Scott Ferguson
Associate Professor
- Phone: (919) 515-5231
- Email: smfergu2@ncsu.edu
- Office: Engineering Building III (EB3) 3244
- Website: https://sdoresearch.wordpress.ncsu.edu/
Research Overview
Dr. Ferguson leads the Systems, Decisions, and Objectives (SDO) Lab at NC State. The lab’s mission is to advance the science of engineered systems designed to adapt, evolve, and deliver long-term value within deeply uncertain environments.
As modern systems face unprecedented and unexpected disruptions in sectors such as national infrastructure, defense, aerospace, mobility, and healthcare, the SDO Lab addresses a critical guiding question: How should engineers architect today’s systems to meet immediate requirements while ensuring resilience against unpredictable future shifts?
Scientific Approach
Our work synthesizes systems architecting, decision science, and digital engineering to bridge the gap between computational intelligence and human judgment. By developing rigorous decision-making frameworks and digital tools, we empower engineers to manage complexity and make confident, explainable choices that balance immediate performance with long-term adaptability.
Research Areas
The SDO Lab’s research program is organized into four core areas:
- Designing systems for change: Enabling systems to evolve, adapt, and remain resilient over time
- Decision-making under deep uncertainty: Ensuring explainability, traceability, and transparency in AI-supported workflows
- Portfolio-level strategy: Framing small-world engineering problems to balance risk, value, and adaptability
- Educating the next generation: Training the next generation to tackle ill-structured, complex problems using systems thinking, computational intelligence, and critical reasoning
Collaboration & Impact
The SDO Lab actively collaborates with industry leaders, government agencies, and academic institutions to solve high-impact challenges at the intersection of complexity and long-term performance. Our goal is to provide the theoretical foundations and practical capabilities necessary to sustain critical functions in an increasingly uncertain world.
To learn more about this work, please visit his lab website: Systems, Decisions, and Objectives Lab.
Courses Taught
Dr. Ferguson has taught undergraduate courses in Dynamics (MAE 208), Introduction to Aerospace Engineering (MAE 250), Aerospace Vehicle Performance (MAE 251), ME Capstone Design (MAE 416), Fundamentals of Product Design (MAE 426), and Introduction to Space Flight (MAE 467).
He also teaches graduate sections of Fundamentals of Product Design (MAE 526) and Engineering Design Optimization (MAE 531).
Publications
- Bridging the Gap: Transferring Design Margins Into MBSE Practice for System Changeability Analysis
- Valverde, O., Jacobson, L., & Ferguson, S. (2025, August 17). , . https://doi.org/10.1115/detc2025-169180
- Narrative-Driven Decision-Making: Integrating Conviction Narrative Theory (CNT) Into Engineering Design Theory
- Ferguson, S., & Deering, L. R. (2025, August 17). , . https://doi.org/10.1115/detc2025-169048
- Pre-registering a case study: requirements and narrative alignment in teams
- Edwards, S. L., Summers, J., Deering, L. R., & Ferguson, S. (2025, August 1), Proceedings of the Design Society, Vol. 8. https://doi.org/10.1017/pds.2025.10276
- Repeated Measures Investigation of Self-Efficacy in Jonassen-Inspired Problem-Based Learning for Aerospace Engineering Students
- Ghoreyshi, S., Olewnik, A., & Ferguson, S. (2025, November 2). , (Vol. 11). Vol. 11. https://doi.org/10.1109/fie63693.2025.11328310
- Toward Explainable Engineering Decisions: Pursuing a Descriptive Decision Theory at the Intersection of Analysis, Judgment, and Conviction
- Ferguson, S., & Bryden, K. M. (2025, November 5), Systems Engineering. https://doi.org/10.1002/sys.70019
- Using the Delphi Method to Understand Convergent and Divergent Perspectives of PBL Experts and Engineering Faculty in Aerospace Engineering
- Olewnik, A., Schrewe, L., Ferguson, S., Olewnik, A., Schrewe, L., & Ferguson, S. (2025, December 16), Journal of Problem Based Learning in Higher Education. https://doi.org/10.54337/ojs.jpblhe.v13i1.10026
- ML-Based Analysis of In-Situ Backscatter Electron Detection for Quality Assurance During Additive Manufacturing
- Gbadamosi-Adeniyi, T., McDonald, T., Peverall, D., Amoako, E., Tassone, C., Ferguson, S., & Horn, T. (2024, April 23), 2024 JOINT INTERNATIONAL VACUUM ELECTRONICS CONFERENCE AND INTERNATIONAL VACUUM ELECTRON SOURCES CONFERENCE, IVEC + IVESC 2024. https://doi.org/10.1109/IVECIVESC60838.2024.10694970
- Managing and modelling margins in design as a means for confronting the challenges of a disruptive world
- Ferguson, S., Brahma, A., Eckert, C., & Isaksson, O. (2024, October 2), Journal of Engineering Design, Vol. 35, pp. 1185–1192. https://doi.org/10.1080/09544828.2024.2414130
- Deep Neural Networks in Natural Language Processing for Classifying Requirements by Origin and Functionality: An Application of BERT in System Requirements
- Mullis, J., Chen, C., Morkos, B., & Ferguson, S. (2023, October 12), Journal of Mechanical Design, Vol. 146. https://doi.org/10.1115/1.4063764
- Margins in design – review of related concepts and methods
- Brahma, A., Ferguson, S., Eckert, C., & Isaksson, O. (2023, June 20), Journal of Engineering Design, Vol. 6. https://doi.org/10.1080/09544828.2023.2225842