Keegan J. Moore
Dr. Keegan J. Moore is an Associate Professor in the Daniel Guggenheim School of Aerospace Engineering and the Director of the Moore Dynamics and Analytics Laboratory (MoDAL) at Georgia Tech. The vision of his research group is to place nonlinear dynamics into the toolbox of every engineer. To achieve this, the lab weaves together theory, simulation, and experimentation with modern data science and autonomy to make complex systems easier to understand and control.
Dr. Moore's lab pioneers next-generation, data-driven methods for the analysis and design of nonlinear aerospace structures. This foundational work includes discovering governing equations directly from experimental data, developing AI-based frameworks for autonomous testing and model reconciliation within the Digital Engineering paradigm, and creating advanced reduced-order models for efficient simulation. These methods are then used to investigate fundamental phenomena, such as energy guiding and non-reciprocity in acoustic metamaterials, and to engineer novel vibration mitigation strategies using nonlinear absorbers. Ultimately, this research tackles critical challenges across multiple domains: from ensuring the structural integrity of bolted joints and predicting the response of structures to extreme loading like shocks and impacts, to controlling the aeroelastic performance of high-aspect-ratio wings and vertical-lift vehicles.
Recognized for his contributions, Dr. Moore is the recipient of the 2023 National Science Foundation (NSF) CAREER Award and the 2022 Air Force Office of Scientific Research (AFOSR) Young Investigator Program Award. Before his appointment at Georgia Tech, he was an Assistant Professor of Mechanical and Materials Engineering at the University of Nebraska-Lincoln from 2018 to 2024. He received his B.Sc. in Mechanical Engineering from the University of Akron in 2014 and his Ph.D. in Mechanical Engineering from the University of Illinois at Urbana-Champaign in 2018, where he was a recipient of the prestigious NSF Graduate Research Fellowship.
Professor Moore is dedicated to transforming the engineering classroom through evidence-based active learning and collaborative gamification. His educational philosophy centers on "learning from failure" and fostering deep conceptual intuition over pure memorization. In his undergraduate courses, such as Dynamics (AE 2220) and System Dynamics & Vibrations (AE 3530), he replaces traditional passive lectures with team-based worksheets that guide students through complex derivations and problem-solving strategies in real-time.
A key component of his teaching is the integration of immersive technology. Supported by his NSF CAREER Award, Professor Moore is developing a Virtual Reality Dynamics Laboratory utilizing platforms like WebXR and Unity. This initiative allows students to visualize and manipulate abstract dynamical concepts—such as harmonic oscillators and particle kinematics—in a familiar, interactive environment.
Beyond the mechanics of dynamics, Professor Moore emphasizes collaborative engineering. He has used role-based gamification and iterative assignment structures to encourage teamwork and reduce the anxiety often associated with difficult engineering subjects. His teaching interests extend to Data-Driven Nonlinear Dynamics and Vibrations, drawing on his extensive course development experience to equip students with the theoretical and computational tools necessary for modern aerospace analysis.
Professor Moore directs the Moore Dynamics and Analytics Laboratory (MoDAL), where he combines theory, computational modeling, and autonomous experimentation to exploit strongly nonlinear dynamical phenomena. His research vision is to place nonlinear dynamics in the toolbox of every engineer, addressing the estimated $1 trillion annual industrial loss caused by structural failures and suboptimal designs that arise from ignoring nonlinearity.
His group’s work is defined by four primary thrusts:
• Digital Engineering & Autonomy: Developing synchronous, feedback-driven frameworks that allow digital models and physical experiments to "talk" to one another, enabling autonomous model updating and self-optimizing test designs (supported by the AFOSR).
• Tribomechadynamics: Investigating the "evolution of nonlinearities" over a structure’s lifetime, specifically how dynamics drive the loosening of bolted joints and damage progression (supported by an NSF CAREER Award).
• Physics-Informed System ID: Creating "white-box" machine learning algorithms that reverse-derive interpretable governing equations of motion directly from noisy experimental data.
• Vibration Mitigation: Designing novel Two-Dimensional Nonlinear Vibration Absorbers (2D-NVA) to suppress multi-modal instabilities in next-generation aircraft with Ultra-High-Aspect-Ratio (UHAR) wings (sponsored by NASA).
AE Multidisciplinary Research Areas:
- Mechanics of Multifunctional Structures and Materials
- Large-Scale Computations, Data, & Analytics
- Vertical Lift and Urban Air Mobility
- Robotics, Autonomy and Human Interaction
- Cyberphysical Systems, Safety, Security, & Reliability
- Ph.D., University of Illinois at Urbana-Champaign, 2018;
- B.Sc., University of Akron, 2014.
- C. López, A. Singh, Á. Naranjo, K.J. Moore. “A Data-Driven, Energy-based Approach for Identifying Equations of Motion in Vibrating Structures Directly from Measurements,” Mechanical Systems and Signal Processing, Vol. 225, 112341, 2025.
- C. López, Á. Naranjo, D. Salazar, K.J. Moore. “Weak-form modified sparse identification of nonlinear dynamics,” Journal of Computational Physics, Vol. 521, 113539, 2025.
- C. López, K.J. Moore. “Energy-based dual-phase dynamics identification of clearance nonlinearities,” Nonlinear Dynamics, Vol. 113, 17933-17948, 2025.
- B.J. Chang, L.A. Bergman, K.J. Moore, W.A. Silva, A.F. Vakakis. “Nonlinear Modal Interaction Identification in KTH-NASA Generic Fighter in Supersonic Flow in Transonic Dynamics Tunnel,” AIAA Journal, 2024.
- J.D. Brown, M. Mustafa, K.J. Moore. “Vibration Mitigation of a Model Aircraft with High-Aspect-Ratio Wings Using Two-Dimensional Nonlinear Vibration Absorbers,” International Journal of Non-Linear Mechanics, Vol. 167, 104878, 2024.