Esa Rantanen Headshot

Esa Rantanen

Associate Professor

Department of Psychology
College of Liberal Arts

585-475-4412
Office Location

Esa Rantanen

Associate Professor

Department of Psychology
College of Liberal Arts

Education

BS, MS, Embry-Riddle Aeronautical University; MS, Ph.D., Pennsylvania State University

Bio

Professor Rantanen trained as an airline pilot and worked as an air traffic controller before going back to school and into an academic career. Before joining the psychology faculty at RIT in 2007, Professor Rantanen was in the faculty of Institute of Aviation of the University of Illinois at Urbana-Champaign.

Professor Rantanen teaches the PSYC 642 Graduate Research Methods, PSYC 714 Graduate Engineering Psychology, and PSYC 234 Industrial and Organizational Psychology courses.

Professor Rantanen's theoretical research interests lie in the areas of human factors in complex and dynamic systems, human performance measurement and modeling, mental workload, decision making, and human error and reliability. His primary research focus is on the role of time and temporal mental models in human performance. Professor Rantanen is currently pursuing research in three applied domains: Air traffic control (air traffic controllers' situation awareness), healthcare (human error in medicine), and process control (control room displays).

Professor Rantanen is a member of the Human Factors and Ergonomics Society (HFES; since 1993), Institute of Electrical and Electronics Engineers (IEEE Systems, Man, and Cybernetics Society; since 1997), and Association for Aviation Psychology (AAP; since 1999). He serves in the editorial boards of journals 'Human Factors' and 'International Journal of Aviation Psychology'. 

585-475-4412

Personal Links

Select Scholarship

Dr. Esa Rantanen is a member of the faculty team of the AWARE-AI NSF Research Traineeship (NRT) Program. Graduate students from associated RIT PhD and MS programs are invited to review information on how to apply and benefits for Trainees at our website: https://rit.edu/nrtai. Women, Deaf or Hard-of-Hearing, and African American, Latino/a American, or Native American students are especially encouraged to apply.

Currently Teaching

ISEE-734
3 Credits
In this course the students will learn to recognize the integrated (systems) nature of Engineering Psychology, the centrality of human beings in systems design, and to use the topics covered and the available knowledge base to adapt the environment to people. This course will cover several fundamental models of human information processing in the context of human-system interactions. The models may include but are not limited to Signal Detection Theory, Information Theory, theories of attention, both normative and naturalistic decision making-models, Control Theory, and the Lens Model of Brunswick, as well as models of the human as a physical engine, that is, anthropometry, biomechanics, and work physiology. Most topics include readings in addition to the course text as well as a lab exercise with a detailed lab report.
PSYC-101
3 Credits
Introduction to the field of psychology. Provides a survey of basic concepts, theories, and research methods. Topics include: thinking critically with psychological science; neuroscience and behavior; sensation and perception; learning; memory; thinking, language, and intelligence; motivation and emotion; personality; psychological disorders and therapy; and social psychology.
PSYC-234
3 Credits
Industrial and organizational (I/O) psychology is a branch of applied psychology that is concerned with efficient management of an industrial labor force and especially with problems encountered by workers in a mechanized environment. Specific areas include job analysis, defining and measuring job performance, performance appraisal, tests, employment interviews, employee selection and training, and human factors. This course covers the basic principles of the above areas as well as applications of current research in I/O psychology.
PSYC-251
3 Credits
This course will serve as an advanced research methods course in psychology, and will build on the foundational knowledge presented in Research Methods I. Topics and tasks for this course include designing single and multi-factor experiments, interpreting correlational research, completing statistical analyses appropriate to design, completing and analyzing an IRB application, understanding observational and survey research, and presenting results in APA style. This is a required course for all psychology majors, and is restricted to students in the psychology program.
PSYC-714
3 Credits
In this course the students will learn to recognize the integrated (systems) nature of Engineering Psychology, the centrality of human beings in systems design, and to use the topics covered and the available knowledge base to adapt the environment to people. This course will cover several fundamental models of human information processing in the context of human-system interactions. The models may include but are not limited to Signal Detection Theory, Information Theory, theories of attention, both normative and naturalistic decision-making models, Control Theory, and the Lens Model of Brunswick, as well as models of the human as a physical engine, that is, anthropometry, biomechanics, and work physiology. Most topics include readings in addition to the course text as well as a lab exercise with a detailed lab report.
PSYC-719
1 Credits
This course will provide students with fundamental information for human-centered design of applications of artificial intelligence. There are three parts to the course: The first part is about methods of design and evaluation. The second part introduces students to the psychology of sensation and perception, memory, attention, judgment, decision-making, and problem solving, as well as human error and reliability. Finally, students will become familiar with design principles as they apply to displays and controls, human-computer interaction, human-automation interaction, and human-centered automation. Guest lectures and case studies will be examined to illustrate topics covered in it and to provide a survey of the current state of AI research, development, and controversies. Ethics and moral responsibility in technology development, with links to current policy debates, are also discussed in this context.