Industrial Engineering

 The program is given in Hebrew

Students in the Industrial Engineering program engage in research in a number of fields, including the design and control of production systems, project management, ergonomics, labor productivity, supply chain management, processes of learning and forgetting, and the use of simulators in employee training.

At the beginning of their academic training, Industrial Engineering students are required to take courses in quantitative mathematical concepts, as well as courses designed to broaden their knowledge of the above subjects. Early courses equip students with the tools to conduct research in Industrial Engineering, and subsequent courses provide more focused knowledge in the specific research field in which the student chooses to specialize. After completing the theoretical study component, students learn hands-on how to conduct research under the supervision of a senior faculty member.

Master’s and doctoral studies in Industrial Engineering prepare the student for employment in both industrial and research positions. Graduates of the program are unique in their ability to gather, analyze and synthesize data so as to address complex and difficult problems.

The program is designed as a full time program lasting two years. Nonetheless, both full time and part time students are accepted to the program. Scholarships are available to qualified students.

Research Topics  

The Faculty encourages interdisciplinary research and cross-field cooperation. A student from any study field may choose an academic supervisor from the faculty staff.

  • Artificial Intelligence (neural networks, computational learning, natural language processing…)
  • Electronic Markets and Electronic Commerce
  • Viral Processes (viral, ideas..) in human or computer communities
  • Cognitive Robots (artificial intelligence and robotics)
  • Game Theory and Decision Making
  • Software Engineering (complex systems modeling and analysis)
  • Knowledge and Data (information) Management
  • Mathematical Logic and program verification
  • Probability and Stochastic Processes
  • Service Engineering (queue systems in hospitals, banks etc.)
  • Data-based Operation Research
  • Efficient Optimization
  • Behavioral Economics
  •  Marketing and Strategic Theories
  •  Supply Chain in Dynamic and Multi-data environment.
  •  Various subjects in Information and Data Science. 
  • Network algorithms
  • Distributed algorithms
  • Self stabilizing systems
  • Optimization in the face of uncertainty
  • Network security and fault tolerance