Scott Ferguson

Associate Professor

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Dr. Ferguson’s long-term goal is to improve system design by exploring how customer needs and preferences impact engineering design decisions. We do this by advancing the state-of-the-art in engineering design theory  and design automation by creating tools and methodologies that help engineers navigate the interdisciplinary challenges associated with designing consumer products and complex systems.

Dr. Ferguson’s research addresses the science of engineering design and is motivated by the challenge that engineers must constantly balance tradeoffs. These tradeoffs result from the organizational, political and human interactions that serve to define the criteria under which the system operates. For any engineering problem, even the most basic decisions require making tradeoffs to maximize the value of the design. Fundamental questions driving this work include:

  1. What is the right mix of products to offer because of variety in customer taste?
  2. What drives customer purchasing / adoption decisions?
  3. What is the relationship between system configuration/architecture and needs and preferences that change over time?
  4. What information is needed to make effective design decisions when considering a market systems context?

Dr. Ferguson and his team draw upon research in design theory, multiobjective / multidisciplinary optimization, customer preference modeling, and complex systems. Currently, the lab pursues five primary research directions:

  1. Designing complex engineered systems capable of reconfigurability, evolvability and resilience
  2. Demand modeling, product platforming, and mass customization
  3. Design of engineered materials
  4. Product sustainability
  5. Improving engineering design education

To learn more about this work, please visit his lab website: System Design Optimization Laboratory.

Dr. Ferguson arrived at NC State in the Fall of 2008 and has taught undergraduate courses in Dynamics (MAE 208), Introduction to Aerospace Engineering (MAE 250), Aerospace Vehicle Performance (MAE 251), Introduction to Space Flight (MAE 453) and Fundamentals of Product Design (MAE 426). He has also created graduate-level classes in Engineering Design Optimization (MAE 531) and the Fundamentals of Product Design is also offered at the graduate level (MAE 526).



Ph.D. 2008

Mechanical Engineering

University at Buffalo, State University of New York

M.S. 2004

Mechanical Engineering

University at Buffalo, State University of New York

B.S. 2002

Aerospace Engineering

University at Buffalo, State University of New York

B.S. 2002

Mechanical Engineering

University at Buffalo, State University of New York

Research Description

Dr. Ferguson’s research in the area of engineering design focuses on market-based product design and the design of complex engineered systems. His contributions toward technical feasibility modeling and product line optimization have been adopted by his industrial collaborators and have received interest from market research software companies in this area. Dr. Ferguson’s research has also helped define the area of reconfigurable system design, advanced understanding of how such configuration changes can mitigate unexpected system behavior, and studied how the information presented to designers can facilitate tradeoff decisions in the presence of multiple objectives.

Honors and Awards

  • ASEE New Mechanical Engineering Educator Award, 2015
  • ASME Design Automation Young Investigator Award, 2014
  • NC State Outstanding Teacher Award, 2012
  • National Science Foundation CAREER Award, 2011


Design for excess capability to handle uncertain product requirements in a developing world setting
Allen, J. D., Mattson, C. A., Thacker, K. S., & Ferguson, S. M. (2017), Research in Engineering Design, 28(4), 511–527.
Exploring architecture selection and system evolvability
White, S., & Ferguson, S. (2017), In Proceedings of the asme international design engineering technical conferences and computers and information in engineering conference, 2017, vol 2b.
Exploring how optimal composite design is influenced by model fidelity and multiple objectives
Joglekar, S., Von Hagel, K., Pankow, M., & Ferguson, S. (2017), Composite Structures, 160, 964–975.
A case study of evolvability and excess on the B-52 stratofortress and FA-18 hornet
Long, D., & Ferguson, S. (2017), In Proceedings of the asme international design engineering technical conferences and computers and information in engineering conference, 2017, vol 4.
Bubble tracking simulations of turbulent two-phase flows
Fang, J., & Bolotnov, I. A. (2016), In Proceedings of the asme fluids engineering division summer meeting, 2016, vol 1b.
Design optimization and analysis of a prescribed vibration system
Malinga, B., Ferguson, S. M., & Buckner, G. D. (2016), (pp. 353–360).
Evaluation of system evolvability based on usable excess
Allen, J. D., Mattson, C. A., & Ferguson, S. M. (2016), Journal of Mechanical Design (New York, N.Y. : 1990), 138(9).
Excess identification and mapping in engineered systems
Cansler, E. Z., White, S. B., Ferguson, S. M., & Mattson, C. A. (2016), Journal of Mechanical Design (New York, N.Y. : 1990), 138(8).
Exploring the relationship between excess and system evolutions using a stress-test
Cansler, E. Z., Ferguson, S. M., & Mattson, C. A. (2016),
Modeling noncompensatory choices with a compensatory model for a product design search
Shin, J., & Ferguson, S. (2016),

View all publications via NC State Libraries

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Algorithm optimization and tuning for Under Armour
Under Armour(11/15/18 - 5/14/19)
UAS Roadmap
NC Department of Transportation(8/01/17 - 7/31/19)
Powering Energy Efficiency & Impacts Framework: Mapping a comprehensive energy strategy for the Upper Coastal Plain Council of Governments Region
US Dept. of Energy (DOE) - Energy Efficiency & Renewable Energy (EERE)(10/01/16 - 12/31/18)
Workshop: NSF CAREER Writing Workshop for Early Career Professionals; Charlotte, NC; August 23, 2016
National Science Foundation (NSF)(8/01/16 - 7/31/17)
CAD Apps for Core Courses in AE and ME Curricula: Bridge Funding 
The MathWorks, Inc.(1/01/16 - 5/31/17)
Building a Business Case for UAS Use in Public Power Operations
American Public Power Association(12/16/14 - 11/30/16)
Transfer Spike Analysis and Redesign
Neogen(12/02/13 - 3/31/14)
Collaborative Research: Mitigating Emergent System Behavior through System Evolvability
National Science Foundation (NSF)(6/01/13 - 5/31/17)
Transforming Teaching Through Implementing Inquiry (T2I2)
National Science Foundation (NSF)(11/30/-1 - 7/31/16)
Enabling All-Access Mobility for Planetary Exploration Vehicles via Transformative Reconfiguration
National Aeronautics & Space Administration (NASA)(11/30/-1 - 10/31/12)