Oluwatobi Adedamola Ayilara-Adewale | Artificial Intelligence | Innovative Research Award

Published on by World Top Scientists

Dr. Oluwatobi Adedamola Ayilara-Adewale | Artificial Intelligence | Innovative Research Award

Lecturer | Osun State University | Nigeria

Dr. Oluwatobi Adedamola Ayilara-Adewale is a computer science researcher specializing in machine learning, AI-driven cybersecurity and intelligent systems, serving as an academic and research contributor in these domains. With advanced degrees in computer science and a strong foundation in computational methods and digital systems, he has gained professional experience through participation in national and international research projects involving digital resilience, smart agriculture, climate-focused data analytics and secure digital infrastructures, often providing technical leadership in multidisciplinary teams. His research focuses on artificial intelligence, IoT security, intrusion detection, blockchain security, predictive analytics and cyber-resilient architectures, supported by numerous peer-reviewed publications spanning journals, conference outputs and book chapters. He has contributed to the development of machine learning models for security, intelligent decision-support systems and emerging frameworks for digital trust. Dr. Ayilara-Adewale has received recognition for innovative research and holds professional certifications in cloud computing, cybersecurity and penetration testing. He is an active member of multiple professional bodies, reflecting his commitment to advancing knowledge in computing and cybersecurity, and he has engaged in collaborative initiatives that strengthen the ecosystem of applied AI research. His growing scholarly profile, technical versatility and dedication to secure and intelligent systems position him as a valuable contributor to contemporary research and a strong candidate for excellence awards.

Profiles: Google Scholar

Featured Publications

1. Jimoh, K., Ajayi, A., & Ayilara, O. (2014). Intelligent model for manual sorting of plastic wastes. International Journal of Computer Applications, 101(7), 20–26.

2. Jimoh, K. O., Adepoju, T. M., Sobowale, A. A., & Ayilara, O. A. (2018). Offline gesture recognition system for Yorùbá numeral counting. Asian Journal of Research in Computer Science, 1(4), 1–11.

3. Ajayi, A. O., Jimoh, K. A., & Ayilara, O. A. (2016). Evaluation of plastic waste classification systems. British Journal of Mathematics & Computer Science, 16(3), 1–11.

4. Ayilara, M. S., Fasusi, S. A., Ajakwe, S. O., Akinola, S. A., Ayilara-Adewale, O. A., … (2025). Impact of climate change on agricultural ecosystem. In Climate change, food security, and land management: Strategies for a sustainable future.

5. Olanrewaju, A., & Ayilara, O. A. (2024). The effect of data compromises on internet users: A review on financial implication of the elderly in the United States. African Journal of Social Sciences and Humanities Research, 1, 28–37.

Dr. Oluwatobi Adedamola Ayilara-Adewale’s work advances secure and intelligent digital ecosystems by integrating artificial intelligence with resilient cybersecurity frameworks. His research contributes to safer technologies, sustainable data-driven solutions and innovative systems that support societal development, industry transformation and global digital trust.

Huxiong Li | Artificial Intelligence | Artificial Intelligence

Published on by World Top Scientists

Prof. Dr. Huxiong Li | Artificial Intelligence | Artificial Intelligence

Professor | Shaoxing University | China

Prof. Dr. Huxiong Li is a leading researcher in artificial intelligence, specializing in 3D vision, intelligent perception, urban digital twins, and complex network control. He has made significant contributions through innovative research, demonstrated by his extensive publications, patents, and leadership of multiple national and international projects. His work bridges AI technologies with practical applications in cultural heritage preservation and smart city infrastructure, reflecting a strong interdisciplinary approach. Over the years, he has fostered collaborations with global institutions, enhancing the reach and impact of his research. Prof. Li’s guidance of numerous projects has not only advanced scientific understanding but also facilitated industrial implementation of AI technologies. His research demonstrates consistent excellence, originality, and societal relevance, positioning him as a prominent figure in geospatial artificial intelligence. According to Scopus, his measurable research impact includes 28 citations, 9 documents, and an h-index of 402.

Profiles: Scopus | ORCID

Featured Publications

1. Reducing the clustering challenge in the IoT using two disjoint convex hulls. Scientific Reports, 2025.

2. Integrating InSAR coherence and air pollution detection satellites to study the impact of war on air quality. International Journal of Applied Earth Observation and Geoinformation, 2025.

 

Bushra Naz | Deep learning | Best Researcher Award

Published on by World Top Scientists

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.

Ritu Tanwar | Artificial intelligence | Best Researcher Award

Published on by World Top Scientists

Ms. Ritu Tanwar | Artificial intelligence | Best Researcher Award

Research Scholar, NIT Uttarakhand, India

Ms. Ritu Tanwar is a dedicated Research Scholar at the National Institute of Technology, Uttarakhand, India, specializing in stress and emotion recognition through advanced machine learning techniques. Her innovative research harnesses deep learning and artificial intelligence to interpret physiological signals, contributing significantly to the field of affective computing. Ritu’s academic journey and teaching roles underline her commitment to advancing both theoretical and practical aspects of her research.

Profile

Scopus

Research for “Best Researcher Award” for Ms. Ritu Tanwar

Strengths for the Award

Ms. Ritu Tanwar, currently pursuing her PhD at the National Institute of Technology, Uttarakhand, has demonstrated exceptional strengths in her field of research. Her primary area of focus—stress and emotion recognition through physiological signals—highlights her deep engagement with cutting-edge technology and data analysis. Ritu’s work utilizes advanced techniques in deep learning and machine learning to address significant challenges in affective state recognition.

Innovative Research Contributions: Ritu’s research integrates multimodal physiological signals to enhance stress recognition, showcasing her ability to develop and implement novel frameworks. Her attention-based hybrid deep learning models for wearable stress recognition, published in prestigious journals like Engineering Applications of Artificial Intelligence and Computers and Electrical Engineering, underline her proficiency in blending theory with practical application.

High-Impact Publications: Her publications in high-impact journals and conferences, including Computers in Biology and Medicine and the International Conference on Artificial Intelligence, reflect the substantial impact of her work on the field. Her innovative models, such as the CNN-LSTM based stress recognition system, are well-received and contribute to advancing the state of the art in affective computing.

Diverse Expertise: Ritu’s skill set spans various domains, from deep learning and artificial intelligence to data analysis and signal processing. Her ability to apply these skills effectively in her research demonstrates a well-rounded expertise that is crucial for a leading researcher.

Areas for Improvement

While Ms. Tanwar’s achievements are commendable, there are areas where she could further enhance her profile:

Broader Research Collaboration: Expanding her collaborative network with researchers from diverse fields could provide new insights and foster interdisciplinary approaches. Engaging in more collaborative projects could also increase the visibility and applicability of her research outcomes.

Broadened Publication Scope: Although Ritu has published extensively, diversifying her publication portfolio to include more interdisciplinary journals or higher-impact venues could further amplify the reach and influence of her research.

Enhanced Outreach: Increasing her participation in academic and industry conferences, workshops, and seminars could boost her professional network and provide more platforms to showcase her research. Additionally, contributing to review articles or special issues in her field could enhance her visibility as a thought leader.

Education 🎓

Ms. Tanwar is currently pursuing a PhD in Electronics Engineering at the National Institute of Technology, Uttarakhand, India, focusing on developing a deep learning framework for affective state recognition using multimodal physiological signals (April 2021-present). She earned her M.Tech. in Electronics & Communication Engineering from the University Institute of Engineering & Technology, Kurukshetra, India, with a thesis on emotion recognition from audio signals (July 2018). Her foundational B.Tech. in Electronics & Communication Engineering was also completed at the same institute (July 2013).

Experience 💼

Ms. Tanwar has a robust academic background, having worked as a Teaching Assistant at the National Institute of Technology, Uttarakhand, where she taught courses on Microcontroller and Interfacing, Digital Signal Processing, and Speech & Image Processing. Her research experience includes contributions as an Assistant/Associate Supervisor for undergraduate students and active participation in administrative and outreach activities, including her roles as Session Coordinator and Reviewer for the IC2E3 IEEE Conference.

Research Interests 🔬

Ms. Tanwar’s research interests are centered around stress and emotion recognition, physiological signals, and advanced data analysis techniques. She specializes in applying deep learning, machine learning, and artificial intelligence to improve the accuracy and applicability of affective state recognition systems.

Awards 🏆

Senior Research Fellow Scholarship (2021-present): Awarded for her exceptional research capabilities and contributions to her field.

Publication Recognition: Her work has been accepted and recognized in leading journals and conferences, reflecting her significant contributions to the field of artificial intelligence and machine learning.

Publications Top Notes

Tanwar, R., Phukan, O. C., Singh, G., Pal, P. K., & Tiwari, S. (2024). Attention based hybrid deep learning model for wearable based stress recognition. Engineering Applications of Artificial Intelligence, 127, 107391.

Tanwar, R., Singh, G., & Pal, P. K. (2024). A Hybrid Transposed Attention Based Deep Learning Model for Wearable and Explainable Stress Recognition. Computers and Electrical Engineering (Accepted).

Tanwar, R., Singh, G., & Pal, P. K. (2024). Explainable Artificial Intelligence System For Stress Recognition Using Multimodal Physiological Signals. Computers in Biology and Medicine (under review).

Tanwar, R., Singh, G., & Pal, P. K. (2024). Stress-Wed: Stress recognition autoencoder using Wearables Data. In Second International Conference on Artificial Intelligence: Towards Sustainable Intelligence. Springer (Accepted).

Conclusion

Ms. Ritu Tanwar’s research on stress and emotion recognition using physiological signals is both innovative and impactful, making her a strong candidate for the “Best Researcher Award.” Her contributions to deep learning and machine learning in affective computing are significant, and her academic and teaching experiences add to her profile as a dedicated and knowledgeable researcher. By addressing areas for improvement, such as expanding collaboration and publication scope, Ritu can further strengthen her position as a leading researcher in her field. Her ongoing research promises to make substantial contributions to both theoretical and applied aspects of artificial intelligence and emotion recognition.

Everton Tetila | Artificial intelligence | Scientific Breakthrough Award

Published on by World Top Scientists

Assoc Prof Dr. Everton Tetila | Artificial intelligence | Scientific Breakthrough Award

professor/researcher, Universidade Federal da Grande Dourados – UFGD/FACET, Brazil

Assoc. Prof. Dr. Everton Tetila of Universidade Federal da Grande Dourados (UFGD), FACET, Brazil, stands at the forefront of artificial intelligence (AI) research, earning acclaim with the prestigious Scientific Breakthrough Award 🏆. His groundbreaking contributions to the field have propelled advancements in AI, reshaping industries and pioneering innovative solutions. With a keen focus on pushing the boundaries of technological innovation, Dr. Tetila’s work represents a fusion of academic rigor and real-world impact. As a respected professor and researcher, he continues to inspire future generations, fostering a culture of excellence and discovery in AI research.

Profile

Orcid

Academic graduation

In 2019, I obtained my PhD in Local Development from Dom Bosco Catholic University, Brazil, focusing on the innovative use of unmanned aerial vehicles and computer vision techniques for detecting and classifying soybean diseases and pests 🌱🔍. Prior to that, I completed my Master’s degree in Production Engineering at Universidade Paulista in 2007, where my research centered on software estimation processes. My academic journey began with a Bachelor’s degree in Computer Science from the State University of Mato Grosso do Sul in 2004, where I delved into bioinformatics and biological sequence analysis under the guidance of André Chastel Lima 🧬

Professional performance

In the realm of environmental sustainability and academic prowess, I’ve traversed diverse roles and responsibilities with unwavering dedication. From steering projects as a Coordinator at SEMADESC to delving into doctoral pursuits at UCDB, and nurturing minds as a Professor at UFGD, my journey embodies a mosaic of commitment and expertise. Whether it’s crafting innovative solutions in Vision Computing or delving into the depths of Database intricacies, my passion resonates across varied domains. Additionally, collaborations with esteemed institutions like UFMS and IEEE-GRSS underscore my commitment to scholarly contributions. Each engagement, be it as a Collaborator, Professor, or Reviewer, fuels my resolve to champion sustainable development and technological advancement. 🌱🎓

Publications Top Notes

  1. YOLO performance analysis for real-time detection of soybean pests
    • Authors: Tetila, Everton Castelão; Godoy da Silveira, Fábio Amaral; Da Costa, Anderson Bessa; Amorim, Willian Paraguassu; Astolfi, Gilberto; Pistori, Hemerson; Barbedo, Jayme Garcia Arnal
    • Journal: Smart Agricultural Technology
    • Year: 2024
  2. Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional
    • Authors: Tetila, E. C.; Moraes, P. M.; Constantino, M.; Costa, R. B.; Ayres, F. M.; Reynaldo, G. O.; Colman, N. A.; Machado, F. C. A. P.; Soares, K. G.; Greco, M. M. D. M.; Pistori, H.
    • Journal: Desenvolvimento e Meio Ambiente (UFPR)
    • Year: 2023
  3. Pseudo-label Semi-supervised Learning for Soybean Monitoring
    • Authors: Menezes, Gabriel Kirsten; Astolfi, Gilberto; Martins, José Augusto Correa; Castelão Tetila, Everton; da Silva Oliveira Junior, Adair; Gonçalves, Diogo Nunes; Marcato Junior, José; Silva, Jonathan Andrade; Li, Jonathan; Gonçalves, Wesley Nunes; Pistori, Hemerson
    • Journal: Smart Agricultural Technology
    • Year: 2023
  4. System for quantitative diagnosis of COVID-19 associated Pneumonia based on Superpixels with deep learning and chest CT
    • Authors: Tetila, E. C.; Bressem, K. K.; Astolfi, G.; Sant’Ana, D. A.; Pache, M. C. B.; Wirti Junior, G.; Barbedo, J. G. A.; Pistori, H.
    • Journal: Observatorio de la Economía Latinoamericana
    • Year: 2023
  5. Desenvolvimento de uma plataforma web para sensoriamento remoto com VANT
    • Authors: Terenciani, Marcelo Figueiredo; Tetila, Everton Castelão; da Silva, Igor Donatti Gonçalves; Tetila, Juliana Queiroz da Silva; Barbedo, Jayme Garcia Arnal
    • Journal: Observatorio de la Economía Latinoamericana
    • Year: 2023
  6. Um sistema de visão computacional para reconhecimento de doenças da soja usando VANTs: resultados preliminares
    • Authors: Tetila, E. C.; Machado, B. B.; Silva, G. G.; Pistori, H.; Belete, N. A. S.; Tetila, J. Q. S.; Barbedo, J. G. A.
    • Journal: Revista Caribeña de Ciencias Sociales
    • Year: 2023
  7. An approach for applying natural language processing to image classification problems
    • Authors: Astolfi, Gilberto; Sant’Ana, Diego André; Porto, João Vitor de Andrade; Rezende, Fábio Prestes Cesar; Tetila, Everton Castelão; Matsubara, Edson Takashi; Pistori, Hemerson
    • Journal: Neurocomputing
    • Year: 2022
  8. Combining Syntactic Methods With LSTM to Classify Soybean Aerial Images
    • Authors: Astolfi, Gilberto; Pache, Marcio Carneiro Brito; Menezes, Geazy Vilharva; Oliveira Junior, Adair da Silva; Menezes, Gabriel Kirsten; Weber, Vanessa Aparecida de Moares; Castelao Tetila, Everton; Belete, Nicolas Alessandro de Souza; Matsubara, Edson Takashi; Pistori, Hemerson
    • Journal: IEEE Geoscience and Remote Sensing Letters
    • Year: 2021