Industrial and Human Factors Engineering, MSIHE

Parent Entity: 
Engineering and Computer Science, College of » Biomedical, Industrial and Human Factors Engineering
Program Type: 
Master
Degree Type: 
Master of Science in Industrial and Human Factors Engineering

Program Description:

The Department of Biomedical, Industrial, and Human Factors Engineering offers a program of graduate study leading to a Master of Science in Industrial and Human Factors Engineering (MSIHE) degree. The MSIHE program prepares students with skills for effective design and operation of a variety of systems in industries such as healthcare, manufacturing, aerospace, distribution, and retail. Industrial engineers utilize tools in simulation, optimization, computing, and statistics to design and improve modern technology-laden systems, while human factors engineers design systems that effectively integrate human abilities and limitations with machines and tools. The MSIHE program is very flexible and can be obtained entirely or partially through distance learning courses. Students work with a faculty advisor to plan a custom course of study within one of four focused areas of study:  Data Analytics, Logistics and Supply Chain, Human Factors and Ergonomics, or Neuroengineering. Both thesis and non-thesis (coursework) options are available.

Admissions Requirements:

To be considered for admission to the MSIHE program, students must first satisfy basic requirements of the Graduate School. This includes having a bachelor's degree in engineering or a related area with an overall undergraduate grade point average of at least 2.7 (on a 4.0 scale). International students must have a TOEFL score of at least 550/213 or an IELTS score of at least 6. In addition, the program requires students from non-ABET accredited undergraduate programs to submit GRE general test scores. Program admission decisions are based on complete application information including overall academic performance and standardized test scores where applicable.

Program Learning Outcomes:

  • Obtain depth in one area of specialization and breadth in complimentary areas.
  • Acquire scientific knowledge and research skills to solve problems in their chosen area.
  • Prepare for an advanced professional career or further graduate studies.

Facilities:

Students have access to a variety of computing platforms: general purpose software for analysis of data, software development and modeling of systems; application-specific software for use within focused areas of instruction and research. Research laboratories include

Data Analytics and Optimization Laboratory
Ergonomics in Remote Environments Laboratory
Human Centered Innovation Laboratory
Human Performance and Cognition Laboratory
Interactions Design and Modeling Laboratory
Large Scale Optimization Laboratory
System Management and Control Laboratory

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