Adil Rasheed

Orcid: 0000-0003-2690-983X

According to our database1, Adil Rasheed authored at least 69 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Correlation-based outlier detection for ships' in-service datasets.
J. Big Data, December, 2024

Real-Time Predictive Condition Monitoring Using Multivariate Data.
IEEE Trans. Image Process., 2024

Physics-guided federated learning as an enabler for digital twins.
Expert Syst. Appl., 2024

Enhancing wind field resolution in complex terrain through a knowledge-driven machine learning approach.
Eng. Appl. Artif. Intell., 2024

Diagnostic Digital Twin for Anomaly Detection in Floating Offshore Wind Energy.
CoRR, 2024

Exploring Urban Mobility Trends using Cellular Network Data.
CoRR, 2024

Privacy Re-identification Attacks on Tabular GANs.
CoRR, 2024

Variational Autoencoders for exteroceptive perception in reinforcement learning-based collision avoidance.
CoRR, 2024

Computationally and Memory-Efficient Robust Predictive Analytics Using Big Data.
CoRR, 2024

Nonlinear Model Predictive Control for Enhanced Navigation of Autonomous Surface Vessels.
CoRR, 2024

Digital Twin for Wind Energy: Latest updates from the NorthWind project.
CoRR, 2024

Digital Twin for Autonomous Surface Vessels for Safe Maritime Navigation.
CoRR, 2024

Digital Twins in intensive aquaculture - Challenges, opportunities and future prospects.
Comput. Electron. Agric., 2024

Enhancing elasticity models with deep learning: A novel corrective source term approach for accurate predictions.
Appl. Soft Comput., 2024

Modular control architecture for safe marine navigation: Reinforcement learning with predictive safety filters.
Artif. Intell., 2024

CasTGAN: Cascaded Generative Adversarial Network for Realistic Tabular Data Synthesis.
IEEE Access, 2024

Multivariate Time-Series Methods with Uncertainty Estimation for Correcting Physics-Based Model: Comparisons and Generalization for Industrial Drilling Process.
Proceedings of the Artificial Intelligence Applications and Innovations, 2024

Unveiling Urban Mobility Patterns: A Data-Driven Analysis of Public Transit.
Proceedings of the International Conference on Control, Automation and Diagnosis, 2024

2023
Physics Guided Machine Learning for Variational Multiscale Reduced Order Modeling.
SIAM J. Sci. Comput., June, 2023

Unsupervised Anomaly Detection for IoT-Based Multivariate Time Series: Existing Solutions, Performance Analysis and Future Directions.
Sensors, March, 2023

Sparse deep neural networks for modeling aluminum electrolysis dynamics.
Appl. Soft Comput., February, 2023

Deep learning assisted physics-based modeling of aluminum extraction process.
Eng. Appl. Artif. Intell., 2023

Modular Control Architecture for Safe Marine Navigation: Reinforcement Learning and Predictive Safety Filters.
CoRR, 2023

Enhancing Elasticity Models: A Novel Corrective Source Term Approach for Accurate Predictions.
CoRR, 2023

Machine Learning for enhancing Wind Field Resolution in Complex Terrain.
CoRR, 2023

Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions.
CoRR, 2023

Deep active learning for nonlinear system identification.
CoRR, 2023

Sparse neural networks with skip-connections for nonlinear system identification.
CoRR, 2023

Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions.
IEEE Access, 2023

A Comparative Study of Sparsity Promoting Techniques in Neural Network for Modeling Non-Linear Dynamics.
IEEE Access, 2023

Artificial Intelligence-Driven Digital Twin of a Modern House Demonstrated in Virtual Reality.
IEEE Access, 2023

Data Integration Framework for Virtual Reality Enabled Digital Twins.
Proceedings of the 9th IEEE World Forum on Internet of Things, 2023

Sparse Neural Networks with Skip-Connections for Identification of Aluminum Electrolysis Cell.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
Physics guided neural networks for modelling of non-linear dynamics.
Neural Networks, 2022

Risk-based implementation of COLREGs for autonomous surface vehicles using deep reinforcement learning.
Neural Networks, 2022

Deep neural network enabled corrective source term approach to hybrid analysis and modeling.
Neural Networks, 2022

An environmental disturbance observer framework for autonomous ships.
CoRR, 2022

A novel corrective-source term approach to modeling unknown physics in aluminum extraction process.
CoRR, 2022

Prospects of federated machine learning in fluid dynamics.
CoRR, 2022

Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systems.
CoRR, 2022

Decentralized digital twins of complex dynamical systems.
CoRR, 2022

Data Processing Framework for Ship Performance Analysis.
CoRR, 2022

Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach.
Appl. Soft Comput., 2022

Unsupervised Clustering of Marine Vessel Trajectories in Historical AIS Database.
Proceedings of the 25th International Conference on Information Fusion, 2022

A receding-horizon estimation and control framework for the content sequencing problem.
Proceedings of the European Control Conference, 2022

Wienerization Based Control of Nonlinear Systems.
Proceedings of the European Control Conference, 2022

Wienerization of systems in nonlinear control canonical normal form.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021
Geometric Change Detection in Digital Twins.
Digit., June, 2021

Self-Organising Map Based Framework for Investigating Accounts Suspected of Money Laundering.
Frontiers Artif. Intell., 2021

Comparing Deep Reinforcement Learning Algorithms' Ability to Safely Navigate Challenging Waters.
Frontiers Robotics AI, 2021

Applying object detection to marine data and exploring explainability of a fully convolutional neural network using principal component analysis.
Ecol. Informatics, 2021

Nonlinear proper orthogonal decomposition for convection-dominated flows.
CoRR, 2021

Ship Performance Monitoring using Machine-learning.
CoRR, 2021

Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution.
CoRR, 2021

Geometric Change Detection in Digital Twins using 3D Machine Learning.
CoRR, 2021

Machine Learning for Capacity Utilization Along the Routes of an Urban Freight Service.
Proceedings of the Intelligent Technologies and Applications, 2021

2020
Deep Reinforcement Learning Controller for 3D Path Following and Collision Avoidance by Autonomous Underwater Vehicles.
Frontiers Robotics AI, 2020

Physics guided machine learning using simplified theories.
CoRR, 2020

On the effectiveness of signal decomposition, feature extraction and selection on lung sound classification.
CoRR, 2020

A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction.
CoRR, 2020

Interface learning of multiphysics and multiscale systems.
CoRR, 2020

Marine life through You Only Look Once's perspective.
CoRR, 2020

Proportional integral derivative controller assisted reinforcement learning for path following by autonomous underwater vehicles.
CoRR, 2020

Digital Twin: Values, Challenges and Enablers From a Modeling Perspective.
IEEE Access, 2020

Taming an Autonomous Surface Vehicle for Path Following and Collision Avoidance Using Deep Reinforcement Learning.
IEEE Access, 2020

COLREG-Compliant Collision Avoidance for Unmanned Surface Vehicle Using Deep Reinforcement Learning.
IEEE Access, 2020

2019
Dissecting Deep Neural Networks.
CoRR, 2019

A non-intrusive reduced order modeling framework for quasi-geostrophic turbulence.
CoRR, 2019

2018
Discovering Thermoelectric Materials Using Machine Learning: Insights and Challenges.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018


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