Publications

Books

  • [1]
    Interactive Engineering Mathematics [In Preparation].
    By Huang, D. and Renganathan, A.
    Cognella, 2026
  • [2]
    Structural Dynamics.
    By Friedmann, P.P., Lesieutre, G.A. and Huang, D.
    Cambridge University Press, 2023

    • Preprints / Under Review

  • [1]
    Data-Enabled Predictive Control for Flexible Spacecraft.
    By Wang, H., Zhang, K., Vahidi-Moghaddam, A., An, H., Li, N., Huang, D. and Li, Z.
    2025.
  • [2]
    A Hamilton-Jacobi-Bellman Framework for Learning Physics-Informed Optimal Feedback Controllers.
    By Vargas Venegas, C.A., Singla, P., Huang, D. and Grant, M.
    2025.
  • [3]
    Physics-Infused Reduced-Order Modeling for Analysis of Multi-Layered Hypersonic Thermal Protection Systems.
    By Vargas Venegas, C.A., Huang, D., Blonigan, P. and Tencer, J.
    2025.
  • [4]
    Global Description of Flutter Dynamics via Koopman Theory.
    By Song, J. and Huang, D.
    2025.
  • [5]
    Compressible Shear Layer Dynamics of a Cone-Slice-Ramp in High-Speed Flows.
    By Sadagopan, A., Huang, D. and Pandey, A.
    2025.
  • [6]
    Residual Dynamic Mode Decomposition with Control for Nonlinear Aeroservoelasticity.
    By Rains, J., Huang, D. and Wang, Y.
    2025.
  • [7]
    Reduced-Order Modeling of Turbulent Flows for High-Speed Aerothermoelastic Analysis.
    By Kimmel, E., Huang, D., Sharma, V., Singh, J., Raman, V. and Friedmann, P.P.
    2025.
  • [8]
    Learning Networked Dynamical System Models with Weak Form and Graph Neural Networks.
    By Yu, Y., Huang, D., Park, S. and Pangborn, H.
    2024.
  • [9]
    PyPose v0.6: The Imperative Programming Interface for Robotics.
    By Zhan, Z., Li, X., Li, Q., He, H., Xiao, H., Xu, Y., Chen, X., Xu, K., Cao, K., Huang, D. and others.
    2023.

    • 2025

  • [1]
    Learning Coarse-Grained Dynamics on Graph.
    By Yu, Y., Harlim, J., Huang, D. and Li, Y.
    In Physica D: Nonlinear Phenomena, vol. 481, p. 134801, 2025.
  • [2]
    Learning Coarse-Grained Dynamics on Graphs.
    By Yu, Y., Harlim, J., Huang, D. and Li, Y.
    In SIAM CSE252025.
  • [3]
    Global Description of Flutter Dynamics via Koopman Theory.
    By Song, J. and Huang, D.
    In AIAA SciTech 2025 Forum2025.
  • [4]
    Modal Analysis of Spatiotemporal Data via Multivariate Gaussian Process Regression.
    By Song, J. and Huang, D.
    In AIAA Journal, vol. 63, no. 2, pp. 1–18, 2025.
  • [5]
    Multi-objective Optimization of Rotorcraft Blade Structure with Multi-disciplinary Constraints.
    By Song, J., Haehnel, R., Huang, D., Zhang, J. and Edward, S.
    In 81st Annual Vertical Flight Society (VFS) Forum and Technology Display2025.
  • [6]
    Towards Control Co-design of Morphing Aerial Autonomous Systems by Multi-objective Optimization.
    By Smith, P., Pudasaini, S. and Huang, D.
    In SIAM CSE252025.
  • [7]
    A Parametric Study for the Effect of Morphing on Aerial Vehicles in Obstacle Avoidance.
    By Smith, P. and Huang, D.
    In AIAA SciTech 2025 Forum2025.
  • [8]
    Aeroservoelastic Modeling for Trajectory Optimization of Morphing Aircrafts.
    By Pudasaini, S., Smith, P. and Huang, D.
    In ASME Aerospace Structures, Structural Dynamics, and Materials Conference (SSDM) 20252025.
  • [9]
    Turbulence and Upstream Shock Wave-Boundary Layer Interaction Effects on Compliant Structures.
    By Kimmel, E., Huang, D., Sharma, V., Singh, J., Raman, V. and Friedmann, P.P.
    In AIAA Journal, 2025.
  • [10]
    Reduced-Order Modeling of Resolved Turbulent Flows for High-Speed Fluid-Structure Interaction Analysis.
    By Kimmel, E., Huang, D., Sharma, V., Singh, J., Raman, V. and Friedmann, P.P.
    In AIAA SciTech 2025 Forum2025.
  • [11]
    Learning Vector Fields of Differential Equations on Manifolds with Geometrically Constrained Operator-Valued Kernels.
    By Huang, D., He, H., Harlim, J. and Li, Y.
    In International Conference on Learning Representations (ICLR) 20252025.

    • 2024

  • [1]
    Street-Level Temperature Estimation using Graph Neural Networks: Performance, Feature Embedding and Interpretability.
    By Yu, Y., Li, P., Huang, D. and Sharma, A.
    In Urban Climate, vol. 56, p. 102003, 2024.
  • [2]
    PIDGeuN: Graph Neural Network-Enabled Transient Dynamics Prediction of Networked Microgrids Through Full-Field Measurement.
    By Yu, Y., Jiang, X., Huang, D. and Li, Y.
    In IEEE Access, 2024.
  • [3]
    A Convex Approach to High-fidelity Landing Trajectory Optimization for Advanced Air Mobility.
    By Wu, Y., Deniz, S., Wang, Z. and Huang, D.
    In AIAA SciTech 2024 Forum2024.
  • [4]
    Development of Weak-Form Physics-Infused Reduced-Order Modeling With Applications.
    By Vargas Venegas, C.A. and Huang, D.
    In AIAA SciTech 2024 Forum2024.
  • [5]
    Control-Theoretic Physics-Infused Reduced-Order Modeling with Infinite-Dimensional Parametric Inputs.
    By Vargas Venegas, C.A. and Huang, D.
    In SIAM UQ242024.
  • [6]
    Parametrized Global Linearization Models for Flutter Prediction.
    By Song, J., Yu, Y. and Huang, D.
    In AIAA SciTech 2024 Forum2024.
  • [7]
    Reduced-Order Modeling for Fluid-Thermal-Structural Interaction of Cone-Slice-Ramp in High-Speed Flows.
    By Sadagopan, A. and Huang, D.
    In AIAA SciTech 2024 Forum2024.
  • [8]
    Control Co-Design of a Slender Structure in High-Speed Flow via Fast Multiobjective Bayesian Optimization.
    By Renganathan, A., Carlson, K. and Huang, D.
    In AIAA Aviation Forum and Ascend 2024, p. 4026, 2024.
  • [9]
    Residual Dynamic Mode Decomposition with Control for Nonlinear Aeroservoelastic Applications.
    By Rains, J.C., Huang, D. and Wang, Y.
    In AIAA SciTech 2024 Forum2024.
  • [10]
    Touchless Underwater Wall-Distance Sensing via Active Proprioception of a Robotic Flapper.
    By Panta, K., Deng, H., Zhang, Z., Huang, D., Panah, A. and Cheng, B.
    In Bioinspiration & Biomimetics, vol. 19, no. 2, p. 026009, 2024.
  • [11]
    Enhancing Transient Dynamics Stabilization in Islanded Microgrids Through Adaptive and Hierarchical Data-Driven Predictive Droop Control.
    By Nandakumar, A., Li, Y., Xu, Z. and Huang, D.
    In IEEE Transactions on Smart Grid, 2024.
  • [12]
    Evaluation of Shock Wave-Boundary Layer Interaction Modeling Capabilities for Use in a Hypersonic Aerothermoelastic Framework.
    By Kimmel, E., Huang, D., Sharma, V., Singh, J., Raman, V. and Friedmann, P.P.
    In AIAA SciTech 2024 Forum2024.
  • [13]
    Modularized Bilinear Koopman Operator for Modeling and Predicting Transients of Microgrids.
    By Jiang, X., Li, Y. and Huang, D.
    In IEEE Transactions on Smart Grid, 2024.
  • [14]
    Data-Driven Modeling and Prediction of Transient Dynamics of Microgrids through Dynamic Mode Decomposition with Control.
    By Jiang, X., Li, Y. and Huang, D.
    In 2024 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), pp. 1–5, 2024.
  • [15]
    Tangent and Normal Space-Based Method for Dynamics Identification in Microgrids.
    By He, H., Harlim, J., Huang, D. and Li, Y.
    In 2024 IEEE Transportation Electrification Conference and Expo (ITEC), pp. 1–5, 2024.

    • 2023

  • [1]
    Graph-based Hierarchical Control of Electrified Aircraft Systems with Automated Timescale Decomposition.
    By Yu, Y., Park, S., Huang, D. and Pangborn, H.
    In AIAA Aviation 2023 Forum2023.
  • [2]
    Precision Landing Trajectory Optimization for eVTOL Vehicles with High-Fidelity Aerodynamic Models.
    By Wu, Y., Deniz, S., Shi, Y., Wang, Z. and Huang, D.
    In AIAA Aviation 2023 Forum2023.
  • [3]
    Optimal Landing Control of eVTOL Vehicles Using ODE-Based Aerodynamic Model.
    By Wang, Z., Wu, Y. and Huang, D.
    In AIAA SciTech 2023 Forum2023.
  • [4]
    PyPose: A Library for Robot Learning With Physics-Based Optimization.
    By Wang, C., Gao, D., Xu, K., Geng, J., Hu, Y., Qiu, Y., Li, B., Yang, F., Moon, B., Huang, D. and others.
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 22024–22034, 2023.
  • [5]
    Physics-Infused Reduced-Order Modeling of Aerothermal Loads for Hypersonic Aerothermoelastic Analysis.
    By Vargas Venegas, C.A. and Huang, D.
    In AIAA Journal, vol. 61, no. 3, 2023.
  • [6]
    Modal Analysis of Spatiotemporal Data via Multi-fidelity Multi-variate Gaussian Processes.
    By Song, J. and Huang, D.
    In AIAA Aviation 2023 Forum2023.
  • [7]
    Hypersonic Fluid-Thermal-Structural Interaction of Cone-Slice-Ramp: Computations with Experimental Validation.
    By Sadagopan, A., Huang, D., Jirasek, A., Seidel, J., Pandey, A. and Casper, K.M.
    In AIAA Journal, vol. 61, no. 11, pp. 4752–4771, 2023.
  • [8]
    Hierarchical Multi-Layered Sparse Identification for Prediction of Non-Linear Dynamics of Reconfigurable Microgrids.
    By Nandakumar, A., Li, Y. and Huang, D.
    In 2023 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), pp. 1–6, 2023.
  • [9]
    Regional Heatwave Prediction using Graph Neural Network and Weather Station Data.
    By Li, P., Yu, Y., Huang, D., Sharma, A. and Wang, Z.-H.
    In Geophysical Research Letters, 2023.
  • [10]
    Design of an Aeroelastically Scaled Model in a Compressible Air Wind Tunnel Facility Using Multifidelity Multi-Objective Bayesian Optimization.
    By Huang, D., Renganathan, A. and Miller, M.
    In AIAA SciTech 2023 Forum2023.
  • [11]
    Learning Koopman Operators with Control Using Bi-level Optimization.
    By Huang, D., Prasetyo, M.B., Yu, Y. and Geng, J.
    In 62nd IEEE Conference on Decision and Control (CDC)2023.
  • [12]
    Geometric Design of Hypersonic Vehicles for Optimal Mission Performance with High-Fidelity Aerodynamic Models.
    By Coulter, B.G., Huang, D. and Wang, Z.
    In Journal of Aircraft, vol. 60, no. 3, pp. 870–882, 2023.

    • 2022

  • [1]
    Reduced-Order Modeling of Ship Airwakes with Atmospheric Turbulence Effects using Dynamic Graph Networks.
    By Yu, Y., Major, D.A., Huang, D. and Schmitz, S.
    In AIAA SciTech 2022 Forum, p. 2533, 2022.
  • [2]
    Physics-Infused Reduced Order Modeling of Hypersonic Aerothermal Loads for Aerothermoelastic Analysis.
    By Vargas Venegas, C.A. and Huang, D.
    In AIAA SciTech 2022 Forum, p. 0989, 2022.
  • [3]
    Modal Analysis of a Shear Layer in High-Supersonic Cavity Flows using Data-Driven and Operator-Based Resolvent Analysis.
    By Sadagopan, A., Huang, D., Safari, M. and Yeh, C.-A.
    In Bulletin of the American Physical Society2022.
  • [4]
    An Experimental and Computational Correlation Study for Fluid-Thermal-Structural Interaction of a Control Surface in Hypersonic Flow.
    By Sadagopan, A., Huang, D., Jirasek, A., Seidel, J., Pandey, A. and Casper, K.M.
    In AIAA SciTech 2022 Forum, p. 0291, 2022.
  • [5]
    Study of Fluid-Thermal-Structural Interaction in High-Temperature High-Speed Flow using Multi-Fidelity Multi-Variate Surrogates.
    By Huang, D., Sadagopan, A., Düzel, Ü. and Hanquist, K.M.
    In Journal of Fluids and Structures, vol. 113, p. 103682, 2022.
  • [6]
    Koopman Operators for Bifurcation Analysis in Hypersonic Aerothermoelasticity.
    By Guého, D., Macchio, G.R., Huang, D. and Singla, P.
    In AIAA SciTech 2022 Forum, p. 0655, 2022.
  • [7]
    Geometric Design of Hypersonic Vehicles for Optimal Mission Performance using Machine Learning.
    By Coulter, B., Wang, Z. and Huang, D.
    In AIAA SciTech 2022 Forum, p. 1304, 2022.

    • 2021

  • [1]
    Expedient Hypersonic Aerothermal Prediction for Aerothermoelastic Analysis via Field Inversion and Machine Learning.
    By Vargas Venegas, C.A. and Huang, D.
    In AIAA Scitech 2021 Forum, p. 1707, 2021.
  • [2]
    Modeling of the Blade Crossover Interaction Using Machine Learning.
    By Sharma, K., Surenderan, V., Yu, Y., Huang, D., Brentner, K. and Anusonti-Inthra, P.
    In 77th Annual Vertical Flight Society (VFS) Forum and Technology Display2021.
  • [3]
    Multi-Variate Gaussian Process Regression for Angles-Only Initial Orbit Determination.
    By Schwab, D., Singla, P. and Huang, D.
    In AAS/AIAA Astrodynamics Specialist Conference, 2020, pp. 3077–3096, 2021.
  • [4]
    Numerical Investigation of Fluid-Thermal-Structural Interaction for a Control Surface in Hypersonic Flow.
    By Sadagopan, A., Huang, D., Xu, H. and Yang, X.I.
    In AIAA Scitech 2021 Forum, p. 0911, 2021.
  • [5]
    Assessment of High-Temperature Effects on Hypersonic Aerothermoelastic Analysis Using Multi-Fidelity Multi-Variate Surrogates.
    By Sadagopan, A., Huang, D., Duzel, U., Martin, L.E. and Hanquist, K.M.
    In AIAA Scitech 2021 Forum, p. 1610, 2021.
  • [6]
    Resilience Analysis of Cyber-Physical Networked Microgrids With Communication Latency.
    By Li, Y., Huang, D., Zhang, Y. and Orekan, T.
    In 2021 IEEE Power & Energy Society General Meeting (PESGM), pp. 1–5, 2021.
  • [7]
    Identifying Hopf Bifurcations of Networked Microgrids Induced by the Integration of EV Charging Stations.
    By Jiang, X., Li, Y., Du, L. and Huang, D.
    In 2021 IEEE Transportation Electrification Conference & Expo (ITEC), pp. 690–694, 2021.
  • [8]
    Applications of Gaussian Process Regression in the Aero-Thermo-Servo-Elastic Analysis Towards Integrated Hypersonic Flight Dynamic Analysis.
    By Huang, D.
    In 60th IEEE Conference on Decision and Control (CDC), pp. 6–15, 2021.
  • [9]
    Sparse Nonlinear System Identification for Hypersonic Aerothermoelastic Analysis with Stochastic Loads.
    By Guého, D., Singla, P. and Huang, D.
    In AIAA Scitech 2021 Forum, p. 1609, 2021.
  • [10]
    Time-Varying Linear Reduced Order Model for Hypersonic Aerothermoelastic Analysis.
    By Guého, D., Singla, P. and Huang, D.
    In AIAA Scitech 2021 Forum, p. 1706, 2021.
  • [11]
    Hypersonic Trajectory Optimization with High-Fidelity Aerothermodynamic Models.
    By Coulter, B., Wang, Z., Huang, D. and others.
    In AIAA Scitech 2021 Forum, p. 0715, 2021.

    • 2020

  • [1]
    Impact of High-Temperature Effects on the Aerothermoelastic Behavior of Composite Skin Panels in Hypersonic Flow.
    By Sadagopan, A., Huang, D. and Hanquist, K.M.
    In AIAA Scitech 2020 Forum, p. 0937, 2020.
  • [2]
    An Aerothermoelastic Analysis Framework with Reduced-Order Modeling Applied to Composite Panels in Hypersonic Flows.
    By Huang, D. and Friedmann, P.P.
    In Journal of Fluids and Structures, vol. 94, 2020.
  • [3]
    Multi-Objective Optimization Framework for Hypersonic Aerothermoelastic Scaling Laws and Its Application.
    By Huang, D. and Friedmann, P.P.
    In AIAA Journal, vol. 58, no. 7, pp. 3250–3257, 2020.

    • 2019

  • [1]
    A Multi-Objective Optimization Framework for Hypersonic Aerothermoelastic Scaling Laws and Its Application to Skin Panels.
    By Huang, D. and Friedmann, P.P.
    In International Forum on Aeroelasticity and Structural Dynamics (IFASD)no. 2019-143, , pp. 1–44, 2019.
  • [2]
    A Surrogate-Based Optimization Framework for Hypersonic Aerothermoelastic Scaling Laws with Application to Skin Panels.
    By Huang, D. and Friedmann, P.P.
    In 16th Dynamics Specialists Conference, pp. 1–27, 2019.
  • [3]Development of a Hypersonic Aerothermoelastic Framework and Its Application to Flutter and Aerothermoelastic Scaling of Skin Panels, PhD thesis, University of Michigan, Ann Arbor, 2019

    • 2018

  • [1]
    Efficient Modeling of Fluid-Structure-Thermal Interaction in Hypersonic Flow.
    By Rokita, T., Huang, D. and Friedmann, P.P.
    In 58th Israel Annual Conference on Aerospace Sciences2018.
  • [2]
    An Integrated Aerothermoelastic Analysis Framework With Application to Skin Panels.
    By Huang, D., Rokita, T. and Friedmann, P.P.
    In AIAA Journal, vol. 56, no. 11, pp. 4562–4581, 2018.
  • [3]
    Aerothermoelastic Scaling Laws for Hypersonic Skin Panel Configurations with Arbitrary Flow Orientation.
    By Huang, D., Rokita, T. and Friedmann, P.P.
    In 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (SDM), pp. 1–23, 2018.
  • [4]
    Aerothermoelastic Scaling Laws for Hypersonic Skin Panel Configurations with Arbitrary Flow Orientation.
    By Huang, D., Friedmann, P.P. and Rokita, T.
    In AIAA Journal, 2018.

    • Before 2018

  • [1]
    Efficient Reduced-Order Modeling for Skin Panels in Hypersonic Flow and Its Application to Generating Aerothermoelastic Scaling Laws.
    By Huang, D., Rokita, T. and Friedmann, P.P.
    In International Forum on Aeroelasticity and Structural Dynamics (IFASD)2017.
  • [2]
    An Aerothermoelastic Analysis Framework Enhanced by Model Order Reduction With Applications.
    By Huang, D., Rokita, T. and Friedmann, P.P.
    In 58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, pp. 1–19, 2017.
  • [3]
    An Integrated Aerothermoelastic Analysis Framework for Predicting the Response of Composite Panels.
    By Huang, D. and Friedmann, P.P.
    In 15th Dynamics Specialists Conference, pp. 1–37, 2016.