Ashia Wilson joined the Department of Electrical Engineering and Computer Science as an Assistant Professor in January. Wilson received her PhD in Statistics from the University of California, Berkeley, and her BA in Applied Mathematics from Harvard. Her research centers upon optimization, algorithmic decision making, dynamical systems, and fairness within large scale machine learning. A National Science Foundation Graduate Research Fellow, Wilson has received the NeurIPS ’17 Spotlight Paper Award for The Marginal Value of Adaptive Methods in Machine Learning, and has performed research with Microsoft and Google AI. Her papers have been published in the Proceedings of the National Academy of Science, in Advances in Neural Information Processing Systems, and in the International Conference of Machine Learning, among others. Additionally, she has served as a reviewer for NeurIPS and the Journal of Machine Learning.