2^nd Workshop on Advances in Language and Vision Research (ALVR)

Jacob Andreas is the X Consortium Career Development Assistant Professor at MIT. His research focuses on building intelligent systems that can communicate effectively using language and learn from human guidance. Jacob earned his Ph.D. from UC Berkeley, his M.Phil. from Cambridge (where he studied as a Churchill scholar) and his B.S. from Columbia. He has been the recipient of an NSF graduate fellowship, a Facebook fellowship, and paper awards at NAACL and ICML.

Jason is a research scientist at Google, where he works on natural language understanding. He was previously an Associate Professor of Computational Linguistics at the University of Texas at Austin. His main research interests include categorial grammars, parsing, semi-supervised learning for NLP, reference resolution and text geolocation. He has long been active in the creation and promotion of open source software for natural language processing, including co-creating the Apache OpenNLP Toolkit and OpenCCG. Jason received his Ph.D. from the University of Edinburgh in 2002, where his doctoral dissertation on Multimodal Combinatory Categorial Grammar was awarded the 2003 Beth Dissertation Prize from the European Association for Logic, Language and Information.

Dr. Mohit Bansal is the John R. & Louise S. Parker Associate Professor and the Director of the MURGe-Lab (UNC-NLP Group) in the Computer Science department at University of North Carolina (UNC) Chapel Hill. He received his PhD from UC Berkeley in 2013 (where he was advised by Dan Klein) and his BTech from IIT Kanpur in 2008. His research expertise is in statistical natural language processing and machine learning, with a particular focus on multimodal, grounded, and embodied semantics (i.e., language with vision and speech, for robotics), human-like language generation and Q&A/dialogue, and interpretable and generalizable deep learning.

Yonatan Bisk is an Assistant Professor at Carnegie Mellon University. Yonatan’s research area is Natural Language Processing (NLP) with a focus on grounding. In particular, his work broadly falls into: 1. Uncovering the latent structures of natural language, 2. Modeling the semantics of the physical world, and 3. Connecting language to perception and control.

Joyce Y. Chai is a Professor at University of Michigan. Her research interests are in the area of artificial intelligence, particularly on natural language processing, situated dialogue agents, human-robot communication, and intelligent user interfaces. Her recent work has focused on grounded language processing to facilitate situated communication with robots and other artificial agents. Prior to joining UM, she was a professor at MSU directing the Language and Interaction Research Lab . At UM, she is a member of Michigan AI Lab and directing the Situated Language and Embodied Dialogue (SLED) research group. She is also affiliated with Michigan Robotics Institute.

Yejin Choi is an associate professor of Paul G. Allen School of Computer Science & Engineering at the University of Washington with the Brett Helsel Career Development Professorship, adjunct of the Linguistics department, and affiliate of the Center for Statistics and Social Sciences. She is also a senior research manager at the Allen Institute for Artificial Intelligence overseeing the project Mosaic on Commonsense Intelligence. She is a co-recepient of the AAAI Outstanding Paper Award in 2020, the Marr Prize (best paper award) at ICCV 2013, a recepient of Borg Early Career Award (BECA) in 2018, and named among IEEE AI's 10 to Watch in 2016.

Raymond J. Mooney is a Professor in the Department of Computer Science at the University of Texas at Austin. He received his Ph.D. in 1988 from the University of Illinois at Urbana/Champaign. He is an author of over 160 published research papers, primarily in the areas of machine learning and natural language processing. He was the President of the International Machine Learning Society from 2008-2011, program co-chair for AAAI 2006, general chair for HLT-EMNLP 2005, and co-chair for ICML 1990. He is a Fellow of the American Association for Artificial Intelligence, the Association for Computing Machinery, and the Association for Computational Linguistics and the recipient of best paper awards from AAAI-96, KDD-04, ICML-05 and ACL-07.

Anna Rohrbach is a Research Scientist at UC Berkeley, working with Prof. Trevor Darrell. She has completed her PhD at Max Planck Institute for Informatics under supervision of Prof. Bernt Schiele. Her research is at the intersection of vision and language. She is interested in a variety of tasks, including image and video description, visual grounding, visual question answering, etc. Recently, she is focusing on building explainable models and addressing bias in existing vision and language models.

Kate is an Associate Professor of Computer Science at Boston University and a consulting professor for the MIT-IBM Watson AI Lab. She leads the Computer Vision and Learning Group at BU, is the founder and co-director of the Artificial Intelligence Research (AIR) initiative, and member of the Image and Video Computing research group. Kate received a PhD from MIT and did her postdoctoral training at UC Berkeley and Harvard. Her research interests are in the broad area of Artificial Intelligence with a focus on dataset bias, adaptive machine learning, learning for image and language understanding, and deep learning.

William Wang is the Director of UC Santa Barbara's Natural Language Processing group and Center for Responsible Machine Learning. He is the Duncan and Suzanne Mellichamp Chair in Artificial Intelligence and Designs, and an Assistant Professor in the Department of Computer Science at the University of California, Santa Barbara. He received his PhD from School of Computer Science, Carnegie Mellon University. He has broad interests in machine learning approaches to data science, including statistical relational learning, information extraction, computational social science, speech, and vision.