Dana Nau is a Professor at the University of Maryland, in the Computer Science Department and the Institute for Systems Research. He does research in both automated planning and game theory. Some of his accomplishments include the discovery of pathological game trees, the AI planning and game-tree search algorithm that won the 1997 world championship of computer bridge, work with social psychologists on evolutionary game theoretic studies of the evolution of human behavioral norms, the AI planning systems SHOP, SHOP2, and Pyhop, and two graduate-level textbooks: Automated Planning: Theory and Practice (2004), and Automated Planning and Acting (2016). He has nearly 400 refereed publications, and he is an AAAI Fellow, an ACM Fellow, and an AAAS Fellow.

Matthias Scheutz received a PhD degree in philosophy from the University of Vienna and a joint Ph.D. in cognitive science and computer science from Indiana University. He is the Karol Family Applied Technology Professor of computer and  cognitive science in the Department of Computer Science at Tufts University in the School of Engineering, and Director of the Human-Robot Interaction (HRI) Laboratory and the HRI Masters and PhD programs.  He has over 400 peer- reviewed publications in artificial intelligence, artificial life, agent-based computing, natural language understanding, cognitive modeling, robotics, human-robot interaction and foundations of cognitive science.  His current research focuses on complex ethical cognitive robots with natural language interaction, problem-solving, and instruction-based learning capabilities in open worlds.

Stefanie Tellex is an Associate Professor of Computer Science at Brown University.  Her group, the Humans To Robots Lab, creates robots that seamlessly collaborate with people to meet their needs using language, gesture, and probabilistic inference, aiming to empower every person with a collaborative robot.  She completed her Ph.D. at the MIT Media Lab in 2010, where she developed models for the meanings of spatial prepositions and motion verbs.  Her postdoctoral work at MIT CSAIL focused on creating robots that understand natural language. She has published at SIGIR, HRI, RSS, AAAI, IROS, ICAPs and ICMI, winning Best Student Paper at SIGIR and ICMI, Best Paper at RSS, and an award from the CCC Blue Sky Ideas Initiative.  Her awards include being named one of IEEE Spectrum's AI's 10 to Watch in 2013, the Richard B. Salomon Faculty Research Award at Brown University, a DARPA Young Faculty Award in 2015, a NASA Early Career Award in 2016, a 2016 Sloan Research Fellowship, and an NSF Career Award in 2017.  Her work has been featured in the press on National Public Radio, BBC, MIT Technology Review, Wired and Wired UK, as well as the New Yorker.  She was named one of Wired UK's Women Who Changed Science In 2015 and listed as one of MIT Technology Review's Ten Breakthrough Technologies in 2016.

Chien-Ming Huang is the John C. Malone Assistant Professor in the Department of Computer Science at the Johns Hopkins University. His research focuses on designing interactive AI aimed to assist and collaborate with people. He publishes in top-tier venues in HRI, HCI, and robotics including Science Robotics, HRI, CHI, and CSCW. His research has received media coverage from MIT Technology Review, Tech Insider, and Science Nation. Huang completed his postdoctoral training at Yale University and received his Ph.D. in Computer Science at the University of Wisconsin–Madison. He is a recipient of the NSF CAREER award. https://www.cs.jhu.edu/~cmhuang/