Susanne Still

  • Professor of Information and Computer Sciences, University of Hawai`i at Mānoa

    Susanne Still is Professor of Information and Computer Sciences at the University of Hawai`i at Mānoa, where she leads the Machine Learning and Physics of Information Laboratory and developed the machine learning curriculum. A physicist by training, she also serves as contributing graduate faculty in the Department of Physics and Astronomy. She serves on the Editorial Board of Entropy. She is a member of the Foundational Questions Institute, from which she has received several research grants. Her work has advanced our understanding of the physics of information processing, in particular the thermodynamic analysis of learning (understood as a process in which memories are formed to make predictions), the stochastic thermodynamics of strongly coupled systems, and the thermodynamics of information engines. In the context of information theoretically motivated learning methods, Prof. Still pioneered approaches to dynamical and interactive learning, and generalizations to quantum information processing. She has contributed to the foundations of information theory and applied her expertise in statistical learning theory and support vector machines to mathematical finance and robotics.