Contact Information:

T. Steven Cotter, Ph.D.

Master Lecturer

Department of Engineering Management & Systems Engineering

Systems Engineering and Research, Rm. 2101I

Batten College of Engineering and Technology

Old Dominion University

Norfolk, Virginia, USA, 23529

Telephone: 757-683-3758

E-mail: tcotter@odu.edu

Biography

T. Steven Cotter (BS, MBA, MS, PhD) is a Senior Lecturer with the Engineering Management and Systems Engineering department at Old Dominion University. He is a Certified Quality Engineer and Certified Reliability Engineer with the American Society for Quality. He holds certifications as a SQL Server Application Developer and Database Administrator. He has over 40 years of experience in quality and production engineering and management in automated chemicals manufacturing, automated computer manufacturing, and defense electronics. He has supported projects for the startup of two production facilities and a research and development center. He has managed projects for Six Sigma quality improvement, automated quality information systems, and automated measurement systems. He lectured for five years as an Adjunct Assistant Professor before joining the Department of Engineering Management and Systems Engineering as full-time faculty. His research initiatives are in computational systems statistical engineering, AI-Human quality and reliability systems, AI-human knowledge engineering, and digital engineering informatics.

Education

Ph.D. Engineering Management and Systems Engineering, 2005

Old Dominion University

M.S. Engineering Managment, 1994

Concentration: Quality and Reliability Engineering

University of Massachusetts at Amherst

M.B.A., 1989

Concentration: Finance

BS, 1986

Concentration: Management

University of South Carolina

Electronic Technology, 1971

Graff Area Vocational and Technical School

(now Ozarks Technical Community College)

Professional Associations

American Society for Engineering Management

American Society for Quality

  • Certified Quality Engineer
  • Certified Reliability Engineer

Association for Computing Machinery

INFORMS

Institute of Electrical and Electronics Engineers

International Statistical Engineering Association

Teaching Philosophy

Coming from an industrial engineering, managerial, and teaching background, I view students as both my customer and product. My objectives in interacting with, mentoring, and teaching students are to facilitate their transition into an integrated management, engineering, and technology education and to support their maturation through that education into functioning professional technicians, engineers, and engineering managers who represent their school and chosen disciplines with the highest degree of integrity and competence. I support student transition and maturation through a mentoring Socratic teaching style supplemented with learning experiences including sequenced problem analysis and solution activities, case studies, and research, documentation, and presentation with defense. I use the Socratic Method in lecture, questioning, and testing to guide students toward a greater understanding of the required engineering or technical knowledge. I use learning experiences as a discovery process to support greater understanding and increased performance. As a former industrial manager, I set the expectation that students contribute as much effort in attaining managerial, engineering, or technical education as I do in providing it.

Courses Taught

ENMA 302, Engineering Economics

ENMA 401, Project Management

ENMA 420/520, Statistical Concepts in Engineering Management

ENMA 605 Capstone Project

ENMA 614, Quality Systems Design

ENMA 711/811, Methodology for Advanced Engineering Projects

ENMA 720/820, Multivariate Analysis for Engineering Research

ENMA 897 Special Topics Courses

* Applied Ontology Engineering

* Hybrid Ai-Human Systems Control

* Psychology of Judgment and Decision Making

* Quality Systems Risk Engineering

* Software Quality Engineering

Research Areas

  • AI-Human Knowledge Ontology Engineering
  • AI-embedded Quality and Reliability Engineering
  • Computational Systems Engineering
  • Cyber Physical Systems Engineering
  • Digital Engineering Informatics
  • Multivariate Computational Statistical Learning