Suivre
hojat ghorbanidehno
hojat ghorbanidehno
Student in Mechanical Engineering department, Stanford University
Adresse e-mail validée de stanford.edu
Titre
Citée par
Citée par
Année
Recent developments in fast and scalable inverse modeling and data assimilation methods in hydrology
H Ghorbanidehno, A Kokkinaki, J Lee, E Darve
Journal of Hydrology 591, 125266, 2020
392020
Real-time data assimilation for large-scale systems: The spectral Kalman filter
H Ghorbanidehno, A Kokkinaki, JY Li, E Darve, PK Kitanidis
Advances in water resources 86, 260-272, 2015
362015
The compressed state K alman filter for nonlinear state estimation: Application to large‐scale reservoir monitoring
JY Li, A Kokkinaki, H Ghorbanidehno, EF Darve, PK Kitanidis
Water Resources Research 51 (12), 9942-9963, 2015
322015
Deep learning technique for fast inference of large-scale riverine bathymetry
H Ghorbanidehno, J Lee, M Farthing, T Hesser, EF Darve, PK Kitanidis
Advances in Water Resources 147, 103715, 2021
222021
Riverine bathymetry imaging with indirect observations
J Lee, H Ghorbanidehno, MW Farthing, TJ Hesser, EF Darve, PK Kitanidis
Water Resources Research 54 (5), 3704-3727, 2018
212018
Novel data assimilation algorithm for nearshore bathymetry
H Ghorbanidehno, J Lee, M Farthing, T Hesser, PK Kitanidis, EF Darve
Journal of Atmospheric and Oceanic Technology 36 (4), 699-715, 2019
122019
Optimal estimation and scheduling in aquifer management using the rapid feedback control method
H Ghorbanidehno, A Kokkinaki, PK Kitanidis, E Darve
Advances in water resources 110, 310-318, 2017
122017
Deep learning techniques for nearshore and riverine bathymetry estimation using water-surface observations
H Ghorbanidehno, Y Qian, JH Lee, M Farthing, T Hesser, PK Kitanidis, ...
Ocean Sciences Meeting, 2020
12020
Fast Data Assimilation and Optimal Control Methods and Applications
H Ghorbanidehno
Stanford University, 2018
12018
Efficient data assimilation algorithms for bathymetry applications
H Ghorbanidehno, A Kokkinaki, JH Lee, M Farthing, T Hesser, ...
AGU Fall Meeting Abstracts 2016, OS23A-2001, 2016
12016
Optimal management of large scale aquifers under uncertainty
H Ghorbanidehno, A Kokkinaki, PK Kitanidis, EF Darve
AGU Fall Meeting Abstracts 2016, IN11C-1638, 2016
12016
Fast parameter and state estimation with the Spectral Kalman Filter: an application for CO2 injection in heterogeneous domains
H Ghorbanidehno, A Kokkinaki, EF Darve, PK Kitanidis
AGU Fall Meeting Abstracts 2014, H33C-0810, 2014
12014
Surfzone Topography-informed Deep Learning Techniques to Nearshore Bathymetry with Sparse Measurements.
Y Qian, H Ghorbanidehno, MW Farthing, T Hesser, PK Kitanidis, EF Darve
AAAI Spring Symposium: MLPS, 2020
2020
deep learning techniques for riverine bathymetry and flow velocity estimation
H Ghorbanidehno, JH Lee, M Farthing, T Hesser, PK Kitanidis, EF Darve, ...
AGU Fall Meeting 2019, 2019
2019
Rapid wave model-based nearshore bathymetry inversion with UAS measurements
JH Lee, M Farthing, T Hesser, KL Brodie, H Ghorbanidehno, MP Geheran, ...
AGU Fall Meeting 2019, 2019
2019
deep learning techniques for riverine bathymetry and flow velocity estimation
M Forghani, H Ghorbanidehno, JH Lee, M Farthing, T Hesser, ...
AGU Fall Meeting Abstracts 2019, EP53C-07, 2019
2019
Applications of Deep Neural Network to Near-shore Bathymetry with Sparse Measurements
Y Qian, H Ghorbanidehno, JH Lee, M Farthing, T Hesser, PK Kitanidis, ...
AGU Fall Meeting Abstracts 2019, EP43C-04, 2019
2019
Nearshore Bathymetry Estimation using Batch Inversion from UAS Based Observations
T Hesser, JH Lee, H Ghorbanidehno, MP Geheran, KL Brodie, BL Bruder, ...
AGU Fall Meeting Abstracts 2018, EP52D-34, 2018
2018
Bathymetry estimation using deep learning techniques
H Ghorbanidehno, JH Lee, M Farthing, T Hesser, PK Kitanidis, EF Darve
AGU Fall Meeting Abstracts 2018, IN21D-0746, 2018
2018
Riverine bathymetry imaging with indirect observations.
LJH Lee JongHyun, H Ghorbanidehno, MW Farthing, TJ Hesser, ...
2018
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–20