Organizers
Bio
Remi Denton (they/them) is a Staff Research Scientist at Google, within the Technology, AI, Society, and Culture team, where they study the sociocultural impacts of AI technologies and conditions of AI development. Prior to joining Google, Remi received their PhD in Computer Science from the Courant Institute of Mathematical Sciences at New York University, where they focused on unsupervised learning and generative modeling of images and video. Prior to that, they received their BSc in Computer Science and Cognitive Science at the University of Toronto.
Though trained formally as a computer scientist, Remi draws ideas and methods from multiple disciplines and is drawn towards highly interdisciplinary collaborations, in order to examine AI systems from a sociotechnical perspective. Remi’s recent research centers on emerging text- and image-based generative AI, with a focus on data considerations and representational harms. Remi published under the name "Emily Denton".
Bio
Dr. Hyung Jin Chang is an Associate Professor in the school of computer science at the University of Birmingham. Before joining the University of Birmingham, he was a post-doctoral researcher at Imperial College London and received his PhD degree from Seoul National University. His research combines multiple artificial intelligence areas, including computer vision, machine learning, robotics, and intelligent human-computer interaction. His research career started focusing on theoretical underpinnings of machine learning, and it has converged on applying these aspects to more practical problems in visual surveillance, HCI, and robotics, with an emphasis on estimating human eye gaze, hand pose, body pose, kinematic structure, and 6D object pose etc. Recently, his research has focused on exploiting and making advances in computer vision and deep learning techniques to move toward intelligent human-robot/human-computer interaction based on visual data. Moreover, he extends his expertise to interdisciplinary research, where he applies cutting-edge deep learning technologies to fields like brain imaging analysis for diagnostic purposes and enhancing rehabilitation exercises.
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