Jennifer Chayes served as co-editor for Harvard Data Science Review from 2019 to 2021. Dr. Chayes is Associate Provost of Computing, Data Science, and Society, and Dean of the School of Information at University of California, Berkeley, as well as Professor in four UC Berkeley departments and schools. For 23 years, she was at Microsoft Research where she co-founded and led three interdisciplinary labs: Microsoft Research New England, New York City, and Montreal. Chayes has received numerous awards for both leadership and scientific contributions, including the Anita Borg Institute Women of Vision Leadership Award, the John von Neumann Lecture Award of the Society for Industrial and Applied Mathematics (the highest honor of SIAM), election to the American Academy of Arts and Sciences and the National Academy of Sciences, and an honorary doctorate from Leiden University. Chayes is a Fellow of many societies include the American Association for the Advancement of Science, the American Mathematical Society, the Association of Computing Machinery, the Association of Women in Mathematics, and the Fields Institutes. Chayes’ research areas include phase transitions in computer science, structural and dynamical properties of networks including graph algorithms, and applications of machine learning. Chayes is one of the inventors of the field of graphons, which are widely used for the machine learning of large-scale networks. Her recent work focuses on machine learning, including applications in cancer immunotherapy, ethical decision making, and climate change.