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OBU—Oklahoma Baptist University
Dr. Timothy Darr
Dr. Timothy Darr

Dr. Timothy Darr

Lawrence Peitz Chair of Business
Assistant Professor of Computer Information Science

See full CV.

Biography

Dr. Timothy P. Darr joined OBU with more than twenty years experience in the computer science and computer information systems industry. Dr. Darr is passionate about preparing students for careers in computer science and information technology by providing the skills and tools that employers value (not just Theory or book learning).

In addition, Dr. Darr believes that CS practitioners of faith need to be aware of issues related to Christian faith and computer science (specifically artificial intelligence), such as:

  • What does it mean to be human?
  • What is intelligence?
  • Will we ever achieve the goal of general artificial intelligence (AGI)?

To that end, in each CS course, students will read and discuss short books that address these issues written by leading Christian philosophers and thought leaders such as John Lennox, Donald Knuth, Ros Picard and Sharon Dirckx.

Dr. Darr is an (ongoing) artificial Intelligence (AI) technology researcher and practitioner with particular focus on knowledge representation, human decision modeling, and intelligent agent modeling. He has practical experience in applying a multitude of cutting-edge technologies to real-world problems, including: natural language processing and understanding, data mining, machine learning, deep learning with neural networks, sentiment and opinion mining, social network analysis, and social media analytics. He has working familiarity with a variety of programming languages (C, Java, Python, Clojure, Visual Basic, Prolog, Lisp), data and knowledge models (RDF/OWL, JSON, XML/XSL), query languages (SQL, SPARQL), programming methods (object-oriented, functional), and software project management methods (waterfall, agile, scrum, X programming). Dr. Darr’s publications have appeared in refereed journals and conferences. His research has appeared in invited workshops. He has co-authored chapters in books on concurrent engineering and expert systems.

Dr. Darr has successfully led small development teams delivering customer success in the government and commercial sectors. In the government sector, he led agile teams in transitioning applied research solutions to the Navy, Air Force, Army and intelligence community. In the commercial sector, he led teams in building and customizing knowledge bases for enterprise-scale applications in the computer and telecommunications industries for Fortune 500 companies.

Education

  • Ph. D. Computer Science and Engineering (May 1997) - The University of Michigan
  • M. S. E. Computer Science and Engineering (May 1992) - The University of Michigan
  • B. S. E. Computer Engineering Summa Cum Laude (December 1988) - The University of Michigan

Subjects Taught

  • Basic Programming Concepts
    • Introduction to Programming - Python
    • Computer Science I and II (Java)
    • Introduction to Web Development
  • Advanced Programming Concepts / Software Engineering
    • Programming Languages
    • Data Structures
    • Systems Analysis
    • Software Development Project I and II
  • Computer Hardware
    • Computer Systems and Organization
    • Logic Design
  • Introduction to Data Science
  • Honors Business Colloquia on topic of the intersection of Christian faith and Artificial Intelligence

Professional Memberships

  • Christian Engineering Society
  • Association for the Advancement of Artificial Intelligence (AAAI)
  • IEEE
  • Association for Computing Machinery (ACM)

Selected Publications

  • Hancock, B. J., Darr, T. P., Hazell, R., Grazaitis, P., "Integrating Civil Affairs Through the Application of Battlefield Relevant Civil Information Management," Civil Affairs Association Issue Papers (to appear), 2019.
  • Darr, T. P., Mayer, R., Jones, R. D., Ramey, T., Smith, R. and Zimmerman, C., "Quantum Probability Models for Decision Making," in 24th International Command and Control Research & Technology Symposium, Laurel, MD, 2019.
  • Houser, D., Wang, J., Darr, T. P. & Mayer, R., (2019). Time pressure improves decisions in generalized Colonel Blotto games. 24th International Command and Control Research & Technology Symposium. Laurel, MD
  • Darr, T.P., Benjamin, P. and Mayer, R., “A Utility-Theoretic Preference Model for OPFOR Course-of-Action Selection and Assessment”, HSCB Focus 2011: Integrating Social Science Theory and Analytic Methods for Operational Use, February 8-10, 2011.
  • Darr, T. P. and Birmingham, W. P., “Part-selection Triptych: A Representation, Problem Properties and Problem Definition, and Problem-solving Method”, AI EDAM, Vol. 14, No. 1, 2000, pp. 39-52.

Selected Lectures

  • OBU Philosophy Forum, April 8, 2022 - "Imago hominis: A Gentle Introduction to Artificial Intelligence and the Imago Dei"