Adil Rasheed
Background and activities
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
Courses
- TK8117 - Multivariate Data Analysis - Advanced Topics
- TTK4260 - Multivariate analysis and Machine learning methods
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
2022
- (2022) Deep neural network enabled corrective source term approach to hybrid analysis and modeling. Neural Networks. vol. 146.
- (2022) Data Processing Framework for Ship Performance Analysis. arXiv.org.
- (2022) Ship Performance Monitoring using Machine-learning. Ocean Engineering. vol. 254.
- (2022) Risk-based implementation of COLREGs for autonomous surface vehicles using deep reinforcement learning. Neural Networks. vol. 152.
- (2022) Frame invariant neural network closures for Kraichnan turbulence. arXiv.
- (2022) Multi-fidelity information fusion with concatenated neural networks. Scientific Reports. vol. 12 (1).
- (2022) Physics guided neural networks for modelling of non-linear dynamics. arXiv.org.
2021
- (2021) A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction. Computers & Fluids. vol. 221.
- (2021) On closures for reduced order models— A spectrum of first-principle to machine-learned avenues. Physics of Fluids. vol. 33 (9).
- (2021) Multifidelity computing for coupling full and reduced order models. PLOS ONE. vol. 16 (2).
- (2021) Nonlinear proper orthogonal decomposition for convection-dominated flows. Physics of Fluids. vol. 33 (12).
- (2021) Self-organising map based framework for investigating accounts suspected of money laundering. Frontiers in Artificial Intelligence. vol. 4.
- (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) Comparing Deep Reinforcement Learning Algorithms’ Ability to Safely Navigate Challenging Waters. Frontiers in Robotics and AI. vol. 8.
- (2021) A novel hybrid analysis and modeling approach applied to aluminum electrolysis process. Journal of Process Control. vol. 105.
- (2021) Hybrid analysis and modeling for next generation of digital twins. Journal of Physics: Conference Series (JPCS). vol. 2018.
- (2021) Model fusion with physics-guided machine learning: Projection-based reduced-order modeling. Physics of Fluids. vol. 33 (6).
- (2021) A nonintrusive hybrid neural-physics modeling of incomplete dynamical systems: Lorenz equations. GEM - International Journal on Geomathematics. vol. 12.
- (2021) Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution. GAMM-Mitteilungen. vol. 44 (2).