Dean Hougen
About
Dr. Dean F. Hougen is a professor in the School of Computer Science at the University of Oklahoma. Dr. Hougen has a PhD in Computer Science and Engineering from the University of Minnesota, with a graduate minor in Cognitive Science, and a BS in Computer Science from Iowa State University with minors in Philosophy and Mathematics. His primary research involves artificial intelligence (AI), particularly robotics and machine learning (ML), focusing on artificial neural networks and deep learning; interpretable, informed, informative, and interactive machine learning; the evolution of learning; distributed, heterogeneous, multi- agent robotic systems and situated learning in real robotic systems; reinforcement learning, connectionist learning, and evolutionary computation. He also has strong interests in computer science education and ethics. He has also worked in the areas of expert systems, decision support systems, geographic information systems, data compression, and user interfaces. Dr. Hougen has jointly secured grant and contract awards in excess of $21M since coming to OU in 2001 and has more than 115 refereed publications in the areas of artificial intelligence, machine learning, robotics, ethics, and computer science education during his career. He has more than thirty years of experience developing AI/ML systems and fielded software and hardware systems including OU’s first official iPhone application OU2GO in Summer 2009. He has advised dozens of doctoral and masters students, as well as countless undergraduates. In 2022, Dr. Hougen was awarded the Lloyd and Joyce Austin Presidential Professorship in honor of his excellence in scholarship and teaching. In 2024, Dr. Hougen was named Director of the School of Computer Science at OU for his strategic leadership.
Research Performance Summary
First Recorded Paper
Use of an eligibility trace to self-organize output
Year: 1993
Citations: 24
Venue: Science of Artificial Neural Networks II 1966
Latest Recorded Paper
SR4-Fit: An Interpretable and Informative Classification Algorithm Applied to Prediction of US House of Representatives Elections
Year: 2026
Citations: 0
Venue: arXiv preprint arXiv:2602.06229
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.