Katherine E. Isaacs

Katherine E. Isaacs is an Associate Professor at the University of Utah, where she is part of the School of Computing and the Scientific Computing and Imaging (SCI) Institute. Her academic journey is marked by a profound dedication to the fields of data visualization and computing systems. Katherine's research primarily focuses on developing innovative methods to represent complex computing processes, enabling a deeper exploration and analysis of their behavior. Her work is pivotal in various domains, including high-performance computing, distributed computing, data science, program analysis, and optimization. Katherine's contributions have been recognized through prestigious awards, such as the National Science Foundation (NSF) CAREER grant and the Department of Energy (DOE) Early Career Research Program grant. These accolades underscore her commitment to advancing the frontiers of computing and visualization. Currently, Katherine is engaged in several cutting-edge projects. One of her key endeavors involves enhancing node-link diagrams for graph visualizations within computing systems. This work aims to improve the clarity and effectiveness of visual representations, facilitating better understanding and analysis. Additionally, she is exploring "traveler," a node-to-code visualization tool designed for performance analysis, which promises to revolutionize how performance data is interpreted and utilized. Katherine is also delving into the realm of interactive visualization within Jupyter Notebooks, a popular tool among data scientists and researchers. Her research seeks to enhance the interactivity and usability of visualizations in this environment, making data analysis more intuitive and accessible. Furthermore, she is examining how individuals conceptualize and think about data, a study that holds significant implications for the design of user-friendly data analysis tools. Through her work, Katherine E. Isaacs continues to push the boundaries of what is possible in data visualization and computing systems, contributing valuable insights and tools that empower researchers and practitioners across various disciplines. Her dedication to her field and her innovative approach to problem-solving make her a leading figure in the world of computing research.