Shengxin (Anthony) Luo is a Ph. D. student and Dean's Fellow at the University of Miami Computer Science department, where he has been since 2016 as an undergraduate student. He has extensive knowledge in mathematics and has been awarded both Departmental Honor of Mathematics and Outstanding Senior in Mathematics from the Math department at UM. He has been a researcher in the RoboCanes lab since 2019, and his current research tasks are to program autonomous robots to perform complex and stable motion planning by utilizing concepts from algebraic and differential geometry. He participated in RoboCup Sydney DSPL league competition and is the designated team leader for the upcoming RoboCup 2021. He was also involved in several publications by the RoboCanes research group.

Zishi Wu is currently pursuing a master's degree at the University of Miami Computer Science Department. He is interested in Data Science and has interned as a data analyst at Bupa, where he worked on business intelligence dashboards and predictive models for the insurance industry. He has been selected for a PRISM fellowship to TA students in Scientific Computing and enjoys helping students. He participated in RoboCup 2019 in Sydney, where he was responsible for training the Toyota HSR to recognize objects using YOLO. Currently, his focus has shifted to creating solutions that integrate audio and lip-syncing components for a virtual avatar that can serve as an interface for human-robot interaction.

Rahul Dass is a Computer Science Ph.D. student and U-LINK Predoctoral Fellow at the University of Miami. His doctoral dissertation centers around building trustworthy computer vision systems based on multidisciplinary research and understanding its implications for all citizens when deployed in society. More specifically, he is exploring deep learning models’ sensitivity and bias based on model visualizations and data augmentations including the multi-dimensionality of labels, geometrical and texture transformations of images. In combination with theories and methods from the social sciences, he is currently investigating the extent of systemic disparities within the Miami-Dade County criminal justice system and AI-based applications in Ophthalmology. Extending into robotics, he is developing a multi-modal (2D/3D) deep learning based robot vision pipeline for object recognition to be used in conjunction with other robotic tasks such as planning and manipulation.

Christine Lisetti's long-term research goal is to create digital and engaging socially intelligent agents that can interact naturally with humans via expressive multi-modalities in a variety of contexts involving socio-emotional content (e.g. empathetic health coach, social companion, cyber-therapy, intelligent tutoring system, serious/educational game). Her research therefore lies at the intersection of human-computer interaction, affective computing (she co-founded the IEEE Transactions on Affective Computing), artificial intelligence, emotion and personality theories, social communication, and of disciplines providing the socio-emotional content where VISAGEs can be particularly helpful (e.g. healthcare, education).