Information Management Engineering

 The program is given in Hebrew

Program Objectives

Ongoing developments in the field of information technologies are enabling the creation of information systems with steadily increasing scale and sophistication.  Concurrently, the demands of information systems users are also on the rise. As a result, systems engineers are required to develop products and applications whose complexity and intricacy are progressively increasing.  These systems utilize state-of-the-art technologies that include communication and distributed systems, command and control using artificial intelligence, data organization and retrieval, organizational resource management systems, electronic trade systems, integrated hardware and software systems and decision support systems.

The master’s program in Information Management Engineering, offered by the Information Systems Area in the Technion’s Faculty of Industrial Engineering and Management, places an emphasis on research.  Students will participate in research studies essential for the management of complex systems conducted by faculty members in the fields of science and technology.  The list of fields in which faculty members currently work includes systems engineering and systems analysis, software engineering, software testing and verification, databases and data storage, artificial intelligence and autonomous systems, communication, distributed systems, information retrieval, and natural language processing, as well as more general topics such as algorithms, game theory and human factors engineering, all at an advanced level.

The master’s degree graduate program confers an MSc in Information Management Engineering.

Graduates of the program participate in academic and research and development activities, where they utilize their know-how and research capabilities developed during the course of the graduate program.  As part of their research study, graduate students uncover new principles and methods with which they can enhance systems or which can constitute a basis for repurposed systems.  Another possibility is an emphasis on development, where graduates can create or improve infrastructure products or intelligent and complex information systems for organizations.  In order to reach these goals, the graduate student requires a knowledge base that includes most of the following fields: basic information technologies, software engineering, algorithmetics and operations research, artificial intelligence, communications, data mining, databases and cognitive sciences.  Ideally, knowledge in these fields is attained during the student’s undergraduate studies. At the graduate studies level, prerequisite courses and advanced subjects in these fields will be offered, as well as courses in individual faculty members’ research fields. In many cases, these subjects constitute a basis for the student’s research study or project.

Program Duration and Format

The Industrial Engineering and Management master’s programs are based on full-time academic studies and research.  In order to enable full-time studies, the Technion offers a scholarship for a 24-month period as well as dormitory accommodation.  The basic scholarship includes living expenses and covers ¾ of the tuition.  Outstanding students will be offered the option of continuing for a doctorate.

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