Radwa El Shawi

Orcid: 0000-0002-5679-9099

According to our database1, Radwa El Shawi authored at least 52 papers between 2011 and 2026.

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Bibliography

2026
Optimizing stock price forecasting: a hybrid approach using fuzziness and automated machine learning.
Expert Syst. Appl., 2026

2025
Empowering Machine Learning With Scalable Feature Engineering and Interpretable AutoML.
IEEE Trans. Artif. Intell., February, 2025

To tune or not to tune? An approach for recommending important hyperparameters for classification and clustering algorithms.
Future Gener. Comput. Syst., 2025

AgingFedNAS: Aging Evolution Federated Deep Learning for Architecture and Hyperparameter Search.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2025

Zero-Shot Machine Unlearning Using Generative Adversarial Network.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2025

Context-Aware AutoML for Accurate Wheat Disease Detection.
Proceedings of the Workshops of the EDBT/ICDT 2025 Joint Conference co-located with the EDBT/ICDT 2025 Joint Conference, 2025

Automated Machine Learning for Ex-ante Life Cycle Assessment of Barley Production.
Proceedings of the Workshops of the EDBT/ICDT 2025 Joint Conference co-located with the EDBT/ICDT 2025 Joint Conference, 2025

FedForecaster: An Automated Federated Learning Approach for Time-series Forecasting.
Proceedings of the Proceedings 28th International Conference on Extending Database Technology, 2025

ML-EvalPro: Machine Learning Evaluation Profiler for Supervised Tasks.
Proceedings of the Artificial Intelligence in Medicine - 23rd International Conference, 2025

2024
ConceptGlassbox: Guided Concept-Based Explanation for Deep Neural Networks.
Cogn. Comput., September, 2024

AutoMLBench: A comprehensive experimental evaluation of automated machine learning frameworks.
Expert Syst. Appl., 2024

MachineLearnAthon: An Action-Oriented Machine Learning Didactic Concept.
CoRR, 2024

GizaML: A Collaborative Meta-learning Based Framework Using LLM For Automated Time-Series Forecasting.
Proceedings of the Proceedings 27th International Conference on Extending Database Technology, 2024

2023
Interpretable Local Concept-based Explanation with Human Feedback to Predict All-cause Mortality (Extended Abstract).
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

OnlineAutoClust: A Framework for Online Automated Clustering.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Interpretable Local Concept-based Explanation with Human Feedback to Predict All-cause Mortality.
J. Artif. Intell. Res., 2022

AutoMLBench: A Comprehensive Experimental Evaluation of Automated Machine Learning Frameworks.
CoRR, 2022

TPE-AutoClust: A Tree-based Pipline Ensemble Framework for Automated Clustering.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

cSmartML-Glassbox: Increasing Transparency and Controllability in Automated Clustering.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

BigFeat: Scalable and Interpretable Automated Feature Engineering Framework.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
To tune or not to tune? An Approach for Recommending Important Hyperparameters.
CoRR, 2021

DLBench: a comprehensive experimental evaluation of deep learning frameworks.
Clust. Comput., 2021

Interpretability in healthcare: A comparative study of local machine learning interpretability techniques.
Comput. Intell., 2021

Research perspective: the role of automated machine learning in fuzzy logic.
Proceedings of WILF 2021, 2021

Towards Automated Concept-based Decision TreeExplanations for CNNs.
Proceedings of the 24th International Conference on Extending Database Technology, 2021

cSmartML: A Meta Learning-Based Framework for Automated Selection and Hyperparameter Tuning for Clustering.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
An Empirical Analysis of Integrating Feature Extraction to Automated Machine Learning Pipeline.
Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

D-SmartML: A Distributed Automated Machine Learning Framework.
Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020

2019
On the interpretability of machine learning-based model for predicting hypertension.
BMC Medical Informatics Decis. Mak., 2019

Automated Machine Learning: State-of-The-Art and Open Challenges.
CoRR, 2019

Correction to: Runtime self-monitoring approach of business process compliance in cloud environments.
Clust. Comput., 2019

A Decision Support Framework for AutoML Systems: A Meta-Learning Approach.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Automated Machine Learning: Techniques and Frameworks.
Proceedings of the Big Data Management and Analytics - 9th European Summer School, 2019

DLBench: An Experimental Evaluation of Deep Learning Frameworks.
Proceedings of the 2019 IEEE International Congress on Big Data, 2019

ILIME: Local and Global Interpretable Model-Agnostic Explainer of Black-Box Decision.
Proceedings of the Advances in Databases and Information Systems, 2019

2018
Correction To: Large scale graph processing systems: survey and an experimental evaluation.
Clust. Comput., 2018

Big Data Systems Meet Machine Learning Challenges: Towards Big Data Science as a Service.
Big Data Res., 2018

2017
Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project.
BMC Medical Informatics Decis. Mak., 2017

Big Data Systems Meet Machine Learning Challenges: Towards Big Data Science as a Service.
CoRR, 2017

2016
Big Data 2.0 Processing Systems: Taxonomy and Open Challenges.
J. Grid Comput., 2016

2015
Large scale graph processing systems: survey and an experimental evaluation.
Clust. Comput., 2015

Runtime self-monitoring approach of business process compliance in cloud environments.
Clust. Comput., 2015

Runtime detection of business process compliance violations: an approach based on anti patterns.
Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

BP-MaaS: A Runtime Compliance-Monitoring System for Business Processes.
Proceedings of the BPM Demo Session 2015 Co-located with the 13th International Conference on Business Process Management (BPM 2015), 2015

Big Graph Processing Systems: State-of-the-Art and Open Challenges.
Proceedings of the First IEEE International Conference on Big Data Computing Service and Applications, 2015

2014
A fast algorithm for data collection along a fixed track.
Theor. Comput. Sci., 2014

Quickest path queries on transportation network.
Comput. Geom., 2014

On Characterizing the Performance of Distributed Graph Computation Platforms.
Proceedings of the Performance Characterization and Benchmarking. Traditional to Big Data, 2014

An Overview of Large-Scale Stream Processing Engines.
Proceedings of the Large Scale and Big Data - Processing and Management., 2014

2013
Fast query structures in anisotropic media.
Theor. Comput. Sci., 2013

2011
Quickest Paths in Anisotropic Media.
Proceedings of the Combinatorial Optimization and Applications, 2011

Shortest Path in Transportation Network and Weighted Subdivisions.
Proceedings of the Graph Data Management: Techniques and Applications., 2011


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