Adil Rasheed
Bakgrunn og aktiviteter
Research Interests
- Bigdata Cybernetics: Combining data-driven methods with control theory
- Hybrid Analytics / Modeling: Combining physics based modeling with advanced machine learning algorithms
- Artificial Intelligence and Machine Learning
- Reduced Order Modeling
- Computational Fluid Dynamics and Turbulence Modelling
- Numerical Methods
Application Area
- Wind Energy
- Aviation
- Autonomous Vessels
- Drones in urban area
Vitenskapelig, faglig og kunstnerisk arbeid
Et utvalg av nyere tidsskriftspublikasjoner, kunstneriske produksjoner, bok, inklusiv bokdeler og rapport-del. Se alle publikasjoner i databasen
Tidsskriftspublikasjoner
- (2021) A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction. Computers & Fluids. vol. 221.
- (2021) Multifidelity computing for coupling full and reduced order models. PLOS ONE. vol. 16 (2).
- (2021) On the effectiveness of signal decomposition, feature extraction and selection to identify lung crackles. arXiv.
- (2021) Statistical modeling of Ship’s hydrodynamic performance indicator. Applied Ocean Research. vol. 111.
- (2021) Deep Reinforcement Learning Controller for 3D Path-following and Collision Avoidance by Autonomous Underwater Vehicles. Frontiers in Robotics and AI. vol. 7.
- (2021) Hybrid analysis and modeling for next generation of digital twins. arXiv.
- (2021) Physics guided machine learning using simplified theories. Physics of Fluids. vol. 33 (1).
- (2021) Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution. arXiv.org.
- (2021) Applying Object Detection to Marine Data and Exploring Explainability of a Fully Convolutional Neural Network Using Principal Component Analysis. Ecological Informatics. vol. 62.
- (2021) Geometric Change Detection in Digital Twins using 3D Machine Learning. arXiv. vol. 1.
- (2020) Forward sensitivity approach for estimating eddy viscosity closures in nonlinear model reduction. Physical review. E. vol. 102 (4).
- (2020) Reduced order modeling of fluid flows: Machine learning, Kolmogorov barrier, closure modeling, and partitioning. arXiv.org.
- (2020) Interface learning of multiphysics and multiscale systems. Physical review. E. vol. 102 (5).
- (2020) A long-short term memory for hybrid uplifted reduced order models. Physica D : Non-linear phenomena. vol. 409.
- (2020) Fast divergence-conforming reduced basis methods for stationary and transient flow problems. Journal of Physics: Conference Series (JPCS). vol. 1669.
- (2020) Proportional integral derivative controller assisted reinforcement learning for path following by autonomous underwater vehicles. arXiv.org.
- (2020) COLREG-Compliant Collision Avoidance for Unmanned Surface Vehicle using Deep Reinforcement Learning. IEEE Access. vol. 8.
- (2020) Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning. IEEE Access. vol. 8.
- (2020) An evolve-then-correct reduced order model for hidden fluid dynamics. Mathematics. vol. 8 (4).
- (2020) Data-driven recovery of hidden physics in reduced order modeling of fluid flows. Physics of Fluids. vol. 32 (3).