Friday, October 29th, 2021
The fourth annual WeCNLP (West Coast NLP) 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.
Like last year, WeCNLP will be a virtual event due to the pandemic.
Registration is now open!
Acceptance results will be available by Thursday September 30
The deadline for abstracts/papers is extended to Aug 14 2021!
WeCNLP is happening virtually on Oct 29 2021!
Dan Roth is the Eduardo D. Glandt Distinguished Professor at the Department of Computer and Information Science, University of Pennsylvania, the NLP Science Lead at Amazon AWS, and a Fellow of the AAAS, the ACM, AAAI, and the ACL.
In 2017 Roth was awarded the John McCarthy Award, the highest award the AI community gives to mid-career AI researchers. Roth was recognized “for major conceptual and theoretical advances in the modeling of natural language understanding, machine learning, and reasoning.”
Roth has published broadly in machine learning, natural language processing, knowledge representation and reasoning, and learning theory, and has developed advanced machine learning based tools for natural language applications that are being used widely. Until February 2017 Roth was the Editor-in-Chief of the Journal of Artificial Intelligence Research (JAIR). He also served as the Program Chair of ACL, CoNLL, and AAAI. Roth has been involved in several startups; most recently he was a co-founder and chief scientist of NexLP, a startup that leverages the latest advances in Natural Language Processing (NLP), Cognitive Analytics, and Machine Learning in the legal and compliance domains. NexLP was acquired by Reveal in 2020. Prof. Roth received his B.A Summa cum laude in Mathematics from the Technion, Israel, and his Ph.D. in Computer Science from Harvard University in 1995.
Verena leads research on Conversational AI at the intersection of Natural Language Processing and Machine Learning. She is a full professor in Computer Science at Heriot-Watt University in Edinburgh, co-founder of ALANA AI, and Director of Ethics at the UK National Robotarium. Verena received her PhD in 2008 from Saarland University (Germany) and then joined the University of Edinburgh as a postdoctoral research fellow, before taking up a faculty position at Heriot-Watt in 2011 and joining ALANA AI in 2020. She is the PI of several funded research projects and industry awards. She was recently awarded a Leverhulme Senior Research Fellowship by the Royal Society in recognition of her work in developing multimodal conversational systems.
David Traum is the Director for Natural Language Research at the Institute for Creative Technologies (ICT) and Research Professor in the Department of Computer Science at the University of Southern California (USC). He leads the Natural Language Dialogue Group at ICT. More information about the group can be found here: http://nld.ict.usc.edu/group/ Traum’s research focuses on Dialogue Communication between Human and Artificial Agents. He has engaged in theoretical, implementational and empirical approaches to the problem, studying human-human natural language and multi-modal dialogue, as well as building a number of dialogue systems to communicate with human users. Traum has authored over 250 refereed technical articles, is a founding editor of the Journal Dialogue and Discourse, has chaired and served on many conference program committees, and is a past President of SIGDIAL, the international special interest group in discourse and dialogue. Traum earned his Ph.D. in Computer Science at the University of Rochester in 1994.
Dr. Michelle Zhou is a Co-founder and CEO of Juji, Inc., a California-based company that powers and democratizes Cognitive Artificial Intelligence (AI) Assistants in the form of chatbots. She is an expert in the field of Human-Centered AI, an interdisciplinary area that intersects AI and Human-Computer Interaction (HCI). Zhou has authored more than 100 scientific publications and 45 patent applications on subjects including conversational AI, personality analytics, and interactive visual analytics of big data. Prior to founding Juji, she spent 15 years at IBM Research and the Watson Group, where she managed the research and development of Human-Centered AI technologies and solutions, including IBM Watson Personality Insights.
Zhou serves as Editor-in-Chief of ACM Transactions on Interactive Intelligent Systems (TiiS) and an Associate Editor of ACM Transactions on Intelligent Systems and Technology (TIST), and was formerly the Steering Committee Chair for the ACM International Conference Series on Intelligent User Interfaces. She is an ACM Distinguished Member and received a Ph.D. in Computer Science from Columbia University.
Marine Carpuat is an Associate Professor in Computer Science at the University of Maryland. Her research aims to design technology that helps people communicate no matter what language they speak, focusing on multilingual natural language processing and machine translation. Before joining the faculty at Maryland, Marine was a Research Scientist at the National Research Council Canada. She received a PhD in Computer Science and a MPhil in Electrical Engineering from the Hong Kong University of Science & Technology, and a Diplome d'Ingenieur from the French Grande Ecole Supelec. She is the recipient of an NSF CAREER award, research awards from Google and Amazon, best paper awards at the *SEM and TALN conferences, and an Outstanding Teaching Award.
Antonios Anastasopoulos is an Assistant Professor in Computer Science at George Mason University. He received his PhD in Computer Science from the University of Notre Dame, advised by David Chiang and then did a postdoc at Languages Technologies Institute at Carnegie Mellon University. His research is on natural language processing with a focus on low-resource settings, endangered languages, and cross-lingual learning, and is currently funded by the National Science Foundation, the National Endowment for the Humanities, Google, Amazon, and the Virginia Research Investment Fund.
Dilek Hakkani-Tür is a senior principal scientist at Amazon Alexa AI focusing on enabling natural dialogues with machines and a Visiting Distinguished Professor at UC Santa Cruz. Prior to joining Amazon, she was leading the dialogue research group at Google (2016-2018), a principal researcher at Microsoft Research (2010-2016), International Computer Science Institute (ICSI, 2006-2010) and AT&T Labs-Research (2001-2005). She received her BSc degree from Middle East Technical Univ, in 1994, and MSc and PhD degrees from Bilkent Univ., Department of Computer Engineering, in 1996 and 2000, respectively.
Her research interests include conversational AI, natural language and speech processing, spoken dialogue systems, and machine learning for language processing. She has over 80 patents that were granted and co-authored more than 300 papers in natural language and speech processing. She received several best paper awards for publications she co-authored on conversational systems, including her earlier work on active learning for dialogue systems, from IEEE Signal Processing Society, ISCA and EURASIP. She served as an associate editor for IEEE Transactions on Audio, Speech and Language Processing (2005-2008), member of the IEEE Speech and Language Technical Committee (2009-2014), area editor for speech and language processing for Elsevier's Digital Signal Processing Journal and IEEE Signal Processing Letters (2011-2013), and served on the ISCA Advisory Council (2015-2019). She is currently the Editor-in-Chief of the IEEE/ACM Transactions on Audio, Speech and Language Processing, an IEEE Distinguished Industry Speaker (2021) and a fellow of the IEEE (2014) and ISCA (2014).
Luke Zettlemoyer is a Professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, and a Research Scientist at Facebook. His research focuses on empirical methods for natural language semantics, and involves designing machine learning algorithms, introducing new tasks and datasets, and, most recently, studying how to best develop self-supervision signals for pre-training. Honors include multiple paper awards, a PECASE award, and an Allen Distinguished Investigator Award. Luke received his PhD from MIT and was a postdoc at the University of Edinburgh.
Dan Bohus is a Senior Principal Researcher in the Adaptive Systems and Interaction Group at Microsoft Research. His work centers on the study and development of computational models for physically situated spoken language interaction and collaboration. The long term question that shapes his research agenda is how can we enable interactive systems to reason more deeply about their surroundings and seamlessly participate in open-world, multiparty dialog and collaboration with people? Prior to joining Microsoft Research, Dan obtained his Ph.D. from Carnegie Mellon University.
Quentin Lhoest is a Machine Learning Engineer at Hugging Face and the Lead Maintainer of the huggingface/datasets library. He is a former member of the Feedly team. He obtained his Master of Engineering at CentraleSupélec, and MVA Master at ENS Paris-Saclay.
Mona Diab is a Research Scientist with Facebook AI Research and she is also a full Professor of CS at the George Washington University where she directs the CARE4Lang NLP Lab. Before joining FB, she led the Lex Conversational AI project within Amazon AWS AI. Her current focus is on Responsible AI and how to operationalize for NLP technologies. Her interests span building robust technologies for low resource scenarios with a special interest in Arabic technologies, (mis) information propagation, computational socio-pragmatics, NLG evaluation metrics, and resource creation. She has served the community in several capacities: Elected President of SIGLEX and SIGSemitic. She currently serves as the elected VP-Elect for ACL SIGDAT, the board supporting EMNLP conferences. She has delivered tutorials and organized numerous workshops and panels around Arabic processing. She is a cofounder of CADIM (Consortium on Arabic Dialect Modeling, previously known as Columbia University Arabic Dialects Modeling Group), in 2005, which served as a world renowned reference point on Arabic Language Technologies. Moreover she helped establish two research trends in NLP, namely computational approaches to Code Switching and Semantic Textual Similarity. She is also a founding member of the *SEM conference, one of the top tier conferences in NLP. She currently serves as Senior area chair for multiple top tier conferences and the Diversity and Inclusion co-chair for ACL 2022. She has published more than 230 peer reviewed articles.
Dr. Yetisgen is an Associate Professor in the Department of Biomedical Informatics and Medical Education. She leads the Biomedical Language Processing group (UW-BioNLP). Before joining the University of Washington, she worked in industry as a researcher. During this period, she designed and developed statistical Natural Language Processing (NLP) systems for event extraction from various types of text. Her current research specializes on the design and development of text processing systems in the clinical domain for a wide range of secondary use applications that have direct impact on improving quality of patient care and advancing clinical research.
Adina is a Research Scientist at Facebook AI Research in NYC (started October 2018). Previously, she earned her PhD at New York University in the Department of Linguistics, where she investigated the brain basis of syntactic and semantic processing. Her main research goal is to strengthen the connections between linguistics and cognitive science on the one hand and natural language processing and artificial intelligence on the other. She approaches this process from both directions: she brings linguistic and cognitive scientific insights about human language to bear on training, evaluating, and debiasing NLP systems, and also applies statistical methods and corpus analytic tools from NLP to uncover new quantitative, cross-linguistic facts about particular human languages.
As CTO of Embodied, Stefan Scherer leads the research and development of Embodied's SocialX™ technology, a revolutionary robotics platform that interprets natural human behavior and drives believable and empathetic robotic behavior through a combination of multimodal sensing, machine learning, and natural language processing. SocialX™ allows Embodied's robot Moxie to perceive, process, and respond to natural conversation, eye contact, and facial expressions both quickly and accurately.
Prior to joining Embodied, Stefan led a successful academic career pioneering multimodal machine learning and affective computing research with applications focusing on wicked problems in healthcare (e.g., depression or suicide risk assessment) and education. As a faculty member in Computer Science at the University of Southern California (USC) and the Associate Director of Neural Information Processing at the USC Institute for Creative Technologies (ICT), Stefan secured research awards and contracts exceeding 10M USD to support his lab. His research has been funded by the National Institutes of Health (NIH) through a prestigious R01 award, the National Science Foundation (NSF), and the Department of Defense (DoD). His academic work has won several best paper awards and has been featured in international media such as The Economist, The Atlantic, Harvard Business Review, Wired Magazine, and the Guardian.
Dr. Sameer Singh is an Associate Professor of Computer Science at the University of California, Irvine (UCI) and an Allen AI fellow at Allen Institute for AI. He is working primarily on robustness and interpretability of machine learning algorithms, along with models that reason with text and structure for natural language processing. Sameer was a postdoctoral researcher at the University of Washington and received his PhD from the University of Massachusetts, Amherst. He has received the NSF CAREER award, selected as a DARPA Riser, UCI Distinguished Early Career Faculty award, and the Hellman and the Noyce Faculty Fellowships. His group has received funding from Allen Institute for AI, Amazon, NSF, DARPA, Adobe Research, Hasso Plattner Institute, NEC, Base 11, and FICO. Sameer has published extensively at machine learning and natural language processing venues and received conference paper awards at KDD 2016, ACL 2018, EMNLP 2019, AKBC 2020, and ACL 2020. (https://sameersingh.org/)
Margaret Mitchell is a researcher working on Ethical AI, currently focused on the ins and outs of ethics-informed AI development in tech. She has published over 50 papers on natural language generation, assistive technology, computer vision, and AI ethics, and holds multiple patents in the areas of conversation generation and sentiment classification. She previously worked at Google AI as a Staff Research Scientist, where she founded and co-led Google's Ethical AI group, focused on foundational AI ethics research and operationalizing AI ethics Google-internally. Before joining Google, she was a researcher at Microsoft Research, focused on computer vision-to-language generation; and was a postdoc at Johns Hopkins, focused on Bayesian modeling and information extraction. She holds a PhD in Computer Science from the University of Aberdeen and a Master's in computational linguistics from the University of Washington. While earning her degrees, she also worked from 2005-2012 on machine learning, neurological disorders, and assistive technology at Oregon Health and Science University. She has spearheaded a number of workshops and initiatives at the intersections of diversity, inclusion, computer science, and ethics. Her work has received awards from Secretary of Defense Ash Carter and the American Foundation for the Blind, and has been implemented by multiple technology companies. She likes gardening, dogs, and cats.