Daniel Lowd, Department of Computer Science

Daniel Lowd

Daniel Lowd

Professor
Practice Areas: Machine Learning, Artificial Intelligence

Faculty bio | 541-346-4154


Biography:

Daniel Lowd is an academic expert in machine learning and artificial intelligence. His specific expertise includes adversarial machine learning. These are problems like spam and fraud detection, where it's difficult to build good models because people will always be working to trick them. Daniel researches a range of problems in this area, including understanding the vulnerabilities of popular machine learning methods, how an attacker could exploit them, and how we can build models that are more robust and reliable.

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