Teaching and Advising

Graduate Program:

MS in Human Factors Program, Northeastern University

Research in the field of human factors has a significant impact on our day-by-day life. Its application to system design improves ease of use, system performance and reliability, and user satisfaction while reducing operational errors, operator stress, training requirements, user fatigue, and product liability. Human factors engineering is distinctive in being the only discipline that relates humans to technology.




IE 7315 Human Factors Engineering

Offers students an opportunity to acquire the necessary knowledge and skills to recognize and analyze existing or potential human factors problems and to identify, design, and possibly implement feasible solutions. Includes an introduction to human factors and ergonomics; engineering anthropometry and biomechanics; physiology related to human factors and workstation design; cognition and information processing; decision making, attention, and workload; human error and accidents; human-machine interface design; controls and displays; and human factors applications in transportation, aerospace, consumer product design, and so forth.

IE 6500 Human Performance

Studies the integration of sociotechnical systems in order to improve productivity, efficiency, safety, and quality of work life. In particular, this involves designing jobs, machines, operations, and work environments in systems and organizations so that they are compatible with human capabilities, characteristics, and limitations. Covers a wide range of sociotechnical systems and is focused on human performance, human-system integration, and evaluation. Discusses a variety of sociotechnical systems and interactions, including transportation, healthcare, manufacturing and service industries, and human-computer and human-robot interaction.

IE 5630 Biosensors and Human Behavior Measurement

Emphasizes the measurement of human behavior in complex human-machine interaction. Topics include the introduction of complex human-machine interactions; research methods in complex human-machine interactions; various kinds of human psychophysiological signals/cues, including physiological cues, facial expressions, eye-gaze movement, head movement, contextual cues; human cues and behavior relationship; transducers and measurement for these human cues/signals; basic principles of biosensors; general classification of biosensors; current technologies for building biosensors; conventional transducers and new technologies including micro-/nanotechnology; general systematic design process for biosensors; application of biosensors to understand human behavior in human-machine interactions. It also introduces the latest relevant research advancements in sensor fusion, affective computing, and emotion recognition.

MEIE 4701/2 Capstone Design

Offers the first in a two-course sequence that culminates the student’s education and experience with the design process. Students form teams and are assigned their design projects and faculty adviser. Projects can be industrially, departmentally, or externally sponsored. Students are expected to communicate with their faculty adviser, course coordinator, and sponsor using the Internet, teleconferencing, and other electronic methods. Topics include project management, ethics, cost analysis, Internet and library research methods, and engineering codes and standards. Students prepare written reports and make oral presentations. Students are expected to complete a thorough state-of-the-art report on their problem and a problem statement with specifications and requirements.

IE 4535 Human-Machine Systems in a Global Context (Dialogue of Civilizations)

Introduces human-machine systems in an international setting. Students have an opportunity to travel to a foreign country to develop theoretical understanding while experiencing the issues and human factors considerations in a global environment.

IE 4699 Special Topics in IE: Human-Machine Systems in a Global Environment

Topics include human performance, information processing, learning, memory; vision, visual performance, interface display design; audition, noise, hearing and auditory signals; human anthropometric characteristics; cognition, usability testing, and principles of human-machine interface design. Laboratory experiences include design of experiment, data collection, analysis, and laboratory reports generation. Includes a project that focuses on applications that allow students to delve into issues that affect engineering and technology development in their host country.




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