Research Areas

• Numerical methods: embedded/immersed boundary method, adaptive method, high-order method.
• Scientific machine learning: Bayesian calibration/inference, neural operator, data­-driven closure modeling, tensor-­based data analysis.
• Applications: fluid­-structure interaction, aeroelasticity, Earth system model, engineering design, biomedical engineering.

Journal Publications (18)

	AI-aided Geometric Design of Anti-infection Catheters Tingtao Zhou*, Xuan Wan*, Daniel Zhengyu Huang, Zongyi Li, Zhiwei Peng, Anima Anandkumar, John F. Brady, Paul W. Sternberg, Chiara Daraio Submitted, 2023 [arXiv]
	Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance Yifan Chen, Daniel Zhengyu Huang†, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart Submitted, 2023 [arXiv] [code]
	Fourier Neural Operator with Learned Deformations for PDEs on General Geometries Zongyi Li, Daniel Zhengyu Huang, Burigede Liu, Anima Anandkumar Submitted, 2022 [arXiv] [code]
	Long Random Matrices and Tensor Unfolding Gérard Ben Arous, Daniel Zhengyu Huang, Jiaoyang Huang Annals of Applied Probability, 2023 [arXiv] [DOI]
	The Cost-Accuracy Trade-Off In Operator Learning With Neural Networks Maarten V. de Hoop, Daniel Zhengyu Huang†, Elizabeth Qian, Andrew M. Stuart Journal of Machine Learning, 2022 [arXiv] [DOI] [code]
	Efficient Derivative-Free Bayesian Inference for Large-Scale Inverse Problems Daniel Zhengyu Huang†, Jiaoyang Huang, Sebastian Reich, Andrew M. Stuart Inverse Problems, 2022 [arXiv] [DOI] [code]
	Bayesian Calibration for Large­Scale Fluid Structure Interaction Problems Under Embedded/Immersed Boundary Framework Shunxiang Cao, Daniel Zhengyu Huang† International Journal for Numerical Methods in Engineering, 2022 [arXiv] [DOI] [code]
	Iterated Kalman Methodology for Inverse Problems Daniel Zhengyu Huang†, Tapio Schneider, Andrew M. Stuart Journal of Computational Physics, 2022 [arXiv] [DOI] [code]
	Power Iteration for Tensor PCA Jiaoyang Huang, Daniel Zhengyu Huang, Qing Yang, Guang Cheng Journal of Machine Learning Research, 2022 [arXiv] [DOI]
	Learning Constitutive Relations Using Symmetric Positive Definite Neural Networks Kailai Xu*, Daniel Zhengyu Huang*, Eric Darve† Journal of Computational Physics, 2021 [arXiv] [DOI] [code]
	A Homogenized Flux-Body Force Approach for Modeling Porous Wall Boundary Conditions in Compressible Viscous Flows Daniel Zhengyu Huang†, Man Long Wong, Sanjiva K. Lele, Charbel Farhat AIAA Journal, 2021 [arXiv] [DOI] [code]
	A Computationally Tractable Framework for Nonlinear Dynamic Multiscale Modeling of Membrane Fabric Philip Avery†, Daniel Zhengyu Huang, Wanli He, Johanna Ehlers, Armen Derkevorkian, Charbel Farhat International Journal for Numerical Methods in Engineering, 2021 [arXiv] [DOI] [code]
	Learning Constitutive Relations from Indirect Observations Using Deep Neural Networks Daniel Zhengyu Huang*, Kailai Xu*, Eric Darve† Journal of Computational Physics, 2020 [arXiv] [DOI] [code]
	High-Order Partitioned Spectral Deferred Correction Solvers for Multiphysics Problems Daniel Zhengyu Huang†, Will Pazner, Per-Olof Persson, Matthew J. Zahr Journal of Computational Physics, 2020 [arXiv] [DOI] [code]
	An Embedded Boundary Approach for Resolving the Contribution of Cable Subsystems to Fully Coupled Fluid-Structure Interaction Daniel Zhengyu Huang†,Philip Avery, Charbel Farhat International Journal for Numerical Methods in Engineering, 2020 [arXiv] [DOI] [code]
	Mesh Adaptation Framework for Embedded Boundary Methods for CFD and Fluid-Structure Interaction Raunak Borker†, Daniel Zhengyu Huang, Sebastian Grimberg, Charbel Farhat, Philip Avery, Jason Rabinovitch International Journal for Numerical Methods in Fluids, 2019 [ResearchGate] [DOI] [code]
	High-Order, Linearly Stable, Partitioned Solvers for General Multiphysics Problems Based on Implicit-Explicit Runge-Kutta Schemes Daniel Zhengyu Huang†, Per-Olof Persson, Matthew J. Zahr Computer Methods in Applied Mechanics and Engineering, 2018 [arXiv] [DOI]
	A Family of Position- and Orientation-Independent Embedded Boundary Methods for Viscous Flow and Fluid-Structure Interaction Problems Daniel Zhengyu Huang, Dante De Santis, Charbel Farhat† Journal of Computational Physics, 2018 [ResearchGate] [DOI] [code]

Conference Publications (7)

	Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty Luning Sun*, Daniel Zhengyu Huang*, Hao Sun, Jian-xun Wang† Conference on Neural Information Processing Systems, 2022 [arXiv] [DOI] [code]
	Modeling, Simulation and Validation of Supersonic Parachute Inflation Dynamics During Mars Landing Daniel Zhengyu Huang†,Philip Avery, Charbel Farhat, Jason Rabinovitch, Armen Derkevorkian, Lee D Peterson AIAA Science and Technology Forum and Exposition, 2020 [arXiv] [DOI] [code]
	Effects of Structural Parameters on the FSI Simulation of Supersonic Parachute Deployments Armen Derkevorkian, Lee D Peterson, Jason Rabinovitch, Daniel Zhengyu Huang, Philip Avery, Charbel Farhat AIAA Aviation and Aeronautics Forum and Exposition, 2019 [DOI] [code]
	Towards a Validated FSI Computational Framework for Supersonic Parachute Deployments Jason Rabinovitch, Daniel Zhengyu Huang, Raunak Borker, Philip Avery, Charbel Farhat, Armen Derkevorkian, Lee D Peterson AIAA Aviation and Aeronautics Forum and Exposition, 2019 [DOI] [code]
	A High-Order Partitioned Solver for General Multiphysics Problems and Its Applications in Optimization Daniel Zhengyu Huang†, Per-Olof Persson, Matthew J. Zahr AIAA Science and Technology Forum and Exposition, 2019 [arXiv] [DOI]
	Preliminary Verification and Validation Test Suite for the CFD Component of Supersonic Parachute Deployment FSI Simulations Jason Rabinovitch, Daniel Zhengyu Huang, Raunak Borker, Philip Avery, Charbel Farhat, Armen Derkevorkian, Lee D Peterson AIAA Science and Technology Forum and Exposition, 2018 [DOI] [code]
	Simulation of Parachute Inflation Dynamics Using an Eulerian Computational Framework for Evolving Fluid-Structure Interfaces in High Speed Turbulent Flows Daniel Zhengyu Huang†, Charbel Farhat, Philip Avery, Jason Rabinovitch, Armen Derkevorkian, Lee D Peterson AIAA Science and Technology Forum and Exposition, 2018 [DOI] [code]