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Industrial Engineering

Research Methodologies

Systematic Research

Through collaborations among the faculty members within the Department of Industrial Engineering, five research methodologies were formed out of the areas of specialization.

  1. Optimization
  2. Natural Decision Making and Resilience Engineering
  3. Statistical Modeling and Learning
  4. Stochastic Modeling and Systems
  5. Task Analysis
Two people sitting at computer viewing data points.
Person using glass wall to perform Optimization research


Our methodological research in optimization spans theory, analysis, and design of computationally efficient, robust, and scalable algorithms to handle real-world problems in engineering, operations, economics, and business.

Optimization Research

Naturalistic Decision Making

A key theme is identifying adaptive patterns and emergent properties of systems through proactive learning. Insights can be used to inform decisions at various organizational levels and in complex naturalistic environments in various domains such as healthcare, education, and crisis response.

Naturalistic Research
Decision making during Crisis Response
Ergonomics use through statistical modeling

Statistical Modeling and Learning

Going from data to models, our methodological research is shaped around devising novel frameworks that can lead to fair and interpretable decisions and insights. Key drivers are the availability of data and computational powers in the last decade.

Statistical Modeling Research

Stochastic Modeling and Systems

Stochastic modeling is built upon probability theory, statistics, and stochastic processes to address uncertain, complex physical, cyber, and service systems. Our research spans a host of applications in supply chains and healthcare systems.

Stochastic Modeling Research
Supply chain logistics through Stochastic modeling and systems research
Qualitative Data Analysis for Task Analysis Research

Task Analysis

The Department of Industrial Engineering is dedicated to gaining and sharing a better understanding of how tools, technologies, and work practices affect health and performance and how they can be improved through human-centered design.

Task Analysis Research