The University of Arizona
Picture of Clayton Morrison

Clayton Morrison

Associate Professor, Statistics-GIDP | Associate Professor, School of Information | Associate Professor, Cognitive Science - GIDP | Member of the Graduate Faculty

School of Information

About

Clayton T. Morrison is an Associate Professor in the School of Information at the University of Arizona and faculty member of the Statistics Graduate Interdisciplinary Program. He leads the Machine Learning for Artificial Intelligence Laboratory ml4ai.org) Professor Morrison received his Ph.D. in Philosophy from Binghamton University in 1998 in the area of computational cognitive modeling and received his M.Sc. in computer science from University of Massachusetts in 2004. He spent five years at the University of Southern California Information Sciences Institute, for two years as a Director of Central Intelligence Postdoctoral Fellow, and then as a Research Computer Scientist He joined the University of Arizona in 2008. His current research focuses on developing machine learning and statistical modeling approaches to learning structured representations from unstructured, semi-structured and time series data. Applications include natural language processing and machine reading, biological structure and processes, computational music analysis, and modeling the relationships between human facial expressions and decision-making. His work has been funded by multiple grants from NSF, DARPA, AFOSR, and ONR. His areas of interest include Machine Learning, Natural Language Processing, and Image Analysis.

Research Area

    Page 1 of 5

    Chart
    Bar chart with 31 bars.
    The chart has 1 X axis displaying Year.
    The chart has 1 Y axis displaying values. Data ranges from 1 to 6.
    End of interactive chart.
    Recent

    Page 1 of 8

    • The Computational Language Understanding (CLU) Lab at University of Arizona is a team of faculty, students, and research programmers who work together to build systems that extract meaning from natural language texts, including question answering (answering natural language questions), information extraction (extracting specific relations and events), semantic role labeling (extracting semantic frames that model who did what to whom, when and where), parsing the discourse structure of complex texts, and other computational linguistics problems.These systems were used in several applications, ranging from extracting cancer signaling pathways from biomedical articles to automated systems for answering multiple-choice science-exam questions.The CLU lab includes members from the Computer Science department, the Linguistics department, and the School of Information. For more on natural language processing (NLP) work at UofA, please see our NLP cluster page.
    • The Machine Learning for Artificial Intelligence (ML4AI) Lab conducts research at the frontier of machine learning and artificial intelligence, with applications to a variety of domains, including automated assembly of models from natural language and software ( SKEMA, Reach, Eidos, Delphi, AutoMATES), developing AI musicians capable of collaborating and improvising with humans (Musica), and socially-aware AI agents (ToMCAT).

    • Artificial Intelligence

    • Neural Networks

    • Data Mining and Discovery

    • Research Methods for the Information Age

    • Introduction to Machine Learning

    Page 1 of 2
    Clayton Morrison | KMap Profile - Institutional Knowledge Map (KMap)