Fall 2020

Maria Kyrarini

Maria Kyrarini

Postdoctoral Research Fellow
UT Arlington


Friday, 10/16/20 at 12:00 PM - 1:00 PM (Central)


Making robots more personal and understanding

Watch the Video


Robots have become part of our everyday lives and have several roles, such as helping workers in their work duties, assisting people with impairment in activities of daily living, entertaining and keeping company to children and the elderly, and assisting rehabilitation procedures. In industrial environments, such as assembly lines, a strong level of interaction and cooperation is reached where humans and robots are required to work synergistically on a specific task and have different roles and complementary abilities. However, there is a need on understanding the psychological influence on the human who cooperates with a robot on a daily basis. This talk introduces a real-time framework that assesses the cognitive load of a human while cooperating with a robot to complete a collaborative assembly task. The framework uses multi-modal sensory data from Electrocardiography (ECG) and Electrodermal Activity (EDA) sensors, extracts novel features from the data and utilizes machine learning methodologies to detect high or low cognitive load. The developed framework was evaluated on a collaborative assembly scenario with a user study.


Maria Kyrarini is a postdoctoral research fellow at the University of Texas at Arlington under the advisement of Professor Dr. Fillia Makedon. She is also the assistant director of the Heracleia Human-Centered Computing Lab. In 2019, Maria received her Ph.D. in Engineering from the University of Bremen under the supervision of Professor Dr.-Eng. Axel Gräser. The title of her Ph.D. thesis is: "Robot learning from human demonstrations for human-robot synergy". Before that, she received her M.Eng. degree in Electrical and Computer Engineering and her M.Sc. degree in Automation Systems both from the National Technical University of Athens (NTUA) in 2012 and 2014, respectively. Her primary research interests are in the fields of Robot Learning from Human Demonstrations, Human-Robot Interaction, and Assistive Robotics with a special focus on Enhancing Human Performance.