{"id":574108,"date":"2025-09-16T11:15:39","date_gmt":"2025-09-16T15:15:39","guid":{"rendered":"https:\/\/engineering.jhu.edu\/ece\/faculty\/william-redman\/"},"modified":"2026-07-01T11:51:42","modified_gmt":"2026-07-01T15:51:42","slug":"william-redman","status":"publish","type":"people","link":"https:\/\/engineering.jhu.edu\/ece\/faculty\/william-redman\/","title":{"rendered":"William Redman"},"content":{"rendered":"

William Redman is an assistant research professor of electrical and computer engineering and is affiliated with the Data Science and AI Institute.<\/p>\n

Using and developing tools from dynamical systems theory, control theory, and computational neuroscience, Redman\u2019s research aims to reveal important mechanisms underlying the dynamics of learning and the learning of dynamics in artificial and biological systems. Redman additionally serves as an action editor of Transactions in Machine Learning Research and serves on the organizing committee of the Conference on Parsimony and Learning.<\/p>\n

Before joining Johns Hopkins University, Redman got his PhD from University of California, Santa Barbara in the Dynamical Neuroscience Interdepartmental Program and was a senior research scientist at Johns Hopkins Applied Physics Lab\u2019s Intelligent Systems Center.<\/p>\n","protected":false},"template":"","class_list":["post-574108","people","type-people","status-publish","hentry"],"acf":[],"yoast_head":"\nWilliam Redman - Department of Electrical and Computer Engineering<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/engineering.jhu.edu\/faculty\/william-redman\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"William Redman - Department of Electrical and Computer Engineering\" \/>\n<meta property=\"og:description\" content=\"William Redman is an assistant research professor of electrical and computer engineering and is affiliated with the Data Science and AI Institute. 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