Oluwatobi Adedamola Ayilara-Adewale | Artificial Intelligence | Editorial Board Member

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Dr. Oluwatobi Adedamola Ayilara-Adewale | Artificial Intelligence | Editorial Board Member

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

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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.

 

Hanane Thamik | Artificial Intelligence | Best Researcher Award

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Dr. Hanane Thamik | Artificial Intelligence | Best Researcher Award

Associate Professor at Renmin University of China | China

Dr. Hanane Thamik is a distinguished academic and researcher whose career reflects an exceptional blend of scholarly excellence, global exposure, and social commitment. With advanced qualifications in e-commerce, international management, audit, and governance, she has complemented her academic journey with training in diplomacy and multicultural studies. Her research spans vital areas including artificial intelligence, sustainable development, digital transformation, social capital, and cultural heritage, with publications in respected international journals and contributions to global platforms such as the United Nations. Beyond academia, she has served as a writer, associate professor, and active participant in international forums, demonstrating her ability to bridge research with practice. Multilingual and versatile, she has engaged in projects linking Africa, China, and Europe, highlighting her commitment to cross-cultural understanding and collaboration. Her work embodies perseverance, innovation, and responsibility, positioning her as a role model and a strong candidate for recognition as an outstanding researcher.

Professional Profile 

Google Scholar | Scopus Profile

Education

Dr. Hanane Thamik has pursued a broad and impressive educational journey marked by international exposure and multidisciplinary focus. She completed her PhD in E-Commerce at Wuhan University, building on earlier academic foundations in International MBA studies, Audit and Governance, and a Bachelor’s degree in Economics and Management. Alongside her core academic studies, she enriched her expertise with training in diplomacy at the United Nations in Geneva and the European Academy of Diplomacy in Poland. She also dedicated significant effort to language learning, achieving proficiency in Chinese, Japanese, French, English, Spanish, Turkish, and Russian, which enables her to navigate diverse research and cultural contexts effectively. Technical skills in finance, taxation, accounting, project management, and advanced data analysis tools such as STATA and SPSS further strengthen her academic profile. Her diverse education reflects not only intellectual rigor but also her commitment to interdisciplinary knowledge, equipping her to engage meaningfully in global academic and policy discussions.

Experience

Dr. Hanane Thamik has accumulated extensive professional experience that bridges academia, policy, and international cooperation. She is currently serving as an Associate Professor and Researcher at Renmin University of China, where she contributes to teaching, mentorship, and impactful research. Her career also includes active participation in international political and social initiatives, such as her involvement as a Political Member of the Moroccan National Rally of Independents and as an International Patriotic Volunteer at the United Nations Human Rights Council in Geneva. Her professional journey extends to journalism and writing, with published work in Canadian and African media outlets, as well as a prior role as a business representative facilitating Sino-Moroccan cooperation. She has also delivered speeches at significant platforms including the UN Human Rights Council. This combination of academic, diplomatic, and cross-sectoral experience underlines her versatility and her ability to translate research into practice while addressing global challenges with a multidisciplinary approach.

Research Focus

Dr. Hanane Thamik’s research focuses on critical themes at the intersection of technology, society, and sustainable development. Her scholarly work explores the impact of artificial intelligence, digital transformation, and e-commerce on global economic systems, with particular emphasis on how these innovations support the United Nations Sustainable Development Goals. She also investigates cross-cultural and transnational perspectives, such as African student mobility to China, Sino-African trade relations, and the role of digital infrastructure in fostering international cooperation. Beyond technology and economics, her research extends into cultural heritage and governance, reflecting a holistic interest in the interplay between development, policy, and cultural identity. Her ability to produce interdisciplinary scholarship, published in peer-reviewed journals and leading platforms, demonstrates a balance between academic depth and applied relevance. By addressing both global and regional challenges, she has established herself as a researcher whose work contributes to advancing knowledge while fostering collaboration across societies and sectors.

Award and Honor

Dr. Hanane Thamik has earned multiple awards and recognitions that reflect her leadership, academic excellence, and contributions to global dialogue. She has represented international organizations at the United Nations, including the Commission on the Status of Women in New York, and has been selected as an International Youth Representative for the International Youth Water Forum organized by UNESCO and Wuhan University. Her recognition as a Youth African Leader in the China-Europe-Africa project and her selection in the Youth Development Leaders Cultivation program highlight her role in shaping cross-continental collaboration. She has also been honored for her achievements in Chinese language and culture, winning second prize in the “My Wuhan University Story” competition. These honors underscore her ability to combine academic research with cross-cultural engagement and public service. Collectively, they position her not only as an accomplished researcher but also as an influential figure in fostering dialogue, sustainability, and international cooperation.

Publication Top Notes

  • Title: The impact of artificial intelligence on sustainable development in electronic markets
    Year: 2022
    Citations: 55

  • Title: The digital paradigm: unraveling the impact of artificial intelligence and internet of things on achieving sustainable development goals
    Year: 2024
    Citations: 11

  • Title: African students’ mobility to China: An ecological systematic perspective
    Year: 2022
    Citations: 6

  • Title: Purchase decision-making process using social capital: moderating effect of trustworthiness
    Year: 2020
    Citations: 5

Conclusion

Dr. Hanane Thamik’s publications reflect a strong and evolving research trajectory, with a focus on artificial intelligence, sustainable development, digital transformation, social capital, and cross-cultural perspectives. Her work has gained recognition through citations, showing both academic impact and relevance to global challenges. From exploring the role of AI in electronic markets to analyzing African student mobility and decision-making processes, her contributions demonstrate both depth and diversity. The consistent growth in her research output and collaborations highlights her commitment to advancing knowledge that bridges technology, society, and policy. Overall, her scholarly record positions her as an impactful and promising researcher with global influence.

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.

Mian Usman Sattar | Artificial Intelligence | Best Researcher Award

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Dr. Mian Usman Sattar | Artificial Intelligence | Best Researcher Award

Lecturer at University of Derby, United Kingdom

Dr. Mian Usman Sattar is an accomplished academic and researcher specializing in information systems, business intelligence, and data analytics, with extensive teaching and leadership experience across universities in the United Kingdom, Malaysia, and Pakistan. He has led innovative academic programs, introduced contemporary specialization tracks, and integrated emerging technologies into curricula. His research achievements are supported by multiple prestigious national and international grants, reflecting both expertise and the trust of funding bodies. As a program leader, department chair, and cluster head, he has demonstrated strong leadership in shaping academic directions and fostering institutional collaborations. His expertise spans artificial intelligence for business, data-driven marketing, enterprise systems, and big data analytics, complemented by a track record of academic honors and recognition as an approved PhD supervisor. Through his global exposure, research contributions, and commitment to advancing knowledge, Dr. Sattar has significantly impacted academia and industry, making him a distinguished figure in his field.

Professional Profile 

Google Scholar | Scopus Profile

Education

Dr Mian Usman Sattar holds a diverse and robust academic background, reflecting his dedication to continuous learning and specialization in technology and business domains. He earned his PhD in Informatics from the Malaysian University of Science and Technology, focusing on advanced aspects of information systems and analytics. His postgraduate qualifications include an MS in IT Management from the University of Sunderland, postgraduate diplomas in computer science and communication & computer technology, and an MSc in Computer Science from Government College University, Lahore. His academic progression demonstrates a steady advancement from foundational computer science knowledge to applied IT management and specialized research in informatics. Currently, he is pursuing a Postgraduate Certificate leading to FHEA from the University of Derby, reflecting his commitment to enhancing teaching and academic leadership. This diverse educational portfolio has equipped him with a strong blend of technical expertise, managerial insight, and pedagogical skills essential for his academic and research pursuits.

Experience

Dr. Mian Usman Sattar has an extensive career spanning academia, research leadership, and industry roles in the United Kingdom, Pakistan, and Malaysia. He is currently a Lecturer and Program Leader in Information Technology at the University of Derby, where he oversees academic programs and fosters student engagement. His previous academic roles include Assistant Professor positions at Beaconhouse National University and the University of Management and Technology, where he led academic clusters, introduced new specialization tracks, and managed industry collaborations. Beyond academia, he has held managerial and technical roles such as Deputy Manager (MIS) and Assistant Network Administrator, as well as leadership in training and consultancy for information security. Throughout his career, he has taught a wide range of subjects including business analytics, artificial intelligence for business, enterprise resource planning, and data-driven marketing. His experience reflects a blend of teaching, research supervision, academic program development, and practical industry engagement across multiple disciplines and sectors.

Research Focus

Dr. Mian Usman Sattar’s research centers on business intelligence, data analytics, enterprise systems, and information security, with a strong emphasis on integrating disruptive technologies into organizational and educational contexts. His work explores the use of artificial intelligence, machine learning, and big data analytics to enhance business decision-making and operational efficiency. He is particularly interested in the application of data-driven strategies in marketing, enterprise resource planning, and digital transformation. His research approach is both academic and applied, aiming to bridge the gap between theory and real-world implementation. By leading and participating in funded research projects, he has contributed to advancing knowledge in areas such as analytics governance, trust in digital systems, and emerging technologies for business competitiveness. His interdisciplinary focus enables collaboration across computing, engineering, and management fields, making his research relevant to both academia and industry. This focus reflects a commitment to innovation, problem-solving, and societal impact through technology-driven solutions.

Award and Honor

Dr. Mian Usman Sattar has earned multiple prestigious awards and honors that underscore his research excellence, academic leadership, and professional contributions. He received a PhD Fellowship from the Malaysian University of Science and Technology, recognizing his academic potential and research capability. His work has been supported by competitive grants from organizations such as the Pakistan Science Foundation, Malaysia Digital Economy Corporation, Malaysia Toray Science Foundation, and TWAS-COMSTECH, totaling significant funding for technology-driven research projects. He was awarded a travel grant by the Higher Education Commission of Pakistan to present his research internationally, reflecting recognition from the national academic community. Additionally, he holds the distinction of being an HEC Approved PhD Supervisor, affirming his capability to guide doctoral-level research. These achievements demonstrate his ability to secure funding, contribute to high-impact projects, and earn recognition for his scholarly and professional excellence at both national and international levels.

Publications Top Notes

  • Title: Predicting student performance in higher educational institutions using video learning analytics and data mining techniques
    Authors: R Hasan, S Palaniappan, S Mahmood, A Abbas, KU Sarker, MU Sattar
    Year: 2020
    Citations: 236

  • Title: Effects of virtual reality training on medical students’ learning motivation and competency
    Authors: MU Sattar, S Palaniappan, A Lokman, A Hassan, N Shah, Z Riaz
    Year: 2019
    Citations: 167

  • Title: Motivating medical students using virtual reality based education
    Authors: M Sattar, S Palaniappan, A Lokman, N Shah, U Khalid, R Hasan
    Year: 2020
    Citations: 148

  • Title: Whole-genome sequencing as a first-tier diagnostic framework for rare genetic diseases
    Authors: H Nisar, B Wajid, S Shahid, F Anwar, I Wajid, A Khatoon, MU Sattar, …
    Year: 2021
    Citations: 30

  • Title: An efficient computer vision-based approach for acute lymphoblastic leukemia prediction
    Authors: A Almadhor, U Sattar, A Al Hejaili, U Ghulam Mohammad, U Tariq, …
    Year: 2022
    Citations: 26

  • Title: Validation method for digital flow meter for fuel vendors
    Authors: P Megantoro, DA Husnan, MU Sattar, A Maseleno, O Tanane
    Year: 2020
    Citations: 19

  • Title: A review: Emerging trends of big data in higher educational institutions
    Authors: R Hasan, S Palaniappan, S Mahmood, VR Naidu, A Agarwal, B Singh, …
    Year: 2020
    Citations: 17

  • Title: Design of laboratory scale fluid level measurement device based on arduino
    Authors: NF Apsari, P Megantoro, MU Sattar, A Maseleno, O Tanane
    Year: 2020
    Citations: 12

  • Title: User experience design in virtual reality medical training application
    Authors: MU Sattar, S Palaniappan, A Lokman, N Shah, Z Riaz, U Khalid
    Year: 2021
    Citations: 11

  • Title: Multi-stage intelligent smart lockdown using sir model to control covid 19
    Authors: A Ghaffar, S Alanazi, M Alruwaili, MU Sattar, W Ali, M Humayun, …
    Year: 2021
    Citations: 10

  • Title: Arduino-based digital advanced audiometer
    Authors: NH Wijaya, M Ibrahim, N Shahu, MU Sattar
    Year: 2021
    Citations: 10

  • Title: Block-chain-security advancement in medical sector for sharing medical records
    Authors: R Abid, B Aslam, M Rizwan, F Ahmad, MU Sattar
    Year: 2019
    Citations: 10

  • Title: Customer Satisfaction Affects the Customer Loyalty: Evidence from Telecommunication Sector in Pakistan
    Authors: MU Sattar, B Sattar
    Year: 2012
    Citations: 10

  • Title: eDify: Enhancing Teaching and Learning Process by Using Video Streaming Server
    Authors: R Hasan, S Palaniappan, S Mahmood, KU Sarker, MU Sattar, A Abbas, …
    Year: 2021
    Citations: 9

  • Title: Intelligent digital twin to make robot learn the assembly process through deep learning
    Authors: B Ahmad
    Year: 2021
    Citations: 9

Conclusion

The publication record of Dr. Mian Usman Sattar reflects a strong and diverse research portfolio with impactful contributions in education technology, virtual reality in medical training, artificial intelligence applications, data analytics, and biomedical research. Several of his works, particularly those on predicting student performance and virtual reality in education, have received significant citation counts, indicating strong relevance and recognition in the academic community. His collaborations span across interdisciplinary fields, integrating computing, engineering, healthcare, and business domains, which enhances the applicability and reach of his research. The steady stream of publications in reputable journals and conferences, coupled with high-impact studies, demonstrates his ability to address current challenges with innovative, technology-driven solutions. Overall, the breadth, depth, and influence of his research output position him as a noteworthy and influential scholar whose work continues to contribute meaningfully to academia and industry alike.

Zbigniew Ras | Recommender Systems | Best Researcher Award

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Dr. Zbigniew Ras | Recommender Systems | Best Researcher Award

Professor of Computer Science & KDD Lab Director at University of North Carolina at Charlotte, United States

Zbigniew W. Ras is a distinguished computer scientist renowned for his extensive contributions to artificial intelligence, data mining, and intelligent information systems. With a career spanning multiple decades, he has held professorships and research positions at leading institutions in the United States, Europe, and Asia. His research interests span a broad range of interdisciplinary areas, including sentiment analysis, medical informatics, music information retrieval, and recommender systems. He serves as Editor-in-Chief of the Journal of Intelligent Information Systems and has been a pivotal figure in various international academic boards and conference steering committees. Recognized for both his research and teaching, he has received numerous awards and honors, including inclusion in the global list of top scientists. His leadership extends beyond academia through advisory roles in global AI organizations and think tanks. Ras’s work reflects a rare blend of theoretical depth, innovative application, and commitment to the advancement of both knowledge and academic communities.

Professional Profile 

Google Scholar | Scopus Profile

Education

Zbigniew W. Ras has a rich and internationally respected academic background rooted in mathematics and computer science. He earned his M.S. in Mathematics and Ph.D. in Computer Science from the University of Warsaw, Poland. His academic journey advanced further with the prestigious D.Sc. (Habilitation) from the Polish Academy of Sciences, which marks a high level of scholarly independence and achievement in European academia. His accomplishments were further recognized when he was awarded the National Professorship Title by the President of Poland—one of the highest honors in the Polish academic system. This educational foundation not only highlights his expertise in formal systems and computation but also reflects a rigorous and progressive development of academic excellence. His training under globally respected mathematicians and computer scientists helped shape a career focused on both theoretical innovation and practical application in emerging areas of artificial intelligence, making him a well-rounded and influential academic figure.

Experience

Zbigniew W. Ras has accumulated a distinguished career in academia and research, with extensive international experience. He has been a professor at the University of North Carolina at Charlotte for several decades, where he also held leadership and mentoring roles. His experience includes appointments at the Polish-Japanese Academy of Information Technology, Warsaw University of Technology, and the Polish Academy of Sciences, where he contributed to both research and academic development. Ras has also held visiting professorships at respected institutions across Europe, North America, and Asia, including in Germany, Sweden, Spain, Italy, and Japan. Beyond academia, he has collaborated with industry through advisory roles with organizations in the United States, Switzerland, and Australia. His participation in international advisory boards and departmental councils reflects a strong commitment to institutional leadership. This wide-ranging experience underlines his global academic presence, multidisciplinary engagement, and capacity to foster international research collaboration and innovation.

Research Focus

Zbigniew W. Ras’s research encompasses a broad spectrum of topics within artificial intelligence and intelligent information systems. His work primarily focuses on data mining, granular computing, sentiment analysis, recommender systems, and actionability in decision-making processes. He has also explored emerging areas like music information retrieval, business and art analytics, and medical informatics, showcasing a commitment to applying AI methods across various domains. His research is characterized by a strong theoretical foundation coupled with practical applications, which has made significant contributions to fields such as flexible query answering and algebraic logic. Ras emphasizes the importance of actionable knowledge, striving to ensure that the outcomes of machine learning and data analysis can be effectively used in real-world decision contexts. His interdisciplinary focus demonstrates both depth and adaptability, enabling his work to impact diverse sectors including healthcare, education, cultural preservation, and enterprise intelligence, all while pushing the boundaries of computational and information sciences.

Award and Honor

Zbigniew W. Ras has received numerous awards and honors that reflect his excellence in both research and teaching. He was named among the world’s top 2% scientists in a list compiled by Stanford University and Elsevier, underscoring his global academic impact. He has received several institutional awards, including best paper honors and team achievement recognitions from Warsaw University of Technology. At the University of North Carolina at Charlotte, he was honored with multiple awards for outstanding faculty performance and mentorship, such as the Harshini V. de Silva Graduate Mentor Award. In addition, he was recognized as a finalist for major teaching excellence awards. Ras is also a Distinguished Fellow of the Kosciuszko Foundation’s Collegium of Eminent Scientists. His leadership roles include chairing and serving on advisory boards of several major academic conferences and societies, illustrating his influence within the international research community. These honors collectively affirm his sustained academic excellence and global recognition.

Publications Top Notes

  • Title: Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics): Preface
    Authors: M Dorigo, M Birattari, GA Di Caro, R Doursat, AP Engelbrecht, D Floreano, ZW Ras, et al.
    Year: 2010
    Citations: 280

  • Title: Action-rules: How to increase profit of a company
    Authors: ZW Ras, A Wieczorkowska
    Year: 2000
    Citations: 256

  • Title: Multi-label classification of emotions in music
    Authors: A Wieczorkowska, P Synak, ZW Ras
    Year: 2006
    Citations: 175

  • Title: Association action rules
    Authors: ZW Ras, A Dardzinska, LS Tsay, H Wasyluk
    Year: 2008
    Citations: 105

  • Title: Action rules discovery: system DEAR2, method and experiments
    Authors: LS Tsay, ZW Ras
    Year: 2005
    Citations: 96

  • Title: The Wisdom Web: New Challenges for Web Intelligence (WI)
    Authors: J Liu, N Zhong, Y Yao, ZW Ras
    Year: 2003
    Citations: 95

  • Title: Action rules mining
    Authors: AA Tzacheva, ZW Ras
    Year: 2005
    Citations: 86

  • Title: ARAS: Action rules discovery based on agglomerative strategy
    Authors: ZW Ras, E Wyrzykowska, H Wasyluk
    Year: 2007
    Citations: 83

  • Title: Extracting emotions from music data
    Authors: A Wieczorkowska, P Synak, R Lewis, ZW Ras
    Year: 2005
    Citations: 80

  • Title: Discovering extended action-rules (System DEAR)
    Authors: ZW Ras, LS Tsay
    Year: 2003
    Citations: 80

  • Title: Foundations of Intelligent Systems
    Authors: ZW Ras, A Skowron
    Year: 1999
    Citations: 72

  • Title: Action rule extraction from a decision table: ARED
    Authors: S Im, ZW Ras
    Year: 2008
    Citations: 67

  • Title: Advances in Music Information Retrieval
    Authors: Z Ras, A Wieczorkowska
    Year: 2010
    Citations: 64

  • Title: How to support consensus reaching using action rules: a novel approach
    Authors: J Kacprzyk, S Zadrozny, ZW Ras
    Year: 2010
    Citations: 59

  • Title: Analysis of sound features for music timbre recognition
    Authors: X Zhang, ZW Ras
    Year: 2007
    Citations: 59

Conclusion

The publication record of Zbigniew W. Ras clearly demonstrates a sustained and impactful contribution to the fields of artificial intelligence, data mining, and intelligent information systems. His most cited works reveal a strong emphasis on action rule discovery, emotion analysis in music, and decision support systems—topics of continuing relevance in both academic and applied contexts. Collaborations with various researchers across countries and institutions also reflect his ability to work across disciplinary and cultural boundaries. The high citation counts of multiple papers show that his research has not only been influential but also foundational in shaping discussions and developments within the AI and data science communities. His scholarly output highlights both theoretical depth and practical innovation, underscoring his position as a thought leader in his domain. This consistent and wide-ranging academic influence positions him as a strong candidate for recognition through prestigious awards and honors in research excellence.

 

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.

Ritu Tanwar | Artificial intelligence | Best Researcher Award

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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.

Yusuf KARADEDE | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Yusuf KARADEDE | Artificial Intelligence | Best Researcher Award

Doctor, Gaziantep Islam Science and Technology University, Faculty of Engineering and Natural Sciences, Department of Industrial Engineering, 27010 Gaziantep, Turkey

Profile

Scopus

Strengths for the Award

Dr. Yusuf Karadede’s research in stochastic processes, heuristic algorithms, and stochastic optimization underscores his deep expertise and innovative approach in industrial engineering. His doctoral thesis and subsequent work have made significant contributions to the fields of simulation and stochastic modeling. Notably, his publications in esteemed journals like Soft Computing and Energy highlight his ability to tackle complex problems with advanced computational techniques.

Dr. Karadede’s diverse range of scientific activities demonstrates his commitment to advancing both theoretical and applied aspects of his field. His development of novel models such as the ProFiVaS model for financial indicators, showcased in his recent publication in Expert Systems with Applications, exemplifies his forward-thinking approach and impact on financial modeling.

Areas for Improvement

While Dr. Karadede’s research is highly impactful, expanding the scope of his research to include interdisciplinary approaches could further enhance the applicability of his work. For instance, integrating his stochastic models with emerging technologies like machine learning could offer new insights and broaden the impact of his research. Additionally, increasing collaboration with international research groups might provide new perspectives and enhance the global reach of his contributions.

Academic Background:

  • Bachelor’s Degree: Mathematics, Suleyman Demirel University, 2006-2010
  • Master’s Degree: Industrial Engineering, Suleyman Demirel University, 2011-2014
  • Doctorate (Ph.D.): Industrial Engineering, Suleyman Demirel University, 2015-2020

Professional Experience:

  • Kafkas University: Faculty of Engineering and Architecture, Department of Industrial Engineering (2014-2015)
  • Suleyman Demirel University: Faculty of Engineering, Department of Industrial Engineering (2015-2020)
  • Gaziantep Islam Science and Technology University: Department of Industrial Engineering (2020-Present)

Research Interests:

  • Stochastic Processes and Models
  • Simulation
  • Heuristic Algorithms
  • Stochastic Optimization

 Awards and Scholarships:

  • TÜBİTAK 2210-C Program Scholarship (2013-2014)
  • TÜBİTAK 2211-C Program Scholarship (2018-2020)

Publications Top Notes:

Karadede, Y., Özdemir, G. (2018). A hierarchical soft computing model for parameter estimation of curve-fitting problems. Soft Computing, 22(20), 6937-6964.

Karadede, Y., Ozdemir, G., Aydemir, E. (2017). Breeder Hybrid Algorithm Approach for Natural Gas Demand Forecasting Model. Energy, 141, 1269-1284.

Akdeniz, F., Biçil, M., Karadede, Y., Özbek, F. E., Özdemir, G. (2018). Application of real valued genetic algorithm on prediction of higher heating values of various lignocellulosic materials. Energy, 160, 1047-1054.

Karadede, Y. (2024). A novel stochastic ProFiVaS model based on decomposition of stochastic Vasicek differential equation for modeling and simulating financial indicators. Expert Systems with Applications

Conclusion

Dr. Yusuf Karadede’s distinguished research in stochastic processes and optimization positions him as a strong candidate for the Best Researcher Award. His innovative contributions, including high-impact publications and successful research projects funded by prestigious institutions like TÜBİTAK, highlight his significant achievements and potential for future breakthroughs. His work not only advances theoretical understanding but also offers practical solutions to real-world problems, making him a deserving nominee for this esteemed accolade.