Keynotes


Augmenting vs. Assisting Humans with Pervasive Technology?

Yvonne Rogers

Yvonne Rogers

Professor of Interaction Design
University College London
y.rogers@ucl.ac.uk

Biography:
Yvonne Rogers
is a Professor of Interaction Design, the director of UCLIC and a deputy head of the Computer Science department at University College London. Her research interests are in the areas of interaction design, human-computer interaction and ubiquitous computing. A central theme of her work is concerned with designing interactive technologies that augment humans. A current focus of her research is on human-data interaction and human-centered AI. Central to her work is a critical stance towards how visions, theories and frameworks shape the fields of HCI, cognitive science and Ubicomp. She has been instrumental in promulgating new theories (e.g., external cognition), alternative methodologies (e.g., in the wild studies) and far-reaching research agendas (e.g., "Being Human: HCI in 2020"). She is a fellow of the ACM, BCS and the ACM CHI Academy.



Robots and Language: Grounded Language Learning from Human Interaction

Cynthia Matuszek

Cynthia Matuszek

Assistant Professor
Interactive Robotics and Language (IRAL) Lab, UMBC
cmat@umbc.edu
http://iral.cs.umbc.edu - http://www.csee.umbc.edu/~cmat

Biography:
Cynthia Matuszek is an assistant professor of computer science and electrical engineering at the University of Maryland, Baltimore County, and the director of UMBC’s Interactive Robotics and Language lab. She received her Ph.D. in computer science and engineering from the University of Washington. Her research is focused on how robots can learn grounded language from interactions with non-specialists, which includes work in not only robotics, but human-robot interactions, natural language, machine learning, machine bias, and collaborative robot learning, informed by a background in common-sense reasoning and classical artificial intelligence. Dr. Matuszek's work has been published in machine learning, artificial intelligence, robotics, and human-robot interaction venues.



Supervision Signals for Machine Learning in Healthcare and Beyond

Ismini Lourentzou

Dr. Ismini Lourentzou

Assistant Professor
Virginia Tech
ilourentzou@vt.edu

Biography:
Dr. Ismini Lourentzou is an assistant professor of computer science at Virginia Tech. Her research interests are at the intersection of machine learning and data science, specifically in learning with limited imperfect supervision, self-supervision, multi-modal representation learning with applications to vision and language, and sequential decision making. Dr. Lourentzou's research is focused on building intelligent task assistants that augment human intelligence, and her work has been published in artificial intelligence, machine learning, and data science venues and journals. She obtained her Ph.D. from the Computer Science Department at the University of Illinois at Urbana - Champaign. Dr. Lourentzou was selected as a Rising Star in EECS in 2019, has received an NSF EAGER grant, a Microsoft Azure Research Award, and an IBM Invention Plateau.