Ling Zheng | Computer Science and Artificial Intelligence | Research Excellence Award

Dr. Ling Zheng | Computer Science and Artificial Intelligence | Research Excellence Award

Fujian Maternity and Children Health Hospital | China 

The researcher holds advanced training in computer science with a strong specialization in artificial intelligence and machine learning, Computer Science and Artificial Intelligence particularly in efficient attention mechanisms and multimodal large models for medical and healthcare applications. Current research focuses on the development of intelligent systems for placental pathology analysis, automated diagnostic report generation, and AI-assisted clinical decision support. Major contributions include the construction of annotated medical image databases, AI-guided lesion standardization frameworks, and the application of dynamic intelligent models to support maternal health interventions. The research portfolio also extends to large-scale data management, privacy protection, and secure data sharing technologies for auditory and visual cognitive models, as well as knowledge graph representation and swarm intelligence collaboration. In addition to academic research, the work includes close collaboration with industry partners to develop domain-specific large models for gynecologic oncology and multimodal AI systems for placental pathology diagnosis. Scholarly contributions span high-impact peer-reviewed journals in artificial intelligence, medical informatics, data science, and interdisciplinary computational research. The researcher has also contributed to the academic community through service on program committees for leading international conferences in artificial intelligence, computer vision, and data analytics. Overall, the research demonstrates strong innovation, translational impact, and commitment to advancing AI-driven healthcare technologies.

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Featured Publications

Computer-aided detection of prostate cancer in T2-weighted MRI within the peripheral zone
A. Rampun, L. Zheng, P. Malcolm, B. Tiddeman, R. Zwiggelaar – Physics in Medicine & Biology, 61(13), 4796, 2016

Self-adjusting harmony search-based feature selection
L. Zheng, R. Diao, Q. Shen – Soft Computing, 19(6), 1567–1579, 2015

Feature grouping and selection: A graph-based approach
L. Zheng, F. Chao, N. Mac Parthaláin, D. Zhang, Q. Shen – Information Sciences, 546, 1256–1272, 2021

Boundary-aware network with two-stage partial decoders for salient object detection in remote sensing images
Q. Zheng, L. Zheng, Y. Bai, H. Liu, J. Deng, Y. Li – IEEE Transactions on Geoscience and Remote Sensing, 61, 1–13, 2023

A distributed joint extraction framework for sedimentological entities and relations with federated learning
T. Wang, L. Zheng, H. Lv, C. Zhou, Y. Shen, Q. Qiu, Y. Li, P. Li, G. Wang – Expert Systems with Applications, 213, 119216

Dr. Hadeel Saadany | Computer Science | Best Researcher Award

Dr. Hadeel Saadany | Computer Science | Best Researcher Award

Birmingham City University | United Kingdom

Author Profile 

GOOGLE SCHOLAR 

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. Xiaopeng wang  – Intelligent Manufacturing – Best  Researcher Award 

Mr. Xiaopeng wang  - Intelligent Manufacturing - Best  Researcher Award 

Hebei University of Science and Technology - China 

Author Profile

ORCID 

GOOGLE SCHOLAR 

🌟 Early academic pursuits

Xiaopeng wang embarked on his academic journey with a keen interest in welding engineering and materials science. he pursued his doctoral studies with a focus on innovative detection methods for welding defects, demonstrating a strong foundation in interdisciplinary research. his early academic work laid the groundwork for integrating deep learning algorithms with traditional welding technologies, showcasing his commitment to advancing this niche field.

🧑‍🏫 Professional endeavors

As an assistant professor at hebei university of science and technology, xiaopeng wang has contributed significantly to academia and industry. his professional career is marked by his expertise as an international welding engineer and his dedication to fostering innovation in welding defect detection. his collaborations with industry and academia reflect his role as a bridge between theoretical advancements and practical applications.

🔬 Contributions and research focus

Xiaopeng wang’s research explores the integration of deep learning with welding defect detection. his groundbreaking investigations on channel and spatial attention mechanisms have enhanced understanding of feature information entropy and improved model accuracy. his work demonstrates how attention mechanisms can amplify the focus on welding defect features, Intelligent Manufacturing leading to more precise detection and clustering of defects.

🏆 Accolades and recognition

Xiaopeng wang's contributions have earned him a respected reputation in his field. his research has been published in prestigious journals such as expert systems with applications and ndt&e international. with over 10 academic papers to his credit and a citation index of 40 on google scholar, Intelligent Manufacturing his work has gained significant acknowledgment from the scientific community.

🌍 Impact and influence

By advancing intelligent detection methods for welding defects, xiaopeng wang’s research has broad implications for both academic research and industrial applications. his insights into deep Intelligent Manufacturing learning and attention mechanisms have set new benchmarks in the field, improving defect detection processes and enhancing the efficiency and reliability of welding operations worldwide.

📚 Legacy and future contributions

Xiaopeng wang continues to push the boundaries of research, focusing on novel applications of deep learning in welding and materials science. his ongoing projects, supported by grants like the national natural science foundation of china (u2141216), reflect his dedication to pioneering advancements in his field. he aspires to mentor future researchers and foster global collaborations to expand the scope of intelligent welding technologies.

Notable Publications 

  • Title: Zoom in on the target network for the prediction of defective images and welding defects' location
    Author(s): Xiaopeng Wang, Baoxin Zhang, Xinghua Yu
    Journal: NDT & E International
  • Title: Image Analysis of the Automatic Welding Defects Detection Based on Deep Learning
    Author(s): Xiaopeng Wang, Baoxin Zhang, Jinhan Cui, Juntao Wu, Yan Li, Jinhang Li, Yunhua Tan, Xiaoming Chen, Wenliang Wu, Xinghua Yu
    Journal: Journal of Nondestructive Evaluation
  • Title: Understanding the effect of transfer learning on the automatic welding defect detection
    Author(s): Xiaopeng Wang, Xinghua Yu
    Journal: NDT & E International
  • Title: Binary classification of welding defect based on deep learning
    Author(s): Xiaopeng Wang, Xu Wang, Baoxin Zhang, Jinhan Cui, Xinpeng Lu, Chuan Ren, Weijia Cai, Xinghua Yu
    Journal: Science and Technology of Welding and Joining
  • Title: X-ray stress measurement process of aluminum alloy by analysis of the full width at half maxima
    Author(s): Xiaoyan Li
    Journal: (Not specified, please verify)

Mr. Wei Li – digitization – Best Researcher Award

Mr. Wei Li - digitization - Best Researcher Award

Jining University - China

Author Profile 

ORCID

Early academic pursuits 📚

Wei li began his academic journey with a strong focus on economics and management, laying the foundation for his expertise in digital governance. after completing his education at prestigious institutions, wei li became deeply interested in the role of digital technology in urban governance, positioning himself as a researcher committed to advancing this evolving field.

Professional endeavors 🏢

Wei li is currently a professor at the school of economics and management at jining university in china. his work has been instrumental in shaping the university’s focus on the intersection of digitalization and urban governance. in his professional capacity, he has led numerous research projects, making significant strides in understanding the role of digital tools in enhancing urban management and governance structures.

Contributions and research focus 🔍

At the core of wei li’s research is the exploration of digital technology’s role in urban governance. his work builds a comprehensive theoretical analysis framework and evaluation system for digitally driven urban management. rather than focusing solely on infrastructure and e-government platforms, his innovative approach includes digitization "soft elements" like strategic support, talent, and the security environment. wei li’s application of methods such as the extreme value variance method and obstacle degree model has been critical in identifying the key indicators restricting the development of urban digital governance in china.

Accolades and recognition 🏅

Wei li's contributions have been widely recognized in academic and governmental circles. his research is often cited in discussions on improving urban governance through digital tools, earning him respect and accolades within the fields of economics, management, and urban studies. his innovative thinking and application of digitization practical frameworks have placed him at the forefront of urban digital governance research in china.

Impact and influence 🌍

Wei li’s work on digitally driven urban governance has had a significant impact on policy and academic approaches in china. by addressing the balance of "hard" and "soft" elements in urban governance, his research has influenced both local and national government strategies in the digitalization of urban management systems. digitization his comprehensive models are now used to assess and improve the governance capabilities of chinese cities, aiding in the transition to smarter, more efficient urban environments.

Legacy and future contributions 🚀

Through his dedication to the field of digital governance, wei li is leaving behind a lasting legacy of innovation and practical application. his research paves the way for more advanced models that can be adopted by cities globally, making urban governance more efficient, inclusive, and adaptable. looking forward, wei li is poised to continue contributing to the development of new digital frameworks that will shape the cities of the future, driving smarter, more sustainable urban management practices.

Notable Publications 

  • Title: Digitally Driven Urban Governance: Framework and Evaluation in China
    Authors: Wei Li, Jun Zhang, Xiaojie Guo, Yang Zhou, Fan Yang, Ruilin Li
    Journal: Sustainability
    Date: 2024-11-06
    DOI: 10.3390/su16229673
  • Title: Human Capital Structure and Innovation Efficiency Under Technological Progress: Evidence from China
    Authors: Wei Li, Yuanxiang Peng, Jingjing Yang, Md Sazzad Hossain
    Journal: Sage Open
    Date: 2024-07
    DOI: 10.1177/21582440241277165