Ebenezer Esenogho | Computer Science | Research Excellence Award

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Prof. Ebenezer Esenogho | Computer Science | Research Excellence Award

University of South Africa | South Africa

Prof. Ebenezer Esenogho is a Professor and Head of the Centre for Artificial Intelligence and Multidisciplinary Innovation Studies at the University of South Africa, specializing in artificial intelligence, telecommunications, and emerging network technologies. He holds academic qualifications in computer engineering and advanced degrees in electronics and telecommunications engineering. His professional career spans teaching, research, and leadership roles across multiple universities, where he has contributed to curriculum development, postgraduate supervision, and multidisciplinary research initiatives. His research interests include machine learning, wireless communication systems, medical AI, and sustainable computing, with numerous peer-reviewed publications and conference contributions. He has received several competitive research grants and fellowships and holds a National Research Foundation rating, reflecting international recognition. He also serves in editorial and academic leadership capacities, supporting research development and collaboration.

Professional Profile

Education

Prof. Ebenezer Esenogho has a strong academic background in computer engineering, electronics, and telecommunications. He began with foundational training in computer engineering, developing core technical competencies in computing systems and digital technologies. He advanced to a bachelor’s degree that strengthened his analytical and engineering design skills, followed by a master’s degree focused on electronics and telecommunications engineering, where he gained deeper expertise in communication systems and signal processing. He later earned a doctoral degree in electronic engineering, with a research focus on advanced wireless networks and intelligent communication systems. His academic journey reflects a consistent progression toward specialization in cutting-edge technologies such as artificial intelligence and next-generation communication systems. This solid educational foundation has enabled him to integrate theoretical knowledge with practical innovation, preparing him for impactful research, teaching, and leadership in multidisciplinary and technology-driven environments.

Professional Experience

Prof. Esenogho has built a distinguished academic and research career across several reputable institutions, progressing from lecturer to senior academic and research leadership roles. He has contributed extensively to teaching undergraduate and postgraduate students, curriculum development, and supervision of advanced research projects. His leadership experience includes coordinating research programs, mentoring emerging scholars, and contributing to institutional strategic initiatives in technology and innovation. He has also been involved in international academic engagements and collaborative projects, supporting knowledge exchange and capacity building. In addition to teaching, he has played key roles in developing academic programs and strengthening research frameworks in engineering and artificial intelligence. His experience extends to multidisciplinary environments, where he has contributed to advancing digital transformation and innovation. Through these roles, he has demonstrated strong leadership, administrative capability, and commitment to academic excellence and research-driven impact.

Research Interest

Prof. Esenogho’s research interests lie at the intersection of artificial intelligence, machine learning, telecommunications, and interdisciplinary technological applications. His work focuses on intelligent wireless communication systems, advanced network optimization, and the integration of AI in solving real-world challenges. He has contributed to emerging areas such as deepfake detection, medical and healthcare AI, sustainable computing, and data-driven decision-making systems. His research also explores reinforcement learning, edge computing, and innovative approaches to improving network efficiency and reliability. He has authored and co-authored numerous peer-reviewed journal articles and conference papers, reflecting both depth and breadth in his research contributions. His interdisciplinary approach allows him to address complex societal and technological challenges, bridging gaps between theory and application. His work continues to contribute to advancements in next-generation communication technologies and AI-driven solutions across diverse sectors.

Award and Honor

Prof. Esenogho has received multiple recognitions that reflect his excellence in research, teaching, and academic leadership. He is a recipient of competitive research grants, fellowships, and scholarships awarded by academic institutions and industry partners, highlighting the impact and relevance of his work. He holds a National Research Foundation rating, signifying international recognition for his research contributions and scholarly influence. His achievements also include awards for outstanding research presentations and contributions to academic conferences. In addition, he has participated in international research collaborations and academic exchange initiatives that strengthen global partnerships. He serves in editorial and review capacities for scholarly publications, contributing to the advancement of knowledge in his field. His involvement in academic committees and research strategy groups further demonstrates his leadership and commitment to advancing innovation and research excellence within the global academic community.

Conclusion

Prof. Ebenezer Esenogho stands out as a dedicated scholar, researcher, and academic leader with a strong commitment to advancing knowledge in artificial intelligence and telecommunications. His solid educational background, extensive professional experience, and impactful research contributions position him as a key figure in multidisciplinary innovation. Through his work, he has consistently demonstrated the ability to address complex technological challenges and contribute meaningful solutions that benefit both academia and society. His recognition through awards, research funding, and international collaborations highlights his influence and growing global reputation. Beyond his achievements, he remains committed to mentoring the next generation of researchers and fostering collaborative research environments. His career reflects a balance of academic excellence, leadership, and innovation, making him a highly deserving candidate for recognition and continued contribution to the advancement of science, technology, and education on a global scale.

Publications Top Noted

  • A neural network ensemble with feature engineering for improved credit card fraud detection
    Author: E. Esenogho, I. D. Mienye, T. G. Swart, K. Aruleba, G. Obaido
    Year: 2022
    Citations: 421
  • Integrating artificial intelligence Internet of Things and 5G for next-generation smartgrid: A survey of trends challenges and prospect
    Author: E. Esenogho, K. Djouani, A. M. Kurien
    Year: 2022
    Citations: 307
  • Telemedicine: a survey of telecommunication technologies, developments, and challenges
    Author: C. O. Alenoghena, H. O. Ohize, A. O. Adejo, A. J. Onumanyi, E. E. Ohihoin, et al.
    Year: 2023
    Citations: 187
  • A Machine Learning Method with Filter-Based Feature Selection for Improved Prediction of Chronic Kidney Disease
    Author: I. D. M. Mienye, S. A. Ebiaredoh-Mienye, E. Esenogho, T. G. Swart
    Year: 2022
    Citations: 139
  • Crypto hash algorithm-based blockchain technology for managing decentralized ledger database in oil and gas industry
    Author: L. A. Ajao, J. Agajo, E. A. Adedokun, L. Karngong, et al.
    Year: 2019
    Citations: 129
  • Blockchain-based security mechanism for the medical data at fog computing architecture of internet of things
    Author: D. Ngabo, D. Wang, C. Iwendi, J. H. Anajemba, L. A. Ajao, C. Biamba, et al.
    Year: 2021
    Citations: 114
  • A proposed model for card fraud detection based on Catboost and deep neural network
    Author: N. Nguyen, T. Duong, T. Chau, V. H. Nguyen, T. Trinh, D. Tran, T. Ho, et al.
    Year: 2022
    Citations: 111
  • Toward integrating intelligence and programmability in open radio access networks: A comprehensive survey
    Author: A. Arnaz, J. Lipman, M. Abolhasan, M. Hiltunen, et al.
    Year: 2022
    Citations: 97
  • An interpretable machine learning approach for hepatitis B diagnosis
    Author: G. Obaido, B. Ogbuokiri, T. G. Swart, N. Ayawei, S. M. Kasongo, K. Aruleba, et al.
    Year: 2022
    Citations: 89

Bushra Naz | Deep learning | Best Researcher Award

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Dr. Bushra Naz | Deep learning | Best Researcher Award

Associate professor at Mehran University of Engineering and Technology| Pakistan

Dr. Bushra Naz is an accomplished academic and researcher with expertise in artificial intelligence, deep learning, image processing, hyperspectral image classification, and pattern recognition. Serving as an Associate Professor and PhD supervisor, she has made significant contributions to advancing knowledge through impactful research and dedicated mentorship. Her funded projects include innovative solutions in speech emotion recognition, assistive technologies for visually impaired individuals, water quality monitoring, and sustainable agriculture, reflecting a strong focus on societal benefit. She has published widely, reviewed for leading international journals, and actively participated in global conferences as a session chair and committee member. Her achievements are further recognized through prestigious scholarships, research fellowships, and honors that demonstrate her academic excellence and leadership. With a commitment to bridging theory and practice, Dr. Naz continues to drive interdisciplinary collaborations and inspire future researchers, positioning herself as a leader in advancing AI-driven solutions for real-world challenges.

Professional Profile 

Google Scholar

Education

Dr. Bushra Naz has a strong academic foundation in computer systems and engineering, beginning with a bachelor’s degree in Computer Systems Engineering, followed by a master’s degree in Communication Systems and Networks. She pursued her doctoral studies at Nanjing University of Science and Technology, China, where she completed a PhD in Computer Science and Engineering with a research focus on machine learning and hyperspectral image classification. Her doctoral thesis explored advanced elastic-net representation methods for image classification, demonstrating her early commitment to innovative AI-driven solutions. She also earned international recognition during her doctoral journey, supported by prestigious scholarships and fellowships, which allowed her to gain global exposure and strengthen her research expertise. With a solid academic trajectory rooted in both national and international institutions, Dr. Naz has combined technical depth with interdisciplinary knowledge, equipping her with the skills to pursue cutting-edge research while training the next generation of scholars and professionals.

Experience

Dr. Bushra Naz brings extensive academic and research experience spanning over a decade. She began her professional journey as a laboratory lecturer, progressively advancing to lecturer, assistant professor, and currently serves as an associate professor in the Department of Computer Systems Engineering at Mehran University of Engineering and Technology, Jamshoro. In these roles, she has taught a diverse range of subjects including microprocessors, operating systems, digital image processing, machine learning, deep learning, and artificial intelligence, shaping the technical skills of numerous students. Beyond teaching, she has taken on leadership roles in departmental committees, project supervision, curriculum review, and outcome-based education implementation. Her responsibilities also include supervising undergraduate, master’s, and doctoral research projects, many of which align with pressing technological and societal challenges. Through her experience, she has built a reputation as a dedicated educator, innovative researcher, and academic leader who seamlessly integrates research and teaching to drive meaningful outcomes.

Research Focus

Dr. Bushra Naz’s research focus lies in the application of artificial intelligence and machine learning to solve complex real-world problems. Her expertise covers deep learning, neural networks, hyperspectral imaging, image classification, object detection, and pattern recognition. She has conducted pioneering research in spectral-spatial methods for image classification, advancing techniques in optimization and sparse representation. Her projects span diverse domains, including speech emotion recognition, augmented reality-based navigation for the visually impaired, IoT-driven water quality monitoring, crop sensing for sustainable agriculture, and accident detection systems. This interdisciplinary approach highlights her commitment to applying AI solutions for societal impact, sustainability, and technological innovation. In addition, she actively contributes as a reviewer for high-impact journals and participates in international conferences as a session chair, strengthening global research dialogue. By integrating technical rigor with practical application, Dr. Naz continues to expand the frontiers of AI research while addressing challenges that directly benefit communities and industries.

Award and Honor

Dr. Bushra Naz’s academic excellence and research contributions have been recognized through numerous awards and honors at national and international levels. She received the prestigious China Scholarship Council award for her PhD studies and was further distinguished with the ELITE Scholarship as the Best Foreign Student during her doctoral program. Her excellence in research was acknowledged with honor certificates and rewards for her publications in IEEE journals. Earlier in her career, she earned the Higher Education Commission of Pakistan’s fully funded scholarship for her master’s studies and received merit-based scholarships during her undergraduate years. She also secured the UNESCO/People’s Republic of China Co-Sponsored Fellowship as a senior research scholar, reflecting her growing international recognition. These accolades not only highlight her academic dedication but also underscore her ability to compete successfully at global platforms. Collectively, her awards showcase her talent, perseverance, and impactful contributions to engineering and computer science research.

Publication Top Notes

  • Title: Sustainable Higher Education Reform Quality Assessment Using SWOT Analysis with Integration of AHP and Entropy Models: A Case Study of Morocco
    Year: 2021
    Citations: 64

  • Title: Spatial-Hessian-feature-guided variational model for pan-sharpening
    Year: 2015
    Citations: 50

  • Title: Fast superpixel based subspace low rank learning method for hyperspectral denoising
    Year: 2018
    Citations: 44

  • Title: Bilayer elastic net regression model for supervised spectral-spatial hyperspectral image classification
    Year: 2016
    Citations: 28

  • Title: Hybrid LSTM Self-Attention Mechanism Model for Forecasting the Reform of Scientific Research in Morocco
    Year: 2021
    Citations: 25

  • Title: Onion Crop Monitoring with Multispectral Imagery using Deep Neural Network
    Year: 2021
    Citations: 14

  • Title: A machine learning framework for major depressive disorder (MDD) detection using non-invasive EEG signals
    Year: 2025
    Citations: 13

  • Title: Sustainable higher education reform quality assessment using SWOT Analysis with integration of AHP and Entropy models: A case study of Morocco
    Year: 2021
    Citations: 13

  • Title: Local and nonlocal context-aware elastic net representation-based classification for hyperspectral images
    Year: 2017
    Citations: 8

  • Title: Hyperspectral image classification via Elastic Net Regression and bilateral filtering
    Year: 2015
    Citations: 8

Conclusion

Dr. Bushra Naz has established herself as a distinguished researcher and academic leader with a significant impact in the fields of artificial intelligence, machine learning, and hyperspectral image analysis. Her extensive research portfolio demonstrates a balance of theoretical innovation and practical application, addressing societal challenges such as sustainable agriculture, water quality monitoring, assistive technologies, and mental health detection. With a strong record of high-impact publications, international collaborations, research supervision, and active participation in conferences and editorial roles, she has consistently contributed to advancing knowledge and mentoring future researchers. Her achievements are further reinforced by prestigious awards, fellowships, and funded projects that recognize her scholarly excellence and leadership. Overall, Dr. Naz exemplifies the qualities of a visionary researcher—innovative, dedicated, and socially responsible—making her a highly deserving candidate for recognition through the Best Researcher Award.

María Inmaculada Mohino-Herranz | Artificial Intelligence| Best Research Article Award

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Dr. María Inmaculada Mohino-Herranz | Artificial Intelligence| Best Research Article Award

Investigador, INTA, Spain

Inmaculada Mohíno Herranz is a distinguished researcher in the fields of signal processing, pattern recognition, and emotion detection. She currently works at the National Institute of Aerospace Technology (INTA), bringing her extensive expertise in physiological signal analysis to the forefront of innovative research. 🌟 Her career reflects a commitment to advancing technology and science, contributing to both academia and industry.

Publication profile

Scopus

Education

Inmaculada holds an impressive academic background, beginning with her M.Eng. in Telecommunication Engineering (2010), followed by a second degree in Electronics Engineering (2012), and a Master’s degree in Information and Communication Technologies (2015). 📚 She culminated her academic journey with a Ph.D. in Information and Communication Technologies (2017, with honors) from the University of Alcalá, Madrid, Spain. 🎓

Experience

She has built a solid career in academia and research, having worked at the Signal Theory and Communications Department of the University of Alcalá, where she was part of the Applied Signal Processing research group until 2021. 📡 Currently, she continues her research at INTA, contributing to projects related to aerospace technology. She has also been actively involved in supervising final degree and master’s projects, shaping future innovators. 👩‍🏫

Research Focus

Inmaculada’s research revolves around physiological signal processing, pattern recognition, emotion recognition, and stress detection. 💡 Her work is especially significant in understanding how physiological data can be used to monitor emotional states, which has applications ranging from healthcare to technology-enhanced well-being. 💻

Awards and Honors

Inmaculada has received recognition for her outstanding contributions to the field of Information and Communication Technologies, including supervising several successful degree projects and participating in numerous public and private-funded research initiatives. 🏆 Her efforts in academic and industrial projects further solidify her reputation as a leading researcher.

Publication Top Notes

Inmaculada Mohíno Herranz has authored various impactful papers. She has published nine journal papers, six of which are indexed in the Journal Citation Report. 📄 She has also written a book chapter and around 20 conference papers, showcasing her active engagement in research dissemination.

Metrological analysis on measuring techniques used to determine solubility of solids in supercritical carbon dioxide – Published in Measurement: Journal of the International Measurement Confederation (2025), this article has no citations yet.

Initializing the weights of a multilayer perceptron for activity and emotion recognition – Published in Expert Systems with Applications (2024), this article has no citations yet.

Introducing the ReaLISED Dataset for Sound Event Classification – Published in Electronics (2022), cited by two articles.

Linear detector and neural networks in cascade for voice activity detection in hearing aids – Published in Applied Acoustics (2021), cited by one article.

A wrapper feature selection algorithm: An emotional assessment using physiological recordings from wearable sensors – Published in Sensors (2020), this open-access article focuses on emotion assessment using physiological data from wearable sensors.

Mubarak Albathan | AI | Best Researcher Award

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Dr Mubarak Albathan | AI | Best Researcher Award

Dr Mubarak Albathan , Imam Mohammad Ibn Saud Islamic University (IMSIU) ,Saudi Arabia

Dr. Mubarak Albathan is the Head of the Computer and Information Sciences Research Center and an Assistant Professor at Imam Muhammad Ibn Saud Islamic University in Riyadh, Saudi Arabia. He has a robust academic background, holding a PhD in Data Mining from Queensland University of Technology (QUT). With over a decade of experience in higher education, Dr. Albathan has made significant contributions to the fields of computer science and data analytics. He serves as a consultant to the Vice Rector for Graduate Studies and Scientific Research and has held various leadership roles in academia. Dr. Albathan is passionate about integrating advanced technologies into educational frameworks and enhancing research capabilities in the region. His work aims to bridge the gap between theoretical research and practical applications, driving innovation in data-driven solutions across various industries.

Publication Profile

Google Scholar

Strengths for the Award

Dr. Mubarak Albathan has demonstrated exceptional academic and research capabilities, exemplified by his extensive publication record and impactful research contributions. His work spans various critical areas, including data mining, machine learning, and healthcare applications, showcasing his versatility and innovation. Notably, he has received accolades such as the Best Student Paper Award and the International Publication Award, affirming his standing in the research community. As Head of the Computer and Information Sciences Research Center, he leads initiatives that enhance research quality and foster collaboration. Dr. Albathan’s commitment to integrating advanced technologies into practical solutions further underscores his qualifications for this prestigious award.

Areas for Improvement

While Dr. Albathan has a robust publication record, increasing the frequency of solo-authored publications could enhance his visibility as an independent researcher. Additionally, engaging in more interdisciplinary collaborations could broaden his research impact and foster innovative approaches. Expanding his outreach efforts to disseminate research findings beyond academic circles may also enhance community engagement and application of his work.

Education 

Dr. Mubarak Albathan earned his PhD in Data Mining from Queensland University of Technology (QUT) in 2015. He completed his Master’s degree in Network Computing at Monash University in 2009, where he developed a strong foundation in network systems and computational techniques. Prior to that, he received his Bachelor’s degree in Computer Science from Al-Imam Muhammad Ibn Saud Islamic University in 2004. This comprehensive educational background has equipped Dr. Albathan with the skills and knowledge necessary to excel in both academic and practical applications of computer science. His studies have focused on various aspects of computing, data mining, and network systems, leading him to engage in cutting-edge research and contribute to significant advancements in technology and education.

Experience 

Dr. Mubarak Albathan has extensive experience in academia and research management. Currently, he is the Head of the Computer and Information Sciences Research Center, a position he has held since 2023. He has also served as a consultant to the Vice Rector for Graduate Studies and Scientific Research since 2019. His previous roles include Deputy Director of the Electronic Scientific Research Portal initiative at the Ministry of Education from 2017 to 2019 and Vice-Chair of the Computer Science Department at his university from 2016 to 2017. Dr. Albathan has been involved in several academic projects and has acted as a sessional academic at QUT. His earlier experience includes supervising a diploma program in Computer Applications, showcasing his commitment to education and professional development in the field of computer science.

Awards and Honors

Dr. Mubarak Albathan has received numerous accolades for his academic and research contributions. He was awarded the Best Student Paper Award at the 2014 IEEE/WIC/ACM International Conferences on Web Intelligence in Warsaw, Poland, recognizing his exceptional research in the field. In 2015, he was honored with the International Publication Award from Imam Muhammad Ibn Saud Islamic University for his prolific contributions to scholarly publications. Dr. Albathan’s work has been recognized internationally, with his participation in several prestigious conferences, including the IEEE International Conference on Data Mining and the Australasian Joint Conference on Artificial Intelligence. His commitment to advancing knowledge in computer science and data mining continues to be acknowledged through various awards, highlighting his impact on the academic community and his dedication to research excellence.

Research Focus 

Dr. Mubarak Albathan’s research focuses on data mining, machine learning, and their applications in various domains, including healthcare, agriculture, and cybersecurity. His work emphasizes the development of optimized algorithms for pattern recognition and classification, particularly in complex datasets. Dr. Albathan is particularly interested in leveraging advanced technologies such as deep learning to address real-world challenges, such as disease diagnosis through image analysis and enhancing security protocols in IoT networks. His collaborative research projects have led to significant advancements in understanding and improving data-driven systems. Dr. Albathan’s commitment to integrating theoretical research with practical applications makes him a key contributor to the field, driving innovation and supporting the development of efficient, scalable solutions that benefit multiple sectors.

Publications Top Notes

  • Mobile-HR: An Ophthalmologic-Based Classification System for Diagnosis of Hypertensive Retinopathy Using Optimized MobileNet Architecture. 🩺
  • Leveraging Ethereum Platform for Development of Efficient Tractability System in Pharmaceutical Supply Chain. 💊
  • EfficientPNet—An Optimized and Efficient Deep Learning Approach for Classifying Disease of Potato Plant Leaves. 🌾
  • Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier. 🦠
  • A Supervised Method to Enhance Distance-based Neural Networks’ Clustering Performance by Discovering Perfect Representative Neurons. 🧠
  • Effective 20 Newsgroups Dataset Cleaning. 📊
  • Relevance Feature Discovery for Text Mining. 📖
  • Using Extended Random Set to Find Specific Patterns. 🔍
  • Interpreting Discovered Patterns in Terms of Ontology Concepts. 📚
  • Enhanced N-gram Extraction Using Relevance Feature Discovery. 🌐
  • Using Patterns Co-occurrence Matrix for Cleaning Closed Sequential Patterns for Text Mining. 📈
  • A Deep Learning Framework for the Prediction and Diagnosis of Ovarian Cancer in Pre- and Post-Menopausal Women. 🎗️
  • Optimized Deep Learning Techniques for Disease Detection in Rice Crop Using Merged Datasets. 🌱
  • Detection of Depression Trends in Literary Cyber Writers Using Sentiment Analysis and Machine Learning. 📖
  • Deep-Ocular: Improved Transfer Learning Architecture Using Self-Attention and Dense Layers for Recognition of Ocular Diseases. 👁️
  • ROAST-IoT: A Novel Range-Optimized Attention Convolutional Scattered Technique for Intrusion Detection in IoT Networks. 🔒
  • Enhancing Cloud-Based Security: A Novel Approach for Efficient Cyber-Threat Detection Using GSCSO-IHNN Model. ☁️

Conclusion

Dr. Mubarak Albathan is a highly qualified candidate for the Best Researcher Award. His impressive educational background, extensive experience, and significant contributions to research make him a standout in his field. By focusing on areas for improvement, he can further solidify his impact on academia and industry. Recognizing his achievements through this award would not only honor his dedication but also inspire future researchers in the field.