Ansar Shah l Big Data | Research Excellence Award

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Assoc. Prof. Dr. Ansar Shah l Big Data | Research Excellence Award

University of Southern Punjab Multan | Pakistan

Dr. Ansar Munir Shah is an Associate Professor of Computer Science with extensive experience in teaching, research, academic leadership, and curriculum development at undergraduate and graduate levels. Dr. Ansar Munir Shah holds a PhD in Computer Science from the University of Technology Phnom Penh, Cambodia, and is an HEC-approved PhD supervisor with strong academic credentials. Dr. Ansar Munir Shah has served in prominent academic roles at EM&E College (NUST), King Khalid University, and ISP Multan, earning multiple awards for committee service and academic excellence. Dr. Ansar Munir Shah’s research interests include wireless sensor networks, IoT, cloud computing, cybersecurity, and AI-driven network and data security.

Citation Metrics (Scopus)

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Featured Publications

Big Data Meets Jugaad: Cultural Innovation Strategies for Sustainable Performance in Resource-Constrained Developing Economies
– Sustainability, 2025
DOI: 10.3390/su17157087
Dynamic and Integrated Security Model in Inter Cloud for Image Classification
– Foundation University Journal of Engineering and Applied Sciences, 2024
DOI: 10.33897/fujeas.v4i1.874
Efficient Energy and Delay Reduction Model for Wireless Sensor Networks
– Computer Systems Science and Engineering, 2023
DOI: 10.32604/csse.2023.030802
ILSM: Incorporated Lightweight Security Model for Improving QoS in WSN
– Computer Systems Science and Engineering, 2023
DOI: 10.32604/csse.2023.034951
Improved-Equalized Cluster Head Election Routing Protocol for Wireless Sensor Networks
– Computer Systems Science and Engineering, 2023
DOI: 10.32604/csse.2023.025449

Maria Adam | Spectrum localization | Research Excellence Award

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Dr. Maria Adam | Spectrum localization | Research Excellence Award

 University of Thessaly | Greece

Dr. Maria Adam is a Professor in the Department of Computer Science and Biomedical Informatics at the University of Thessaly, Greece, with extensive expertise in spectral analysis, numerical ranges, numerical linear algebra, and matrix theory with applications to systems theory, algorithms, graphs, statistics, and biostatistics. She earned her PhD in Mathematics from the National Technical University of Athens, following a BSc in Mathematics from the University of Athens. Dr. Maria Adam has a distinguished academic career spanning professorial roles, international teaching appointments, and participation in major national and industrial research projects. She is an active journal reviewer, editorial board member, and conference organizer, contributing significantly to mathematical sciences research and education.

Citation Metrics (Scopus)

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Citations
171

Documents
48

h-index
7

Citations

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Featured Publications


Curves and Spectrum Localization of Real Matrices

– Linear Algebra and Its Applications, Vol. 733, 2026

Selection of the Fastest Solution of the Complex Riccati Equation

– WSEAS Transactions on Systems and Control, Vol. 19, 2024

I/O SNR and Noise Covariances Norm Ratio Relation in Kalman Filter

– WSEAS Transactions on Systems and Control, Vol. 19, 2024

Mohammed Almulla | Prescriptive Analytics | Research Excellence Award

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Prof. Mohammed Almulla | Prescriptive Analytics | Research Excellence Award

Kuwait University | Kuwait

Prof. Mohammed Almulla is a distinguished computer scientist with a Ph.D. from McGill University, Canada. He has served Kuwait University for over three decades, progressing from Assistant Professor to Professor, and held key administrative roles including Department Chair and Acting Vice President. His research focuses on artificial intelligence, automated theorem proving, database systems, and digital transformation in education. He contributed to ABET accreditation, ICT infrastructure, and eLearning initiatives, and actively participates in international conferences and journal reviews. Recognized for his leadership and innovation, he has received awards for informatics excellence, fostering advancements in computing education and research.

Citation Metrics (Scopus)

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Citations
613

Documents
72

h-index
14

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Top 5 Publications

Data-Driven Anesthesia: An Ensemble Model for Propofol and Remifentanil Dosage Control During Medical Surgery

International Journal of Research and Scientific Innovation, 2025
DOI: 10.51244/ijrsi.2025.121500017p
Authors: Abas Almaayofi, Farah Almulla, Mohammed A. Almulla
A Trust-Based Global Expert System for Disease Diagnosis Using Hierarchical Federated Learning

Journal of Engineering Research, 2025
DOI: 10.1016/j.jer.2025.03.001
Authors: Farah M. Almulla, Mohammed A. Almulla
A Novel CLIPS-Based Medical Expert System for Migraine Diagnosis and Treatment Recommendation

Kuwait Journal of Science, 2025
DOI: 10.1016/j.kjs.2024.100310
Author: Mohammed A. Almulla
On the Effect of Prior Knowledge in Text-Based Emotion Recognition

International Journal of Research and Scientific Innovation, 2024
DOI: 10.51244/ijrsi.2024.1108005
Author: Mohammed A. Almulla
Facial Expression Recognition Using Deep Convolution Neural Networks

IEEE Annual Congress on Artificial Intelligence of Things (AIoT), 2024
DOI: 10.1109/aiot63253.2024.00022
Author: Mohammed A. Almulla

Razi Al-Azawi | Image Processing | Research Excellence Award

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Prof. Dr. Razi Al-Azawi | Image Processing | Research Excellence Award

University of Technology | Iraq

Prof. Dr. Razi Al-Azawi is a distinguished academic and researcher specializing in informatics, artificial intelligence, and advanced computational systems. He holds dual B.Sc. degrees in Laser and Optoelectronics Engineering from the University of Technology and Mathematical Sciences from Mustansiriah University, an M.Sc. in Modeling and Simulation from the University of Technology, and a PhD in Informatics from Kharkov National University of Radio Electronics. Over a career spanning more than two decades, he has taught a wide range of postgraduate and undergraduate courses, including image processing, deep learning, AI, modeling and simulation, information theory, optimization, probability, web design, and advanced programming. His research interests encompass machine learning, data mining, medical image analysis, laser engineering, cybersecurity, and advanced computational modeling. He has supervised over 50 undergraduate theses and numerous postgraduate dissertations at the Higher Diploma, M.Sc., and PhD levels. His scholarly output includes 16 documents, 264 citations by 257 documents, and an h-index of 6. He has served as a reviewer for several international journals and conferences and holds multiple patents under processing. Through his academic leadership and scientific contributions, he continues to advance innovation in computer science, AI, and engineering domains.

Profiles : Scopus |

Featured Publications

Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

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Mrs. Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

North Dakota State University(NDSU) | United States

Umme Habiba is a dedicated researcher and educator in computer science whose work centers on machine learning, deep learning, transformer-based architectures, explainable AI, and swarm intelligence, particularly within medical data analysis. She is pursuing her Ph.D. and M.Sc. in Computer Science at North Dakota State University, where she has gained extensive teaching experience as an instructor of record and graduate teaching assistant across several undergraduate courses. Her research contributions span clinical text mining, medical risk prediction, brain–computer interface modeling, IoT security, and usability analysis of mHealth applications, with publications in reputable international journals. She has also collaborated on projects involving mobile sensor–based spatial analysis, voice-controlled IoT automation systems, and hybrid ML models for network intrusion detection. Her academic journey began with a bachelor’s degree in Computer Science and Engineering, where she developed a strong foundation in data-driven system design and intelligent applications. She has received consistently high teaching evaluations and has demonstrated a commitment to interdisciplinary research and student learning. Her long-term goal is to contribute impactful solutions at the intersection of artificial intelligence and healthcare while advancing as both a researcher and an educator.

Profile : Orcid

Featured Publication

PSO-optimized TabTransformer architecture with feature engineering for enhanced cervical cancer risk prediction, 2026

Piotr Porwik | Machine Learning and AI Applications | Best Researcher Award

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Prof. Dr. Piotr Porwik | Machine Learning and AI Applications | Best Researcher Award

University of Silesia | Poland

Prof. Dr. Piotr Porwik is a full professor in the Institute of Computer Science at the University of Silesia in Katowice, specializing in engineering and technical sciences. He earned his M.Sc. in computer science from the University of Silesia in 1978, his Ph.D. in 1985, and completed his habilitation in 2006 at AGH University of Science and Technology in Krakow. His research spans machine learning, biometrics, image processing, biomedical imaging, and spectral methods for Boolean functions. Across his career, he has authored 81 scientific documents that have attracted 1,003 citations from 783 citing documents, and he holds an h-index of 17. He has published extensively in journals, international conferences, books, and book chapters, while also supervising Master’s and Ph.D. students. Prof. Porwik has served in major academic leadership roles, including Deputy Dean and Director of the Institute, and played a key role in shaping academic publishing as Editor-in-Chief of the Journal of Medical Informatics and Technologies. His achievements have been recognized through numerous distinctions, including the Bronze Cross of Merit and multiple awards from the President of the University of Silesia for scientific accomplishments. His work continues to advance biometric security, classifier development, and biomedical informatics, underscoring his long-standing academic influence and research innovation.

Profiles : Scopus | Orcid

Featured Publications

Wrobel, K., Porwik, P., & Orczyk, T. (2025). “Evaluation of the Effectiveness of Ranking Methods in Detecting Feature Drift in Artificial and Real Data” in (Book) / Lecture Notes in?

Mensah Dadzie, B., & Porwik, P. (2025). “Feature-Based Drift Detection in Non-stationary Data Streams Using Multiple Classifiers: A Comprehensive Analysis” in (Book)

Porwik, P., Orczyk, T., Wrobel, K., & Mensah Dadzie, B. (2025). “A Novel Method for Drift Detection in Streaming Data Based on Measurement of Changes in Feature Ranks” in Journal of Artificial Intelligence and Soft Computing Research, (DOI: 10.2478/jaiscr-2025-0008).

Porwik, P., Orczyk, T., & Japkowicz, N. (2024). “Supervised and Unsupervised Analysis of Feature Drift in a New Type of Detector” in Preprint (Research Square)

Porwik, P., Orczyk, T., & Doroz, R. (2022). “A Stable Method for Detecting Driver Maneuvers Using a Rule Classifier” in Lecture Notes in Computer Science

Modafar Ati | Machine Learning and AI Applications | Best Researcher Award

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Assoc. Prof. Dr. Modafar Ati | Machine Learning and AI Applications | Best Researcher Award

Abu Dhabi University | United Arab Emirates

Assoc. Prof. Dr. Modafar Ati is an accomplished academic and researcher in Computer Science and Information Technology with extensive experience in teaching, curriculum development, and leadership. He holds a BSc in Electrical & Communication Engineering and a PhD in Electrical & Computing Engineering from Newcastle upon Tyne, UK. Dr. Ati has over three decades of experience in both academia and industry, serving in senior roles including Associate Professor at Abu Dhabi University, Acting Dean at Sohar University, and Assistant Dean at multiple institutions in Oman. His professional expertise spans software development, systems integration, networking, ICT, project management, Service-Oriented Architecture (SOA), Artificial Intelligence, Big Data, Cybersecurity, and eHealth smart systems. He has published numerous research articles focusing on AI-driven Chronic Disease Management and smart healthcare systems and has led research groups in eGovernment and ICT. Dr. Ati has received multiple grants and awards, including the Chancellor Innovation Award, and serves on editorial boards and as a senior reviewer for international journals and conferences. His teaching portfolio covers programming, network security, project management, human-computer interaction, and mobile application development. Dr. Ati’s contributions to education, research, and innovation reflect a strong commitment to advancing technology-driven solutions in healthcare, smart cities, and digital systems.

Profile : Google Scholar

Featured Publications

Hussein, A. S., Omar, W. M., Li, X., & Ati, M. (2012). “Efficient chronic disease diagnosis prediction and recommendation system” in 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, 209–214.

Mohamed, O., Kewalramani, M., Ati, M., & Al Hawat, W. (2021). “Application of ANN for prediction of chloride penetration resistance and concrete compressive strength” in Materialia, 17, 101123.

Mohamed, O. A., Ati, M., & Najm, O. F. (2017). “Predicting compressive strength of sustainable self-consolidating concrete using random forest” in Key Engineering Materials, 744, 141–145.

Hussein, A. S., Omar, W. M., Li, X., & Ati, M. (2012). “Accurate and reliable recommender system for chronic disease diagnosis” in Global Health, 3(2), 113–118.

Ati, M., Kabir, K., Abdullahi, H., & Ahmed, M. (2018). “Augmented reality enhanced computer aided learning for young children” in 2018 IEEE Symposium on Computer Applications & Industrial Electronics.

Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

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Mr. Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

Jamia Millia Islamia | India

Author Profile

Google Scholar

Mr. Mohammad Zahid

Junior Research Fellow | Ph.D. Scholar in Computer Science | Cybersecurity & AI Researcher

Summary

Mohammad Zahid is a motivated and research-focused computer science professional currently pursuing a Ph.D. in Computer Science at Jamia Millia Islamia, New Delhi. He is working as a Junior Research Fellow (JRF) with a specialization in IoT security, machine learning, deep learning, and federated learning. With strong analytical and technical skills, he is actively engaged in AI-driven cybersecurity research, aiming to develop intelligent systems for threat detection. Zahid is passionate about contributing to innovative and interdisciplinary projects in both academia and the tech industry.

Education

Mr. Zahid is currently enrolled in a Ph.D. program at Jamia Millia Islamia (Central University), New Delhi, with a research focus in computer science and AI. He holds a Master of Computer Applications (MCA) from Maulana Azad National Urdu University (MANUU), Hyderabad, where he graduated with an excellent academic record (87.6%). He also completed a Bachelor of Science (Hons) in Chemistry, Mathematics, and Physics from Aligarh Muslim University (AMU), Aligarh.

Professional Experience

As a Junior Research Fellow, Mr. Zahid is engaged in cutting-edge research related to cybersecurity and artificial intelligence. During his postgraduate studies, he developed a web-based fraud detection system that utilized machine learning algorithms to identify and visualize suspicious banking transactions. His hands-on experience includes technologies such as Java, MySQL, JavaScript, and HTML/CSS, with a strong foundation in data preprocessing and anomaly detection.

Research Interests

Mr. Zahid’s research interests span across IoT security, federated learning, machine learning, and deep learning. His current Ph.D. research is centered on AI-based cybersecurity frameworks, especially for detecting and mitigating threats in decentralized and IoT-based environments. He is particularly interested in applying federated learning models to preserve data privacy while improving detection efficiency in real-world systems.

Honors and Awards

Mr. Zahid was awarded the UGC Junior Research Fellowship (JRF) in Computer Science by the National Testing Agency (NTA) in March 2022, recognizing him among the top national-level researchers eligible for academic and research roles across Indian universities. He also received the Merit-cum-Means Scholarship for Professional Courses from the Ministry of Minority Affairs, Government of India, during his MCA studies (2018–2021), in acknowledgment of his academic performance and financial need.

Publications

 Empowering IoT Networks

Author: M Zahid, TS Bharati

Journal: Artificial Intelligence for Blockchain and Cybersecurity Powered IoT
Year: 2025

Enhancing Cybersecurity in IoT Systems: A Hybrid Deep Learning Approach for Real-Time Attack Detection

Author: M Zahid, TS Bharati
Journal: Discover Internet of Things, Volume 5(1), Page 73
Year: 2025

 Comprehensive Review of IoT Attack Detection Using Machine Learning and Deep Learning Techniques

Author: M Zahid, TS Bharati
Journal: 2024 Second International Conference on Advanced Computing & Communication
Year: 2024

Empowering IoT Networks: A Study on Machine Learning and Deep Learning for DDoS Attack

Author: M Zahid, TS Bharati
Journal: Artificial Intelligence for Blockchain and Cybersecurity Powered IoT
Year: 2025

Huan Rong | Best Researcher Award | Data Analysis Innovation

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Huan Rong - Nanjing University of Information Science and Technology - Data Analysis Innovation🏆

Prof Huan Rong : Data Analysis Innovation

Professional profile:

Early Academic Pursuits:

Prof. Huan Rong embarked on his academic journey at Nanjing University of Information Science and Technology (NUIST), China. He earned his Bachelor's, Master's, and Ph.D. degrees in Computer Science from NUIST between 2009 and 2020. His academic progression demonstrated his commitment to computer science, setting the foundation for his subsequent research endeavors.

Professional Endeavors:

Following his educational journey, Prof. Huan Rong entered the professional realm by joining TrendMicro, CN as a Software Developer from 2016 to 2017. His practical experience outside academia enriched his skill set and provided a different perspective on software development and its applications.

Prof. Huan Rong then transitioned back to NUIST, initially as a Lecturer from 2020 to 2023 and subsequently as an Associate Professor from 2023 onwards. These roles marked his dedication to academia, where he delved deeper into research, mentorship, and shaping future professionals in the field of artificial intelligence.

Contributions and Research Focus:

His  contributions primarily revolve around a broad spectrum of research areas, including brain-inspired computation, data mining, deep learning, natural language processing, information security, and more. His work has been published in esteemed journals such as IEEE TKDE, ACM TKDD, and Neurocomputing, among others. His research projects, funded by notable organizations like the National Natural Science Foundation of China and the Natural Science Foundation of Jiangsu Province, emphasize the significance and impact of his work.

Accolades and Recognition:

His dedication to research and innovation has earned him various accolades and recognitions. Notably, he received the Jiangsu Province Higher Education Science and Technology Research Achievement Award for his work on social network data privacy protection and public opinion supervision in 2021. Furthermore, he was granted the title of Vice President of Science and Technology in Jiangsu Province in 2022, underscoring his influential role in the academic and technological landscape.

Impact and Influence:

With a plethora of publications and active involvement in committees like the Emotional Computing Committee of the Chinese Information Processing Society of China, Rong has made a significant impact on the academic community. His research and contributions have not only advanced the field but also influenced fellow researchers and professionals, evident from his roles as a journal reviewer for several prestigious publications.

Legacy and Future Contributions:

As Prof. Huan Rong continues his academic and research journey, his legacy is shaped by his dedication to advancing the field of artificial intelligence and its applications. His focus on brain-inspired computation, data mining, and other pivotal areas signifies his commitment to addressing contemporary challenges and pushing boundaries. Moving forward, Rong's future contributions are anticipated to further enrich the field, inspire upcoming researchers, and foster innovation in artificial intelligence and related domains.

Notable Publication:

Citations:

A total of 634 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations      :634
  • h-index         :17
  • Documents  :25