Woosik Lee | Computer Science | Research Excellence Award

Published on 22/12/202522/12/2025 by World Top Scientists

Dr. Woosik Lee | Computer Science | Research Excellence Award

Korea Social Security Information Service | South Korea

Dr. Woosik Lee is a researcher at the Research Center of the Korea Social Security Information Service, specializing in wireless sensor networks, Internet of Things systems, and data-driven intelligent services. He holds advanced degrees in computer science with a focus on networked systems, sensor technologies, and intelligent algorithms. His professional experience spans academic, governmental, and international research environments, including faculty service, visiting research appointments, and leadership roles in applied research projects addressing healthcare monitoring, intelligent transportation, and social welfare analytics. His research focuses on low-power communication protocols, neighbor discovery mechanisms, wireless body sensor networks, human monitoring systems, and machine learning–based social welfare applications. He has authored numerous peer-reviewed journal articles and conference contributions, demonstrating sustained scholarly impact and interdisciplinary relevance. His work integrates theoretical modeling, protocol design, simulation, and real-world system implementation, contributing to both academic advancement and societal benefit. Dr. Lee’s research excellence has been recognized through competitive awards and sustained citation impact, highlighting his growing influence and strong potential for continued leadership in intelligent networked systems research.

Citation Metrics (Scopus)

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140

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Featured Publications

Asymmetric Wake-up Scheduling Based on Block Designs for Internet of Things

– Ad Hoc Networks, 2024

Analysis of a Power-Saving MAC Protocol in Smart Intelligence Systems

– ICIC Express Letters, 2020

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

Published on 04/12/202504/12/2025 by World Top Scientists

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.

Hiyam Farhat | Digital twins | Best Researcher Award

Published on 18/11/202518/11/2025 by World Top Scientists

Dr. Hiyam Farhat | Digital twins | Best Researcher Award

Lecturer | Tennessee Tech University | United States

Dr. Hiyam Farhat, a Lecturer and Assistant Director at the DOE Industrial Assessment Center in the Department of Mechanical and Nuclear Engineering at Tennessee Technological University, is a materials and mechanical engineering specialist whose work integrates advanced materials, manufacturing technologies, turbomachinery performance, and energy-efficiency research. She holds a PhD in Mechanical and Industrial Engineering, an MS in Mechanical and Materials Engineering, and a BS in Mechanical Engineering, underpinning a career that spans academic, research, and leadership roles across major engineering organizations. Her professional experience includes directing industrial assessment initiatives, managing engineering programs in the turbomachinery sector, contributing to quality and inspection systems, and teaching a broad range of engineering courses with demonstrated excellence. Her research focuses on AI-driven modeling, digital-twin development, materials degradation prediction, and clean-energy technologies, resulting in influential publications in areas such as hybrid digital-twin frameworks, gas turbine performance, flexible operation lifing criteria, and energy-storage applications. She has delivered invited presentations and contributed chapters to leading technical references, with her work supported by collaborations with national and international partners. Her recognitions include awards for technical presentations, and she maintains active engagement through memberships in professional societies such as ASME, KEEN, and the European Turbine Network. She also holds certifications in research ethics, nondestructive testing, welding inspection, quality auditing, and safety oversight. Dr. Farhat’s record reflects sustained innovation, cross-disciplinary expertise, and impactful contributions to advancing energy sustainability and intelligent engineering systems.

Profiles: Google Scholar | Scopus

Featured Publications

1. Farhat, H., & Salvini, C. (2022). Novel gas turbine challenges to support the clean energy transition. Energies, 15(15), 5474.

2. Farhat, H. (2021). Operation, maintenance, and repair of land-based gas turbines.

3. Farhat, H. (2021). Materials and coating technologies. In Operation, maintenance, and repair of land-based gas turbines (pp. 63–87).

4. Farhat, H., & Salvini, C. (2022). New lifing criterion for land-based gas turbines in flexible operation mode. Energy Reports, 8, 379–385.

5. Farhat, H. (2021). Lifetime extension: Assessment and considerations. In Operation, maintenance, and repair of land-based gas turbines (pp. 175–196).

Dr. Hiyam Farhat’s work advances intelligent energy systems by integrating AI-driven modeling, digital-twin technologies, and materials degradation analytics to enhance performance, reliability, and sustainability in turbomachinery and clean-energy applications. Her contributions support industry and national energy goals by improving efficiency, reducing emissions, and enabling data-informed lifecycle management for next-generation power systems.

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

Published on 15/11/202515/11/2025 by World Top Scientists

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

Lecturer | Osun State University | Nigeria

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.

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.

Zbigniew Ras | Recommender Systems | Best Researcher Award

Published on 07/08/202507/08/2025 by World Top Scientists

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.

Xiaoxu Liu | Engineering | Best Researcher Award

Published on 24/05/202524/05/2025 by World Top Scientists

Dr. Xiaoxu Liu | Engineering | Best Researcher Award

Associate Professor at Shenzhen Technology University, China

Dr. Xiaoxu Liu is an accomplished Associate Professor at the Sino-German College of Intelligent Manufacturing, Shenzhen Technology University. He holds a Ph.D. in Electrical Engineering from the University of Northumbria and specializes in robust fault diagnosis, fault-tolerant control, stochastic systems, and multi-agent systems. Dr. Liu has published extensively in top-tier journals such as IEEE Transactions on Industrial Electronics and Automatica, and has served as Associate Editor for IEEE Transactions on Industrial Informatics. He has led multiple nationally funded research projects, securing over 3 million RMB in grants. His work integrates control theory with data-driven methods, addressing challenges in cyber-physical systems. Recognized as a Shenzhen Overseas High-level Talent, he has received numerous awards for research excellence and student mentorship. With international research experience and significant editorial contributions, Dr. Liu is a prominent figure in intelligent systems and control, demonstrating both academic leadership and impactful research contributions.

Professional Profile

Scopus Profile

Education

Dr. Xiaoxu Liu possesses a strong and progressive academic background in engineering and applied mathematics. He earned his Ph.D. in Electrical Engineering from the University of Northumbria in the UK (2014–2018), where he specialized in fault-tolerant control systems and robust estimation. Prior to this, he completed a Master’s degree in Operations Research and Cybernetics at Northeastern University (2012–2014), and a Bachelor’s degree in Information and Computing Science at the same university (2008–2012). His educational path reflects a solid foundation in both theoretical and applied aspects of control systems, cybernetics, and intelligent systems. This combination of mathematical rigor and engineering application has laid the groundwork for his interdisciplinary research approach. His international academic journey has also helped him build a global perspective and a collaborative mindset, both of which have been instrumental in his subsequent professional and research achievements.

Professional Experience

Dr. Xiaoxu Liu has built an impressive academic and research career marked by rapid progression and leadership. Since December 2021, he has served as an Associate Professor at the Sino-German College of Intelligent Manufacturing, Shenzhen Technology University. Before that, he was an Assistant Professor at the same institution from 2018 to 2021. He also held research and teaching positions internationally, including as a Research Associate at the Faculty of Mathematics, City University of Hong Kong, and as a Lecturer at the University of Northumbria. Throughout these roles, Dr. Liu has led cutting-edge research projects, mentored students, and contributed to institutional development. He has acted as the principal investigator for numerous funded research programs, reflecting his capacity to lead independently and strategically. His experience demonstrates not only academic proficiency but also a sustained commitment to advancing intelligent systems research and fostering interdisciplinary collaboration in both teaching and applied engineering contexts.

Research Interest

Dr. Xiaoxu Liu’s research spans several high-impact areas within intelligent systems and control engineering. His primary interests include robust fault diagnosis, fault-tolerant control, stochastic nonlinear systems, and multi-agent systems. He also ocuses on cyber-physical systems and data-driven control, areas highly relevant to Industry 4.0 and autonomous system applications. Dr. Liu’s work often combines theoretical rigor with practical relevance, leveraging modern tools like deep reinforcement learning and Takagi-Sugeno fuzzy models to address real-world challenges such as actuator faults in UAVs or wind turbine resilience. His interdisciplinary approach blends classical control theory with artificial intelligence, enhancing system adaptability and reliability. His research outputs—published in top-tier journals like IEEE Transactions on Industrial Electronics—demonstrate not only novelty but also applicability to emerging technologies. Dr. Liu’s ability to connect robust theory with practical implementations positions him as a thought leader in intelligent manufacturing and autonomous system control.

ward and Honor

Dr. Xiaoxu Liu has received multiple awards that recognize his research excellence, academic leadership, and contributions to engineering education. He was honored as a Shenzhen Overseas High-level Talent in 2019, highlighting his strategic value to China’s academic and technological development. He has earned several Best Paper and Best Presentation Awards from prestigious conferences and journals, such as the IEEE Industrial Electronics Society and Processes. Dr. Liu also received the IEEE IES Student Paper Travel Award and various recognitions for his mentorship of student teams who achieved national-level prizes in robotics and circuit design competitions. These accolades underscore both the quality and impact of his scholarly work and his dedication to student development. His involvement as an Associate Editor for IEEE Transactions on Industrial Informatics and reviewer for top IEEE journals further validates his status as a trusted expert in his field. These honors collectively reflect his rising prominence in the global research community.

Conclusion

In summary, Dr. Xiaoxu Liu stands out as a highly capable and accomplished researcher in the field of intelligent control systems. With a solid educational foundation, diverse professional experience across top institutions, and a research portfolio that blends theoretical innovation with real-world application, he exemplifies academic excellence. His focus on robust fault diagnosis, resilient control systems, and data-driven approaches addresses some of the most pressing challenges in cyber-physical systems and smart manufacturing. Recognized nationally and internationally through numerous awards, editorial roles, and funded projects, Dr. Liu has established himself as a leader in his domain. He continues to advance the field through impactful publications, student mentorship, and collaborative projects. His trajectory reflects not only technical expertise but also a broader commitment to scientific progress and educational excellence. As such, Dr. Liu is highly deserving of recognition through accolades such as the Best Researcher Award.

Publications Top Notes

Title: Joint Observer Based Fault Tolerant Control for Discrete-Time Takagi-Sugeno Fuzzy Systems With Immeasurable Premise Variables
- Authors: Xiaoxu Liu, Risheng Li, Zhiwei Gao, Bowen Li, Tan Zhang
- Year: 2025
Title: Multiagent Formation Control and Dynamic Obstacle Avoidance Based on Deep Reinforcement Learning
- Authors: Zike Yuan, Chenhao Yao, Xiaoxu Liu, Zhiwei Gao, Wenwei Zhang
- Year: 2025
Title: Fault Estimation for Cyber–Physical Systems with Intermittent Measurement Transmissions via a Hybrid Observer Approach
- Authors: Jingjing Yan, Chao Deng, Weiwei Che, Xiaoxu Liu
- Year: 2024
- Citations: 5
Title: Reinforcement Learning-Based Fault-Tolerant Control for Quadrotor UAVs Under Actuator Fault
- Authors: Xiaoxu Liu, Zike Yuan, Zhiwei Gao, Wenwei Zhang
- Year: 2024
- Citations: 12

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

Published on 19/10/2024 by World Top Scientists

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.

Josiah Lebakeng | Intelligence | Best Research Article Award

Published on 14/10/202414/10/2024 by World Top Scientists

Prof. Josiah Lebakeng | Intelligence | Best Research Article Award

Professor, Thabo Mbeki African School of Public and International Affairs, South Africa

Teboho Josiah Lebakeng is a distinguished Professor at the Thabo Mbeki African School of Public and International Affairs, UNISA, in South Africa. He specializes in Strategic Intelligence and Human Security, imparting knowledge on statecraft, intelligence gathering, analysis, and governance. Prior to his current role, he lectured in sociology and research methodology at the University of Limpopo and had teaching appointments at both Vista University (now University of Johannesburg) and the University of Pretoria. 🌍📚

Publication Profile

ORCID

Education

Professor Lebakeng holds a PhD in Sociology from the University of Limpopo, an MSc in Human Services from Springfield College, an MA in Sociology from the University of Dar es Salaam, and a BA in Sociology from The American University in Cairo. His academic journey reflects a strong foundation in social sciences and research methodologies. 🎓

Experience

His professional journey includes significant roles in the South African State Security Agency, where he served as Manager of Production and Strategic Research and Analysis, and as a Senior Regional Analyst. Additionally, he was seconded as Political Counsellor at South Africa’s Permanent Mission to the UN in New York and led the SADC Preventative Mission in Lesotho. He has extensive experience engaging with international intelligence services. 🔍

Research Focus

Professor Lebakeng’s research interests encompass Strategic Intelligence, Legislative Oversight, and African Epistemology. He is committed to advancing knowledge in these fields, emphasizing the importance of human security and good governance in contemporary society. 📖🔐

Awards and Honors

He has received recognition for his contributions to academia and intelligence, including various awards related to his scholarly work and his autobiography, “They Blunted Us: June 16, Exile and Homecoming,” published by Ziable Publisher in 2021. 🏆📖

Publication Top Notes

Policy sciences and the quest for human security in Africa (Journal of Public Administration, 2023)

The nature and issues in intelligence, with reference to the South African civilian intelligence services (African Security Review, 2023)

Lebakeng, T.J. & Matebese-Notshulwana, K.M. (2023). Doctoral Reflections of Journeys in the Humanities and Social Sciences in South African Universities (Ziable Publishers).

Repurposing the university in Africa in the context of the tenacity of an explicitly racist epistemology in Ndofirepi, A. P., Vurayai, S., and Erima, G. (Eds.). Unyoking African University Knowledge: A Pursuit of the Decolonial Agenda (Brill, 2023).

Niansong Mei | microelectronics | Best Researcher Award

Published on 08/10/202408/10/2024 by World Top Scientists

Assoc Prof. Niansong Mei | microelectronics | Best Researcher Award

Prof, Shanghai Advanced Research Institute, Chinese Academy of Sciences, China

Niansong Mei is an accomplished Associate Professor at the Shanghai Advanced Research Institute, Chinese Academy of Sciences. With a strong foundation in microelectronics, he has significantly contributed to the fields of high-performance integrated circuits and hardware security. 🌟

Publication Profile

Google Scholar

Education

Niansong received his B.S. degree in Physical Science and Technology from Soochow University, China, in 2001. He furthered his education with an M.S. degree in Microelectronics from Southeast University, China, in 2004, and completed his Ph.D. in Microelectronics at Fudan University, China, in 2011. 🎓

Experience

After earning his Ph.D., Niansong joined the Shanghai Advanced Research Institute, Chinese Academy of Sciences, as an Associate Professor. Prior to this, he served as a group leader at Semiconductor Manufacturing International Corporation (SMIC) from 2004 to 2008, where he gained valuable industry experience. 🏢

Research Focus

His research interests encompass high-performance integrated circuits and systems, hardware security, and blockchain technology. Niansong aims to advance the state of the art in these critical areas through innovative research. 🔍

Awards and Honours

Niansong has received various accolades for his contributions to the field, reflecting his commitment to excellence in research and education. 🏆

Publication Top Notes

Vaq-based tri-level switching scheme for SAR ADC

A 920-MHz dual-mode receiver with energy harvesting for UHF RFID tag and IoT

A review of converter circuits for ambient micro energy harvesting

A 16.4 nW, sub-1 V, resistor-less voltage reference with BJT voltage divider

CMOS high linearity PA driver with an on-chip transformer for W-CDMA application

Yusuf KARADEDE | Artificial Intelligence | Best Researcher Award

Published on 25/08/202425/08/2024 by World Top Scientists

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.