 100 Essentials from Morphology and Syntax (2013, Morgan & Claypool) and, with Alex Lascarides, the forthcoming follow-up volume Linguistic Fundamentals for Natural Language Processing: 100 Essentials from Semantics and Pragmatics. She completed her PhD in Linguistics at Stanford University in 2000.

Mari Ostendorf

Talk Title: "Spoken Language as a Multimodal Signal"

Mari joined the University of Washington Electrical & Computer Engineering Department in 1999. She is an Endowed Professor of System Design Methodologies in the ECE Department, an Adjunct Professor in CSE and Linguistics, as well as Associate Vice Provost for Research. She is a Fellow of the IEEE, ISCA and ACL, a Scottish Informatics and Computer Science Alliance Distinguished Visiting Fellow, and a former Australian-American Fulbright Scholar. Prof. Ostendorf has published over 270 papers on a variety of topics in speech and language processing. In 2017, she served as a faculty advisor for the student team winning the inaugural Alexa Prize competition to build a socialbot, and conversational AI is a focus of her current work. Her research explores dynamic models for understanding and generating speech and text, particularly in multi-party contexts, and it contributes to a variety of applications, from education to clinical and scientific information extraction.

Greg Durrett

Talk Title: "Generalizable Deep Learning for NLP via Modularity and Abstraction"

Greg Durrett is an assistant professor of Computer Science at UT Austin. His current research focuses on a range of topics in statistical natural language processing, including information extraction (particularly coreference resolution and entity linking), document summarization, and question answering. He is particularly interested in endowing deep models with the ability to do discrete reasoning and logical inference. Greg completed his Ph.D. at UC Berkeley in 2016, and from 2016-2017, he was a research scientist at Semantic Machines.

Alexandros Papangelis

Alexandros Papangelis is a senior research scientist at Uber AI, on the Conversational AI team; his interests include statistical dialogue management, natural language processing, and human-machine social interactions. Prior to Uber, he was with Toshiba Research Europe, leading the Cambridge Research Lab team on Statistical Spoken Dialogue. Before joining Toshiba, he was a postdoctoral fellow at CMU's Articulab, working with Justine Cassell on designing and developing the next generation of socially-skilled virtual agents. He received his PhD from the University of Texas at Arlington, MSc from University College London, and BSc from the University of Athens.

Pascale Fung

Pascale Fung is a Professor at the Department of Electronic & Computer Engineering and Department of Computer Science & Engineeringat The Hong Kong University of Science & Technology (HKUST). She is an elected Fellow of the Institute of Electrical and Electronic Engineers (IEEE) for her “contributions to human-machine interactions”, and an elected Fellow of the International Speech Communication Association for “fundamental contributions to the interdisciplinary area of spoken language human-machine interactions”. She is the Director of HKUST Center for AI Research (CAiRE), an interdisciplinary research center on top of all four schools at HKUST. She co-founded the Human Language Technology Center (HLTC). She is an affiliated faculty with the Robotics Institute and the Big Data Institute at HKUST. She is the founding chair of the Women Faculty Association at HKUST. She is an expert on the Global Future Council, a think tank for the World Economic Forum. She represents HKUST on Partnership on AI to Benefit People and Societyand is on the Advisory Board of Building Agile Governance for AI & Robotics (BGI4AI).

Chris Quirk

After studying Computer Science and Mathematics at Carnegie Mellon University, I joined Microsoft in 2000 to work on the Intentional Programming project, an extensible compiler and development framework. I moved to the Natural Language Processing group in 2001, where my research has mostly focused on statistical machine translation powering Microsoft Translator, especially on several generations of a syntax directed translation system that powers over half of the translation systems. I am also interested in semantic parsing, paraphrase methods, and very practical problems such as spelling correction and transliteration.