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.

Mr. Sajjad Molaei – Edge/Fog Computing – Best Researcher Award

Mr. Sajjad Molaei - Edge/Fog Computing - Best Researcher Award

Amirkabir University of Technology - Iran 

Author Profile 

GOOGLE SCHOLAR 

🎓 Early academic pursuits

Sajjad Molaei began his academic journey with a bachelor of science in information technology (it) engineering from the university of tabriz, tabriz, iran. during this period (2011–2015), he achieved an exceptional academic performance with a total mark of 18.20 out of 20. he completed his undergraduate studies under the supervision of dr. mohammad ali balafar and was recognized as the top student of his class. this early excellence set the foundation for his future endeavors in the field of computer engineering and power electronics.

🧑‍💼 Professional endeavors

Sajjad Molaei is currently pursuing a ph.d. in computer engineering with a major in computer networks at the amirkabir university of tehran. his doctoral research, under the supervision of dr. masoud sabaei, explores resource management in dynamic fog computing environments for internet of things (iot) applications, a topic of growing global significance in network optimization and power electronics.

🔬 Contributions and research focus

Sajjad’s research interests span a broad spectrum of cutting-edge fields, including wireless sensor networks, cloud and fog computing, internet of things (iot), computer networks, optimization, Edge/Fog Computing evolutionary algorithms, and software development. he has significantly contributed to optimizing computational methods and addressing latency in fog environments—a challenge critical to real-time systems and power electronics.

🌐 Impact and influence

As a distinguished student and a committed researcher, sajjad molaei has held memberships in several elite research groups and academic institutions. he is a valued member of the islamic republic of iran’s national elites foundation for three consecutive years (2017–2019), Edge/Fog Computing reflecting his outstanding contributions to iran’s scientific community.

📚 Academic cites

while the exact citation metrics are not specified, sajjad’s scholarly output has earned recognition through his affiliations and research contributions. his thesis topics and involvement in Edge/Fog Computing high-level labs suggest that his work is cited in contexts involving trust computation, dynamic resource allocation, and energy-aware network designs. future publications based on his ph.d. work are anticipated to be highly referenced in both academic and industrial research.

🚀 Legacy and future contributions

Sajjad Molaei is poised to leave a lasting legacy through his innovative work on resource management in iot-enabled environments. he envisions developing frameworks that ensure optimized resource utilization, minimal latency, and increased reliability—elements vital to the deployment of smart cities and advanced digital infrastructures.

Notable Publications 

  • Title: PSO-ELPM: PSO with elite learning, enhanced parameter updating, and exponential mutation operator
    Author(s): H. Moazen, S. Molaei, L. Farzinvash, M. Sabaei
    Journal: Information Sciences

  • Title: Particle swarm optimization with an enhanced learning strategy and crossover operator
    Author(s): S. Molaei, H. Moazen, S. Najjar-Ghabel, L. Farzinvash
    Journal: Knowledge-Based Systems

  • Title: Application of boosted trees to the prognosis prediction of COVID‐19
    Author(s): S. Molaei, H. Moazen, H.R. Niazkar, M. Sabaei, M.G. Johari, A. Rezaianzadeh
    Journal: Health Science Reports

  • Title: An effective cipher block scheme based on cellular automata
    Author(s): S. Molaei, S. Najjar-Ghabel, L. Farzinvash
    Journal: 2017 IEEE 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI)

  • Title: MRM-PSO: An Enhanced Particle Swarm Optimization Technique for Resource Management in Highly Dynamic Edge Computing Environments
    Author(s): S. Molaei, M. Sabaei, J. Taheri
    Journal: Ad Hoc Networks