Organizing Committee (in alphabetical order)

• Yoav Artzi is an Associate Professor in the Department of Computer Science and Cornell Tech at Cornell University. He holds a B.Sc. from Tel Aviv University and a Ph.D.from the University of Washington. Along his academic work, he conducts research at ASAPP. He studies methods for natural language understanding and generation in automated, situated systems. His research goals are: (a) to build computer systems that interact with users using natural language and continuously improve through interaction, and (b) to develop computational understanding of natural language as a communication system. A core principle underlying his current work is that learning,production, and comprehension of natural language does not occur in isolation, but within dynamic interactions with other intentional agents situated in a shared environment.
• Kianté Brantley is a Postdoctoral scholar at Cornell working with Thorsten Joachims. He complete his Ph.D. in computer science at the University of Maryland College Park (UMD) advised by Professor Hal Daumé III. Brantley designs algorithms that efficiently integrate domain knowledge into sequential decision-making problems. He is most excited about imitation learning and interactive learning or, more broadly, settings that involve a feedback loop between a machine learning agent and the input the machine learning agent sees.
• Soham Dan is a Research Scientist at IBM. He completed his Ph.D. in Computer and Information Science at the University of Pennsylvania, advised by Dan Roth. His research focuses on natural language understanding, specifically for instruction following tasks. He is interested in interactive learning, compositional generalization, neuro-symbolic algorithms, and robust learning from limited supervision.
• Khanh Nguyen is a postdoc researcher at Princeton University. He received a PhD in Computer Science at the University of Maryland–College Park. His research focuses on building agents that can communicate naturally and effectively with humans to better assist them.
• Ji-Ung Lee is a PhD student at the Technical University of Darmstadt. His research focuses on effective model training from user feedback in low-data scenarios coupled with providing the user with instances that fit their needs.
• Edwin Simpson is a lecturer at the University of Bristol working on interactive learning for NLP and machine learning for crowdsourced annotation with an interest in Bayesian methods for handling uncertainty.
• Alane Suhr is a PhD Candidate in the Department of Computer Science at Cornell University. Her research spans natural language processing, machine learning, and computer vision, with a focus on building systems that participate and continually learn in situated natural language interactions with human users.