- BS, 2003, Harvey Mudd College
- MS, 2005, Washington
- PhD, 2010, Washington
Daniel Lowd is an Assistant Professor in the Department of Computer and Information Science at the University of Oregon. His research covers a range of topics in statistical machine learning, including statistical relational representations, unifying learning and inference, and adversarial machine learning applications (e.g., spam filtering). In 2009, he coauthored book on Markov logic with Pedro Domingos, published by Morgan & Claypool. He is also the recipient of graduate research fellowships from the National Science Foundation and Microsoft Research.