Publications

N. Galioto, H. Sharma, B. Kramer, A. Gorodetsky, "Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling", Computer Methods in Applied Mechanics and Engineering, Volume 430, 2024, 117194. [Download]

H. Sharma, D. Najera-Flores, M. Todd, B. Kramer, "Lagrangian operator inference enhanced with structure-preserving machine learning for nonintrusive model reduction of mechanical systems", Computer Methods in Applied Mechanics and Engineering, Volume 423, 2024, 116865. [Download]

H. Sharma, B. Kramer, "Preserving Lagrangian structure in data-driven reduced-order modeling of large-scale dynamical systems", Physica D: Nonlinear Phenomena, Volume 462, 2024, 134128. [Download]

H. Sharma, H. Mu, P. Buchfink, R. Geelen, S. Glas, B. Kramer, "Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds", Computer Methods in Applied Mechanics and Engineering, Volume 417, 2023, 116402. [Download]

H. Sharma, Z. Wang, B. Kramer, "Hamiltonian operator inference: Physics-preserving learning of reduced-order models for canonical Hamiltonian systems", Physica D: Nonlinear Phenomena, Volume 431, 2022, 133122. [Download] 

H. Sharma, J. Borggaard, M. Patil, C. Woolsey, "Performance Assessment of Energy-preserving, Adaptive Time-step Variational Integrators", Communications in Nonlinear Science and Numerical Simulation, Volume 114, 2022, 106646. [Download]

H. Sharma, M. Patil, C. Woolsey, "A review of structure-preserving numerical methods for engineering applications", Computer Methods in Applied Mechanics and Engineering, Volume 366, 2020, 113067. [Download]

H. Sharma, M. Patil, C. Woolsey, "Energy-preserving variational integrators for forced Lagrangian systems", Communications in Nonlinear Science and Numerical Simulation, Volume 64, 2018, pp. 159-177. [Download]

H. Sharma, I. Adibnazari, J. Cervera-Torralba, M.T. Tolley, B. Kramer, "Data-driven Model Order Reduction for Soft Robots via Lagrangian Operator Inference", 26th International Symposium of Mathematical Theory of Networks and Systems (MTNS), 2024, IFAC-PaperOnline, Volume 58, pp. 91-96. [Download]

H. Sharma, N. Galioto, A. Gorodetsky, B. Kramer, "Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models", 2022 IEEE 61st Conference on Decision and Control (CDC), 2022, pp. 6742-6749. [Download]

H. Sharma, T. Lee, M. Patil, C. Woolsey, "Symplectic Accelerated Optimization on SO(3) with Lie Group Variational Integrators", 2020 American Control Conference (ACC), 2020, pp. 2826-2831. [Download]

H. Sharma, M. Patil, C. Woolsey, "Energy-preserving, Adaptive Time-Step Lie Group Variational Integrators for Rigid Body Motion in SE(3)", 2019 IEEE 58th Conference on Decision and Control (CDC), 2019, pp. 8079-8084. [Download]

H. Sharma, T. Lee, "Energy-preserving, Adaptive Time-Step Lie Group Variational Integrators for the Attitude Dynamics of a Rigid Body", 2019 American Control Conference (ACC), 2019, pp. 5487-5492. [Download]

H. Sharma, M. Patil, C. Woolsey, "Hermite-based, One-step, Variational and Galerkin Time Integrators for Mechanical Systems", arXiv:2201.07327. [Download]

Y. Zhu, H. Sharma, "Hamiltonian Adaptive Variational Integrators for Nonconservative Problems in Astrodynamics", 2024 AIAA Regional Student Conferences, p. 80056,  2024. [Download]