Department Head: Emily Liu
Director, Doctoral Program: Jennifer Pazour
Director, Master’s Program: Esra Agca Aktunc
Director, Undergraduate Program: Rostyslav (Rosty) Korolov
Department Home Page: http://www.ise.rpi.edu/
The Department of Industrial and Systems Engineering offers degree programs at the bachelor’s, master’s, and doctoral levels including the bachelor’s and master’s degrees in Industrial and Management Engineering, and the doctoral degree in Decision Sciences and Engineering Systems. The common theme throughout the department’s academic programs is the use of mathematical, statistical, and computational/simulation models to better understand, predict, and optimize complex engineering, managerial, operational, and physical systems.
Research Innovations and Initiatives
The department’s research is focused on the application of mathematical, computational, statistical, and information and data science methods to model, analyze, and solve complex decision problems in engineering, management, and social systems. It is distinct from management and economics in the use of an engineering approach to design and analyze enterprise processes to optimize performance. It is distinct from computer science in its focus on the design of data and knowledge systems as the organizational nerve center where operations and enterprise systems are integrated.
The department’s faculty research aligns directly with these core strengths to exploit opportunities of high societal relevance in such areas as Adaptive Supply Chains, Social and Cognitive Networks, Homeland Security, and Community Resilience.
Liu, E. —Ph.D. (Massachusetts Institute of Technology); energy materials and systems, condensed matter physics, emergency communication, preparedness, and response, engineering education.
Pazour, J.—Ph.D. (University of Arkansas); decision analysis, operations research, military logistics, distribution and transportation systems, health-care logistics, peer-to-peer resource sharing systems.
Bailey, J.—Ph.D. (Georgia Institute of Technology); operations research, online optimization, algorithmic game theory, multiagent systems, machine learning, combinatorial optimization, social choice.
Cavdar, B.—Ph.D. (Georgia Institute of Technology); logistics and supply chain management, behavioral models in operations management.
Moran, D.—Ph.D. (Georgia Institute of Technology); theory and applications of mixed-integer linear and non-linear programming, applications of optimization to production planning, logistics and other relevant real-world business and engineering problems.
Wang, Y.—Ph.D. (Virginia Polytechnic Institute); engineering-driven machine learning for modeling, prediction, uncertainty quantification for complex physical systems.
Agca Aktunc, E.—Ph.D. (Virginia Polytechnic Institute and State University); mathematical programming, combinatorial optimization, humanitarian logistics, transportation, healthcare operations management.
Ahmadi, N.—Ph.D. (Western New England University); development of training interventions, behavior and performance evaluation using eye-tracking and wearable technologies, usability assessments and UX designs.
Hirsa, A.—Ph.D. (Rensselaer Polytechnic Institute); engineering and emerging technology ethics, ethics of modeling, management of engineering and technology, professional development, organizational behavior, cultural analysis and ethnography.
Korolov, R.—Ph.D. (Rensselaer Polytechnic Institute); social media analytics, social network analysis, data science, network science, human behavior modeling.
Senior Research Scientist
Grabowski, M.—Ph.D. (Rensselaer Polytechnic Institute); management information systems, knowledge-based systems, human and organizational error in large-scale systems, impact of information technology on systems and organizations.
Mendonca, D.—Ph.D. (Rensselaer Polytechnic Institute); human factors, cognitive engineering, decision support systems, applications in emergency response and critical infrastructure management.
Schell, K.—Ph.D. (Carnegie Mellon University); large scale optimization, applied statistics and machine learning, power system modeling, renewable energy forecasting, electricity markets, energy policy, decision theory, risk analysis.
Berg, D.—NAE, Ph.D. (Yale University); Institute Professor of Science and Technology (joint in Lally School of Management and Information Technology); management of technological organizations, innovation, policy, robotics, policy issues of research and development in the service sector.
Embrechts, M.J.—Ph.D. (Virginia Polytechnic Institute); application of neural networks and fuzzy logic for manufacturing and process control; image recognition and classification with the aid of neural networks; neural networks, fractals, chaos, and wavelets for time-series analysis; data mining and computational intelligence.
Graves, R.J.—Ph.D. (State University of New York at Buffalo); manufacturing systems modeling and analysis, facilities planning and material handling system design, scheduling systems, concurrent engineering and design for manufacture, continuous flow manufacturing systems design, distributed manufacturing concepts, information infrastructure.
Hsu, C.—Ph.D. (Ohio State University); electronic commerce, metadatabase and information systems, enterprise integration and modeling, Internet enterprises planning, computerized manufacturing, information visualization, economic evaluation of cyberspace-augmented enterprises.
Malmborg, C.J.—Ph.D. (Georgia Institute of Technology); modeling and analysis of problems in facility design, materials handling, material flow, storage systems, simulation-based optimization methods, manufacturing systems, decision analysis.
Raghavachari, M.—Ph.D. (University of California at Berkeley); statistical inference, quality control, multivariate methods, scheduling problems.
Sullo, P.—Ph.D. (Florida State University); reliability, life testing, statistical quality control, quality management, biostatistics, industrial statistics.
Tien, J.—NAE, Ph.D. (Massachusetts Institute of Technology); systems modeling, queuing theory, public policy and decision analysis, computer performance evaluation, and information and decision support systems, expert systems, computational cybernetics.
Wallace, W.A.—Ph.D. (Rensselaer Polytechnic Institute); decision support systems, environmental management, community resilience, disaster management, ethics in modeling.Wilkinson, J.—Ph.D. (University of North Carolina); regression modeling, statistical analysis.
Willemain, T.R.—Ph.D. (Massachusetts Institute of Technology); probabilistic modeling, data analysis, forecasting.
* Departmental faculty listings are accurate as of the date generated for inclusion in this catalog. For the most up-to-date listing of faculty positions, including end-of-year promotions, please refer to the Faculty Roster section of this catalog, which is current as of the May 2023 Board of Trustees meeting.
Objectives of the Undergraduate Curriculum
The Industrial and Management Engineering program is designed to prepare students for continued learning and successful careers in industry, government, academia, and consulting.
Within a few years of graduation, graduates of the Bachelor of Science program demonstrate the following PEO accomplishments:
- Be in professional positions in industry and/or graduate study programs in their areas of interest.
- Contributed to the body of knowledge in their professional discipline through problem-solving, discovery, leadership, and responsible application of technology.
- Developed both professionally and personally through activities such as participation in professional societies, continuing education, and community service.
The Industrial and Management Engineering degree program is accredited by the Engineering Accreditation Commission of ABET, http://www.abet.org.
Outcomes of the Undergraduate Curriculum
Students who successfully complete this program will be able to demonstrate:
- an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
- an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
- an ability to communicate effectively with a range of audiences.
- an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts.
- an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.
- an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
- an ability to acquire and apply new knowledge as needed, using appropriate learning strategies.
The ISE department offers an undergraduate curriculum in Industrial and Management Engineering (IME). The first two years of this curriculum provide a strong foundation in basic science, engineering science, mathematics, and the humanities, arts, and social sciences. These two years are oriented toward the quantitative (mathematical) approach. Computer-based technology, including simulation, computational modeling, and systems design, is emphasized. In the last two years of the program, students concentrate on building expertise in data science, management, and engineering, including statistics and operations research, operations and supply chain management, and industrial engineering methods and models. Through the appropriate choice of electives, students can focus on their selected areas of interest. Design projects include problems in robotics, manufacturing, services, and public systems. It is advisable to develop a Plan of Study leading to the desired degree and concentration by the beginning of the third year. The department recommends that students declare their intent to major in Industrial and Management Engineering as early as possible in their academic career. Students are also urged to work closely with their assigned faculty advisers to ensure that all degree requirements are satisfied.
This curriculum requires a minimum of 128 credit hours and completion of the course requirements shown in the typical four-year program presented in the Programs section of this catalog.
Special Undergraduate Opportunities
Cooperative Education Program
The department encourages this option, which allows students to gain professional experience as part of the educational program. Additional information on co-op opportunities is included in the Educational Programs and Resources section of this catalog, as well as through the faculty adviser or the Center for Career and Professional Development.
Study abroad and other international experiences have become an integral part of a well-rounded undergraduate experience. A period abroad allows students to develop a broader perspective on their chosen academic field of study while earning credit towards a Rensselaer degree, or to gain valuable practical and intercultural experience. Students gain a deeper understanding not only of the culture in which they will be living, but also the culture of the U.S. and its place in today’s global society.
Green Belt Certification
The Student Chapter of IISE, in conjunction with the Institute of Industrial and Systems Engineering, offers certificate programs in Lean Green Belt and Six Sigma Green Belt, which provide students with a great advantage in their job search. These courses are offered on campus on a selected weekend. Please check with the IISE Student Chapter for more details.
Lean Manufacturing Certificate for Undergraduates
IME students can earn this by satisfying the following requirements:
• Complete the following 4 courses with at least a “B” grade.
• Complete at least 3 months of internship, or co-op, or Arch semester away in a manufacturing company.
The Industrial and Systems Engineering Department offers the Master of Science and Master of Engineering degrees in Industrial and Management Engineering. Both degrees require 30 credit hours. The Master of Science degree requires a thesis. The Master of Engineering degree is a non-thesis option. The Industrial and Systems Engineering Department and the Lally School of Management also jointly offer a unique Master of Engineering program in Systems Engineering and Technology Management (SETM). This non-thesis degree requires 30 credit hours of coursework which may include a project. The Graduate Record Exam (GRE) is optional for both master’s programs.
The Industrial and Systems Engineering Department offers the Ph.D. in Decision Sciences and Engineering Systems. The Graduate Record Exam (GRE) is optional for the applicants to the Ph.D. program. A total of 48 credit hours are required for students entering with an approved master’s degree, while a total of 72 credits are required for those entering with an approved bachelor’s degree. Further requirements are found under the Ph.D. in Decision Sciences and Engineering program information.
Outcomes of the Graduate Curriculum
Students who successfully complete this program will be able to demonstrate:
- competency in area of specialization.
- ability to lead or support development of proposals for external funding.
- ability to lead or support delivery of conference and/or journal papers to publication.
- ability to support the delivery of the department’s educational program.
- ability to present work in public forum.
Courses directly related to all Industrial and Systems Engineering curricula are described in the Course Description section of this catalog under the department code ISYE.