Dr. Hadeel Saadany | Computer Science | Best Researcher Award

Dr. Hadeel Saadany | Computer Science | Best Researcher Award

Birmingham City University | United Kingdom

Author Profile 

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Summary


Hadeel Saadany is a distinguished researcher and lecturer specializing in natural language processing, computational linguistics, and data science. she holds a phd in computer science (nlp) and an ma in computational linguistics from the university of wolverhampton, uk. her professional journey spans roles as a lecturer in data science, research fellow, and research assistant, contributing to machine learning model development, large language model applications, knowledge graph construction, sentiment analysis, and multilingual dataset curation. she has supervised numerous undergraduate and postgraduate projects, collaborated with industrial partners, published in peer-reviewed journals, and participated in nlp shared tasks and editorial work.

Early academic pursuits


Hadeel Saadany pursued her phd in computer science with a focus on natural language processing at the university of wolverhampton, uk, completing it in 2023 with honours pass with no correction. prior to her phd, she earned an ma in computational linguistics from the same university in 2019, achieving distinction. her academic journey reflects a deep commitment to language technologies and computational methods, providing a solid foundation for her research and professional endeavors in nlp and ai.

Professional endeavors


Hadeel currently serves as a lecturer in data science at birmingham city university, uk, where she leads and develops modules on ai and machine learning for undergraduate students, while also teaching postgraduate courses in python programming, applied machine learning, and ai. she supervises final year projects and master’s dissertations in computer science and collaborates on faculty research projects focusing on large language models and knowledge graph implementation.

Contributions and research focus


Hadeel’s research is centered on natural language processing, machine learning, and data science applications. she specializes in large language models, knowledge graph implementations, sentiment analysis, information retrieval, and custom language model construction for domain-specific speech recognition. her work extends to compiling and curating multilingual datasets, building relational networks, and employing statistical analysis and visualization techniques for textual data. she actively publishes in peer-reviewed nlp and data science journals and participates in shared tasks, workshops, and conferences.

Impact and influence


Hadeel’s work has influenced both academic and industrial applications of nlp. through her research fellow role and collaboration with industrial partners, she has implemented practical machine learning solutions for commercial pipelines. her supervision of undergraduate and postgraduate students has fostered new talent in computational linguistics and data science. her participation in conferences, workshops, and peer-reviewed publications has contributed to advancing nlp methodologies, multilingual data analysis, and sentiment detection technologies.

Academic cites


Hadeel’s research output spans multiple peer-reviewed journals and conferences in nlp, computational linguistics, and data science. her publications include work on large language models, knowledge graph integration, sentiment analysis, and information retrieval systems. her editorial work with the natural language engineering journal further highlights her engagement in scholarly communication and peer review processes.

Legacy and future contributions


Hadeel Saadany is poised to continue shaping the field of nlp and data science through her teaching, research, and collaborative projects. her future contributions are expected to focus on enhancing large language model applications, improving multilingual data processing, and developing knowledge graph-based solutions for real-world problems. she remains dedicated to mentoring emerging researchers and integrating innovative ai and nlp methods into both academic and industrial settings.

Publications 

Title: BLEU, METEOR, BERTScore: Evaluation of Metrics Performance in Assessing Critical Translation Errors in Sentiment-oriented Text
Author(s): H. Saadany, C. Orasan
Journal: Proceedings of TRITON (TRanslation and Interpreting Technology ONline), 48-56, 2021

Title: Fake or Real? A Study of Arabic Satirical Fake News
Author(s): H. Saadany, E. Mohamed, C. Orasan
Journal: Proceedings of the 3rd International Workshop on Rumours and Deception, 2020

Title: Is it Great or Terrible? Preserving Sentiment in Neural Machine Translation of Arabic Reviews
Author(s): H. Saadany, C. Orasan
Journal: Proceedings of the Fifth Arabic Natural Language Processing Workshop, 24-37, 2020

Title: RGCL at IDAT: deep learning models for irony detection in Arabic language
Author(s): T. Ranasinghe, H. Saadany, A. Plum, S. Mandhari, E. Mohamed, C. Orasan, …
Journal: IDAT, 2019

Title: Challenges in Translation of Emotions in Multilingual User-Generated Content: Twitter as a Case Study
Author(s): H. Saadany, C. Orasan, R.C. Quintana, F. Carmo, L. Zilio
Journal: arXiv preprint arXiv:2106.10719

Conclusion


Hadeel’s work has made a significant impact on both academic research and practical applications of nlp and ai. through her teaching, mentoring, and collaborative projects, she continues to advance the fields of computational linguistics and data science. her dedication to innovation, research excellence, and student development positions her as a leading contributor to the future of natural language processing and machine learning, shaping the next generation of researchers and practitioners.

Assist. Prof. Dr. Ali sayghe | Cyber-Physical Security and Sensnor | Best Researcher Award

Assist. Prof. Dr. Ali sayghe | Cyber-Physical Security and Sensnor | Best Researcher Award

Department of Electrical Engineering/ Yanbu Industril College | Saudi Arabia

Author Profile 

Orcid

Summary

Ali sayghe is an assistant professor and researcher specializing in control systems and cyber-physical security for power systems, with a strong academic background from florida state university, arizona state university, and the university of illinois at chicago. his career combines teaching at yanbu industrial college with innovative research on digital twins, intrusion detection, and the resilience of industrial power systems. blending linear and nonlinear control theory with machine learning, he addresses the evolving challenges of critical infrastructure. his work is widely recognized in academic cites and continues to shape advancements in secure and reliable energy systems.

Early academic pursuits

Ali Sayghe’s educational journey reflects a strong foundation in engineering and technology, beginning with an associate’s degree in telecommunications technology from the college of telecommunication and electronics. he advanced to earn a bachelor of science in electrical and electronic engineering technology with a specialization in telecommunications engineering from arizona state university, followed by a master of technology in electronic engineering technology from the same institution. his pursuit of excellence led him to doctoral research, first at the university of illinois at chicago and later completing a phd in control and cyber-physical security for power systems at florida state university. throughout these formative years, his academic pursuits laid the groundwork for his expertise in control systems, cyber-physical security, and critical infrastructure resilience.

Professional endeavors

Ali sayghe has served as an assistant professor at yanbu industrial college in yanbu al sinaiyah, al madinah, saudi arabia. he has been deeply engaged in teaching, mentoring, and guiding engineering students, bringing real-world applications into the classroom. his professional endeavors also encompass research collaborations in control systems and cyber-physical security for the power and energy industry, often integrating machine learning into advanced control designs. this combination of teaching and applied research underscores his commitment to both academia and industry relevance.

Contributions and research focus

Ali Sayghe’s research contributions center on the reliability, resilience, and security of industrial power systems. he has advanced work in digital twins, intrusion detection systems, and robust control strategies, addressing both linear and nonlinear frameworks. integrating control systems and cyber-physical security with modern machine learning techniques, his work ensures that power infrastructure remains protected against evolving threats. these contributions have been published in reputable scientific journals and conference proceedings, showcasing his role as an innovative researcher in this specialized domain.

Impact and influence

Through his dual role as educator and researcher, ali sayghe has significantly influenced the field of control systems and cyber-physical security for power systems. his ability to simplify complex engineering concepts for students has fostered a generation of engineers equipped to handle the challenges of modern power networks. in the research community, his studies on digital twins and industrial system security are shaping best practices for safeguarding critical infrastructure. his influence extends internationally, bridging the academic and industrial sectors.

Academic cites

Ali sayghe’s work has been cited in multiple research papers, highlighting the relevance and applicability of his findings. his academic cites reflect recognition from fellow scholars and practitioners working in control systems, cyber-physical security, and power system engineering. these citations are a testament to the practical value and originality of his research, especially in areas that combine control theory with cutting-edge machine learning approaches.

Legacy and future contributions

Ali sayghe’s legacy is rooted in his dedication to creating safer and more resilient power systems through innovative control and cyber-physical security strategies. looking forward, he aims to further expand the integration of digital twins, predictive analytics, and artificial intelligence into industrial applications. his vision includes fostering newcomer socialization within academic and research settings, ensuring that new researchers quickly adapt and contribute to the evolving landscape of control systems and cyber-physical security for power systems. his future contributions promise to shape both the educational framework and technological innovations in the energy sector.

Publications 

Title: Security Threats and Risk Exposure in Wireless Sensor Networks for Industrial Control Systems: A Case Study
Author(s): Ali Sayghe
Journal: SSRN

Title: Digital Twin-Driven Intrusion Detection for Industrial SCADA: A Cyber-Physical Case Study
Author(s): Ali Sayghe
Journal: Sensors

Title: Digital Twin-Driven Intrusion Detection for Industrial SCADA: A Cyber-Physical Case Study
Author(s): Ali Sayghe
Journal: Preprints

Title: A Survey of Machine Learning Methods for Detecting False Data Injection Attacks in Power Systems
Author(s): Ali Sayghe, Y. Hu, I. Zografopoulos, X. Liu, R.G. Dutta, Y. Jin, C. Konstantinou
Journal: arXiv

Title: Survey of Machine Learning Methods for Detecting False Data Injection Attacks in Power Systems
Author(s): Ali Sayghe, Y. Hu, I. Zografopoulos, X. Liu, R.G. Dutta, Y. Jin, C. Konstantinou
Journal: IET Smart Grid

Conclusion

Ali sayghe’s journey reflects a deep commitment to advancing control systems and cyber-physical security for power systems through both academic excellence and applied research. his influence spans from the classroom, where he mentors the next generation of engineers, to the global research community, where his contributions guide best practices for safeguarding energy infrastructure. by fostering newcomer socialization in research and promoting innovative solutions, his future work is set to further strengthen the safety, reliability, and adaptability of industrial power systems.