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Detailed Information

Programs of Study

The formation of this Department in 1987 is a prime example of Rensselaer’s ability to anticipate the changing needs of the engineering profession. The Department was created to prepare engineers to design, develop, and implement complex decision-making systems and to conduct research that leads to better understanding of how information technology and quantitative analysis and modeling can support individuals, groups, and systems in problem solving and decision making. These objectives are achieved by extending and integrating knowledge from the traditional disciplines of industrial engineering, information systems, operations research, engineering statistics, computational intelligence, and systems engineering. The Department offers graduate degree programs at the master’s and doctoral levels, including a master’s degree in industrial and management engineering, a master’s degree in systems engineering and technology management, and the doctoral degree in decision sciences and engineering systems. A common theme throughout these programs is the use of mathematical, statistical, and computational/simulation models to better understand engineering, managerial, operational, and physical processes. All of the academic programs in the Department build on the intellectual foundations of information engineering, operations engineering, and enterprise engineering.

Information engineering involves the application of information science, computer science, and mathematics in system design and analysis as it relates to the creation, fusion, processing, management, and deployment of data, information, and knowledge. It employs results from data and knowledge engineering, computational statistics, and information systems to design and provide information infrastructure to support enterprise operations. In contrast to computer science and other related disciplines, information engineering focuses on the design of data and knowledge systems as the organizational nerve center where operations and enterprise systems are integrated. The methodological foundations of information engineering are rooted in soft computing, database systems, and forecasting. Emerging areas of research include the fusion, analysis, and management of real-time data streams from large-scale distributed sources; the design and administration of cyber-infrastructure for digital enterprises; and open-connection technology such as Web services, service-oriented architecture, and ontology. Popular application areas encompass the science of collaboration, intelligent transportation, and manufacturing and service systems.

Operations engineering involves the application of mathematical, scientific, and computational methods to decision problems in engineering design and the modeling and analysis of technical, business, social, and physical systems. It employs methods of mathematical programming, queuing theory, computational optimization, agent-based modeling, engineering statistics, and discrete-event simulation for solving problems related to the design, planning, and operation of complex systems where intelligent coordination is necessary to achieve optimal performance.

Enterprise engineering involves the application and development of management science and engineering principles to the design and control of enterprises. It employs results from information systems, management, organization theory, and microeconomics to design, rationalize, and control large-scale enterprise systems. Operations and enterprise engineering are distinctive from management and economics in the use of an engineering approach to design and plan enterprise processes to optimize performance. Enterprise engineering is distinguished from operations engineering based on its methodological foundations in strategy and policy, entrepreneurship, organization design, production functions, and social networks.

The Department’s faculty research aligns directly with these three core strengths. The primary research theme is adaptive supply chains, with other applications-oriented research initiatives in homeland security, intelligent transportation systems, energy and the environment, services engineering, and biotechnology.

The Department’s research in adaptive supply chains deals with the logistics of efficiently deploying finite resources to assemble, transport, sustain, and distribute people and goods, thereby facilitating the fulfillment of demand associated with economic commerce, national defense, disaster response, and/or humanitarian aid. The focus is on efficient and integrated coupling of supply with distribution network resources from a total integrated systems perspective. The functional scope of adaptive supply chains spans production/procurement, materials management, storage, transport, routing, warehousing, dispatching, delivery, and service. Its contextual scope spans production, transportation, military, health, maritime, and communications systems. All of these systems are characterized by complex interdependencies where methodologies of information, operations, and enterprise engineering can address major challenges in both the ability of supply chains to adapt to evolutionary change and to respond to planned and unplanned disruptive events.

Research Facilities

Research is supported by state-of-the-art facilities and equipment including the Rensselaer Libraries, whose electronic information system provides access to collections, databases, and the Internet from campus and remote terminals; the Rensselaer Computing System, which permeates the campus with a coherent array of more than 7,000 nodes of distributed laptops, desktops, advanced workstations, and servers; a shared toolkit of applications for interactive learning and research and high-speed Internet connectivity; one of the country’s largest academically based, class 100 clean room facilities; high-performance campuswide computing facilities that allow for serial or parallel computation; and five core laboratories for molecular biology, proteomics, bio-imaging, and tissue engineering.

Rensselaer’s research capabilities have been enhanced with the addition of the Computational Center for Nanotechnology Innovations (CCNI). The result of a $100-million collaboration with IBM and New York State, the CCNI is the world’s most powerful university-based supercomputing center and a top ten supercomputing center of any kind in the world. The CCNI is made up of massively parallel Blue Gene supercomputers, POWER-based Linux clusters, and Opteron-based clusters, providing more than 100 teraflops of computational muscle and approximately a petabyte of shared online storage.

Other facilities and research centers include the Center for Biotechnology and Interdisciplinary Studies; the George M. Low Center for Industrial Innovation; research centers for integrated electronics, terahertz science, nanotechnology, fuel cell and hydrogen research, lighting research, science and technology policy, and infrastructure and transportation studies; the Geotechnical Centrifuge Research Center; the Darrin Fresh Water Institute; and the Scientific Computation Research Center.

In addition, academic departments and faculty laboratories have extensive discipline-specific research capabilities and equipment.

Financial Aid

Financial aid is available in the forms of teaching and research assistantships and fellowships, which include tuition scholarships and stipends. Rensselaer assistantships cover the academic year, with summer support available in many departments. University, corporate, or national fellowships fund many of Rensselaer’s full-time graduate students. Outstanding students may qualify for university-sponsored Rensselaer Graduate Fellowship Awards, which carry a minimum stipend of $22,000 and a full tuition and fees scholarship. All fellowship awards are calendar-year awards for full-time graduate students. Low-interest, deferred-repayment graduate loans are available to U.S. citizens with demonstrated need.

Cost of Study

Full-time graduate tuition for the 2008–09 academic year is $36,950. Other costs (estimated living expenses, insurance, etc.) are projected to be about $13,680. Therefore, the cost of attendance for full-time graduate study is approximately $50,630. Part-time study and cohort programs are priced differently. Students should contact Rensselaer for specific cost information related to the program they wish to study.

Living and Housing Costs

Graduate students at Rensselaer may choose from a variety of housing options. On campus, students can select one of the many residence halls and immerse themselves in campus life or choose from a select number of apartments designed for graduate students only. There are abundant, affordable options off campus as well, many within easy walking distance.

Student Group

Of the 1,176 graduate students, 29 percent are women, and 92 percent are full-time, with 75 percent of full-time graduate students studying at the doctoral level.

Student Outcomes

Rensselaer’s graduate students are hired in a variety of industries and sectors of the economy and by private and public organizations, the government, and institutions of higher education. Their starting salaries average $74,807 for master’s degree recipients and $82,750 for Ph.D. recipients.

Location

Located just 10 miles northeast of Albany, New York State’s capital city, Rensselaer’s historic 275-acre campus sits on a hill overlooking the city of Troy, New York, and the Hudson River. The area offers a relaxed lifestyle with many cultural and recreational opportunities, with easy access to both the high-energy metropolitan centers of the Northeast–such as Boston, New York City, and Montreal, Canada–and the quiet beauty of the neighboring Adirondack mountains.

The Institute

Recognized as a leader in interactive learning and interdisciplinary research, Rensselaer continues a tradition of excellence and technological innovation dating back to 1824. Rensselaer has five schools–Architecture, Engineering, Management, Science, and Humanities and Social Sciences–that offer more than 100 graduate programs in over 48 disciplines that attract top students, researchers, and professors. The discovery of new scientific concepts and technologies, especially in emerging interdisciplinary fields, is the lifeblood of Rensselaer’s culture and a core goal for the faculty, staff, and students. Fueled by significant support from government, industry, and private donors, Rensselaer provides a world-class education in an environment tailored to the individual.

Applying

The admission deadline for the fall semester is January 1 for candidates seeking financial aid. Basic admission requirements are the submission of a completed application form (available online), the required application fee ($75), a statement of background and goals, official transcripts, official scores on the GRE General Test, TOEFL or IELTS scores (if applicable), and two recommendations.

The Faculty and Their Research

• Mohamed H. Aboul-Seoud, Clinical Assistant Professor; Ph.D. (reliability engineering, quality control, operations research), Louisville. Reliability engineering, quality assurance, fuzzy logic, operations research, facilities planning and design, simulation, engineering economics. (aboulm@rpi.edu)
• Wai Kin (Victor) Chan, Assistant Professor; Ph.D. (industrial engineering and operations research), Berkeley. Discrete-event simulation, sensitivity analysis, stochastic orders, queueing networks with blocking, resampling nonhomogeneous stochastic processes, mathematical programming, semiconductor manufacturing, biomanufacturing. (chanw@rpi.edu)
• Mark J. Embrechts, Associate Professor; Ph.D. (nuclear engineering), Virginia Tech. Application of neutral networks and fuzzy logic for manufacturing and process control; image recognition and classification with the aid of neural networks; smart experiments; neural networks for trading and finance; neural networks, fractals, chaos, and wavelets for time-series analysis; data mining, computational intelligence. (embrem@rpi.edu)
• William J. Foley, Clinical Associate Professor; Ph.D. (operations research and statistics), Rensselaer. Application of research tools such as statistical analysis and operations research models to policy and planning problems in health-care delivery and health organizations. (foleyw@rpi.edu)
• Martha Grabowski, Research Professor; Ph.D. (management/information systems, expert systems), Rensselaer. Impact of technology in safety-critical systems, risk analysis and risk mitigation in large-scale systems, role of human and organizational error in high-consequence settings. (grabowsk@lemoyne.edu)
• Jose Holguin-Veras, Professor; Ph.D. (transportation), Texas at Austin. Integration of transportation economics principles into transportation modeling, use of large-scale optimization techniques to model equilibrium of markets and transportation networks, use of information technology and information systems to support model building and enhance decision making. (jhv@rpi.edu)
• Cheng K. Hsu, Professor; Ph.D. (management sciences), Ohio State. Development of information technology to solve enterprise engineering problems, enterprise integration and collaboration, e-business and IT-enabled manufacturing enterprises, information visualization, data and knowledge systems methodologies. (hsuc@rpi.edu)
• Charles J. Malmborg, Professor and Department Head; Ph.D. (industrial and systems engineering), Georgia Tech. Conceptualization models for the design and planning of automated storage and retrieval systems, design optimization tools for autonomous vehicle storage and retrieval systems, multiattribute decision models for facility layout and design, multimedia instructional tools for integration of material handling analysis, technology and design. (malmbc@rpi.edu)
• John E. Mitchell, Professor; Ph.D. (operations research), Cornell. Optimization and mathematical programming: integer programming, nonlinear programming, interior point methods, semidefinite programming, portfolio optimization, stochastic programming. (mitchj@rpi.edu)
• Jennifer Ryan, Assistant Professor; Ph.D. Northwestern. Bayesian methods for decision support systems, stochastic optimization methods for logistical systems, stochastic models for inventory control and supply chain management, analysis of make-to-stock production inventory systems, service parts logistics, decision models for large-scale condition monitoring.
• Thomas Sharkey, Ph.D., Florida. Mathematical programming, network algorithms, combinatorial and computational optimization, supply chain logistics, demand allocation based supply chain optimization models, nonlinear network design problems.
• Satish V Ukkusuri, Assistant Professor; Ph.D. (transportation systems, civil engineering), Texas at Austin. Modeling uncertainty in transportation networks, simulations of large-scale robust transportation networks, online network equilibrium problems, information and sensor technologies for transportation applications, intermodal system operations, infrastructure security and network evacuation. (ukkuss@rpi.edu)
• William A. Wallace, Professor; Ph.D., Rensselaer. Analytical approaches to emergency management: development of models for disaster management, including transportation of hazardous materials, development of decision logic for crisis management; process of modeling: the acquiring of an expert’s judgment and experience and its subsequent codification in a form amenable to representation by a complex model. (wallaw@rpi.edu)
• Thomas R. Willemain, Professor; Ph.D. (electrical engineering), MIT. Probabilistic modeling, data analysis, forecasting. (willet@rpi.edu)
• Major Research Centers
• Center for Automation Technologies and Systems (CATS): The CATS provides a means for industry to utilize an extensive pool of knowledge and expertise at RPI in the science and technology of automation. Students and more than 30 faculty members in ten departments participate in the research and educational programs of the center. With annual funding from New York State, the CATS focuses on applying core technologies to a broad range of applications. The traditional engineering of automated systems is frequently addressed by conservative over-design or by experience-based trial and error. However, the steady advances in computational power and miniaturized sensors and actuators make feasible new strategies: the broad application of an integrated systems approach, which promises higher performance, efficiency, robustness, and reliability. The CATS works with industrial partners to pursue such strategies, advancing model-based methods and applying them to design, optimization, control, and monitoring for challenging and high-impact real-world problems.
• Center for Infrastructure and Transportation Studies (CITS): CITS was established in 1993 to create a collaborative environment for multidisciplinary research focused on the systems that make societal activity possible within the built environment. Such systems are the backbone of civilization, and to keep pace with the information age in a sustainable world, they must evolve rapidly in all aspects of their planning, design, operation, maintenance, and metamorphosis. Pushing this frontier within CITS are faculty members and students from many different disciplines. Their interests range from civil engineering to management and include decision sciences; electrical, chemical, mechanical, and materials engineering; information technology; architecture; cognitive science; computer science; and economics. Current research is focused on advanced materials and their application; intelligent transportation systems; the use of simulation for system analysis, design, and operations planning; and the development of new decision-making paradigms and decision-support systems. Both real and virtual laboratories make possible this scientific advancement. Of particular note are the real-world testbeds made accessible by partnerships with the U.S. Department of Transportation, the New York State Department of Transportation, the U.S. Army Corps of Engineers, and the cities of White Plains and Troy, New York. Other major research partners include the New York State Energy Research and Development Authority, Sandia National Laboratories, and the New York State Thruway Authority.
• Center for Integrated Electronics, Electronics Manufacturing and Electronic Media (CIEEM): The Center for Integrated Electronics, Electronics Manufacturing and Electronic Media (CIEEM) was created to carry out industry-oriented research development in semiconductor (electrical) devices and circuits, their design and manufacturing, on-chip interconnect, and the development and utilization of electronic media. The center’s activities, funded by government and industry, range from basic and applied research and education to commercialization through partnerships with industry. A complement of about 50 faculty members, 100 students, and 15 full-time research staff members conduct research activities in fundamental areas of materials processes, semiconductor devices, design, fabrication, packaging, and characterization related to integrated electronics, electronics manufacturing, and electronic media. These projects serve to develop new technologies and real solutions to industrial problems. State-of-the-art facilities include a class 100 microfabrication clean room with processing capabilities for both Si and III-V base devices/circuits; extensive computer resources from such companies as Apple, AT&T, Digital, Hewlett Packard, IBM, and Sun; and numerous state-of-the-art processing design and characterization facilities in individual laboratories.
• The Flexible Manufacturing Center is part of the CATS. The Flexible Manufacturing Center’s associates have conducted research in a variety of areas related to manufacturing process development and automation, energy-efficient processes, and the environment. Some projects are very short in duration, such as the initial consultations made in partnership with NASA’s SATOP program; however, other projects, such as the center’s work in advanced fuel-cell manufacturing process development, are ongoing.
• Scientific Computation Research Center (SCOREC): The Scientific Computation Research Center is focused on the development of reliable simulation technologies for engineers, scientists, medical professionals, and other practitioners. These advancements enable experts in their fields to employ, appraise, and evaluate the behavior of physical, chemical, and biological systems of interest. SCOREC research focuses on high-performance computing strategies to improve understanding of physical phenomena, provide new modeling and simulation techniques, and support computational experimentation. Current projects include automated adaptive techniques for solving PDEs, parallel computation techniques, and procedures for critical applications. Computing facilities include a state-of-the-art IBM SP2 parallel computer and advanced workstations from Apple, IBM, Silicon Graphics, and Sun.

Correspondence and Information

Rensselaer Polytechnic Institute
Department of Decision Sciences and Engineering Systems
Center for Industrial Innovation, Room 5015
110 8th Street
Troy, New York 12180-3590
Telephone: 518-276-2773
Fax: 518-276-4030
Email: dses@rpi.edu