Using machine learning, Rutgers researchers develop a “probability map” from databases that combines whale monitoring and environmental data
Industrial and Systems Engineering Research
Research Areas of Focus
The Department of Industrial and Systems Engineering generates research in several areas with a focus on key areas of critical importance to national competitiveness and productivity including manufacturing, data science, energy systems, optimization and AI and robotics.
Our faculty members have achieved international recognition for their contributions to these areas.
Optimization and Data Science
Optimization and data science are fundamental in our department in both research and teaching with many of our faculty engaged in some aspects of distributed and stochastic optimization, machine learning, statistical inference, predictive and prescriptive analytics, forecasting, planning and decision making. The faculty work on the development of scientific methodology and computational algorithms with a focus in the cross sections of operations research and data science. There are strong links between these and other research areas in the department and faculty are engaged with applications in manufacturing and supply chain, security, energy and transportation.
Faculty
David W. Coit, Elsayed Elsayed, Ahmed Aziz Ezzat, Melike Baykal-Gürsoy, Weihong Guo, Myong K. Jeong, Tuğrul Özel, Hoang Pham, Farzad Yousefian
Advanced Manufacturing and Production
The department has always been active in many aspects of manufacturing and production systems field. The current research focus is in: manufacturing processes, micro machining, sheet folding, 3D printing, semiconductor manufacturing supply chain, process monitoring and control, physics-based learning and prognostics and diagnostics. The department and the School of Engineering are homes to several advanced laboratories in manufacturing.
The faculty are engaged in many interdisciplinary research projects, including:
- Advanced manufacturing
- Additive manufacturing
- Laser processing
- Physics-based process simulations
- Physics-informed learning
- Manufacturing data analytics
- Process monitoring
- Prognostics and diagnostics
Faculty
Melike Baykal-Gürsoy, Elsayed Elsayed, Weihong Guo, Myong K. Jeong, Tuğrul Özel
Quality and Reliability
The department is nationally and internationally known for its renowned faculty in the area of quality and reliability engineering. The research focuses on product and system reliability, resilience, accelerated life testing for infrastructure, medical and manufacturing applications. There is a strong cross link between these topics and data science. The department is home to an advanced laboratory in reliability engineering and accelerated life testing.
Faculty
David W. Coit, Elsayed Elsayed, Ahmed Aziz Ezzat, Hoang Pham
Energy Systems
This is a relatively new research area for the department, and is unique to many peer departments across the country. The faculty research and project funding cover:
- Renewables and distributed energy resources and grid integration
- Load and generation forecasting
- Predictive analytics for maintenance of energy assets, energy markets, planning and operations
- Offshore wind energy
- Electrification of transportation
The department is home to the state of art laboratory in energy and the faculty are actively engaged in many interdisciplinary works across the university and worldwide.
Faculty
David W. Coit, Ahmed Aziz Ezzat, Mohsen Jafari, Robert Mieth, Zhimin Xi
Automation and AI
Automation sciences has always been a strong research area in the department for over several decades. The faculty research has focused on autonomous systems, control and AI, robotics, digital twins and simulation, system integration and informatics, intelligent transportation, smart cities and buildings and more. In overall the department has a long track record in funded projects and published works in this topic.
Faculty
Melike Baykal-Gürsoy, Weihong Guo, Mohsen A. Jafari, Myong K. Jeong, Tuğrul Özel, Zhimin Xi, Farzad Yousefian
ISE Research News
Rutgers Engineering researchers are developing NextG-enabled manufacturing aimed at improving advanced manufacturing efficiencies.
Learn more about assistant professor Robert Mieth whose research focuses on operation and planning of renewable-dominant power and energy systems in the context of climate change.