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.

merve pınar | Machine Learning | Best Researcher Award

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Dr. merve pınar | Machine Learning | Best Researcher Award

Research Ass, Marmara University, Turkey

Merve Pinar is a Research Assistant in the Faculty of Technology, Computer Engineering Department at Marmara University, Turkey. She has been pursuing her doctorate since 2023 at Marmara University in the field of Computer Engineering. Her academic journey includes a postgraduate degree from the Institute for Graduate Studies in Pure and Applied Sciences (2019-2022) and an undergraduate degree from Çanakkale Onsekiz Mart University, where she studied Engineering (2009-2013). Merve’s work primarily focuses on artificial intelligence, machine learning, and their applications in various fields, especially healthcare. She is dedicated to exploring innovative solutions using deep learning and pattern recognition techniques. Her contributions to the academic community include publications in respected journals and conferences. She also actively collaborates with other researchers to advance the field.

Profile 

Education

  • Doctorate (2023-Present): Marmara University, Faculty of Technology, Computer Engineering, Turkey.
  • Postgraduate (2019-2022): Marmara University, Institute for Graduate Studies in Pure and Applied Sciences, Turkey. Dissertation: “Derinöğrenme yöntemleri kullanılarak beyin tümörü tiplerinin ve sınırlarının tahminlenmesi” (Prediction of brain tumor types and boundaries using deep learning methods).
  • Undergraduate (2009-2013): Çanakkale Onsekiz Mart University, Faculty of Engineering, Turkey.

Merve’s academic background provides a solid foundation in computer engineering, artificial intelligence, and data science. She continues to pursue advanced studies, focusing on leveraging machine learning and deep learning methods to address complex problems in health and technology.

Research Focus

Merve Pinar’s research focuses on the intersection of artificial intelligence, machine learning, and medical applications. Her primary interests are database management, data structures, pattern recognition, and deep learning. She specializes in using AI techniques for medical imaging, particularly in the classification and segmentation of brain tumor types using MRI and surgical microscope images. Her work aims to enhance diagnostic tools, improving the accuracy and efficiency of healthcare systems. Additionally, she is involved in hyperparameter optimization for big data applications, which helps improve recommendation systems. Merve’s interdisciplinary research is positioned at the cutting edge of AI, combining computer engineering with real-world applications, particularly in healthcare technology, where deep learning plays a crucial role in revolutionizing diagnostics and treatment strategies.

Publications

  • Deep Learning-Assisted Segmentation and Classification of Brain Tumor Types on Magnetic Resonance and Surgical Microscope Images 🧠💻 (2024)
  • Hyperparameter Optimization for Recommendation Systems with Big Data 📊🔍 (2017)

Álvaro Figueira | Artificial Intelligence | Best Paper Award

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Assist. Prof. Dr. Álvaro Figueira | Artificial Intelligence | Best Paper Award

Professor Auxiliar, FCUP – Universidade do Porto, Portugal

Profile

Orcid

Álvaro Figueira is a distinguished academic and researcher in the field of Computer Science, currently serving as a Professor (Prof. Auxiliar) at Universidade do Porto, Faculdade de Ciências in Portugal. With a robust academic background and extensive experience, his research focuses on data mining, machine learning, social network analysis, and eLearning. Figueira’s passion for technology and innovation is evident in his contribution to various scientific fields, including data visualization and text mining, where his work aims to bridge theory with practical applications. With years of experience in teaching and leading research initiatives, Figueira is a prominent figure in his discipline. 📚💻

Education

Álvaro Figueira’s academic journey is distinguished by his advanced qualifications in Computer Science. He obtained his Bachelor’s (BSc) degree from Universidade do Porto, followed by a Master’s (MSc) from Imperial College London. He continued his academic excellence by completing a Ph.D. at Universidade do Porto in 2004, where he focused on Computer Science. Additionally, Figueira pursued Post-Graduation in Business Intelligence and Analytics at Porto Business School in 2017, further enhancing his expertise. 🎓📖

Experience

Throughout his career, Álvaro Figueira has amassed a wealth of academic and professional experience. He is currently a Professor at Universidade do Porto, where he teaches and supervises students in the field of Computer Science. He has also worked on a variety of research projects related to eLearning, data science, and machine learning, particularly focused on how these technologies can improve education and business practices. His previous experience includes a prestigious Master’s thesis position at Imperial College London. 🌍📊

Research Interests

Álvaro Figueira’s research interests span a wide array of cutting-edge fields within Computer Science. His primary focus areas include Data Mining, Text Mining, Machine Learning, Social Network Analysis, Data Visualization, and eLearning. Figueira’s work aims to apply computational techniques to improve the analysis of large datasets, making significant strides in understanding and enhancing social networks and educational systems. His research has contributed to the advancement of automated assessment systems and the optimization of learning processes. 📈🔍

Award

Álvaro Figueira’s contributions to computer science and education have been recognized with various awards and accolades. Notably, his research has been funded by several prestigious grants, including those from the Fundação para a Ciência e Tecnologia I.P. and Instituto de Engenharia de Sistemas e Computadores. His excellence in research is further highlighted by his numerous publications in top-tier journals, where he continues to make an impact in the fields of data science and machine learning. 🏆🎖️

Publications Top Notes

Álvaro Figueira’s publication record reflects his significant contributions to the fields of data science, machine learning, and eLearning. Some of his recent publications include:

“Topic Extraction: BERTopic’s Insight into the 117th Congress’s Twitterverse” – Informatics (2024).

“Clustering source code from automated assessment of programming assignments” – International Journal of Data Science and Analytics (2024).

“Comparing Semantic Graph Representations of Source Code: The Case of Automatic Feedback on Programming Assignments” – Computer Science and Information Systems (2024).

“GANs in the Panorama of Synthetic Data Generation Methods” – ACM Transactions on Multimedia Computing, Communications, and Applications (2024).

“On the Quality of Synthetic Generated Tabular Data” – Mathematics (2023).

“Bibliometric Analysis of Automated Assessment in Programming Education: A Deeper Insight into Feedback” – Electronics (2023).

Ladislav Karrach | Computer Vision | Best Researcher Award

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Dr. Ladislav Karrach | Computer Vision | Best Researcher Award

Post student, Technical University in Zvolen, Slovakia

Ladislav Karrach is a seasoned computer programmer and systems analyst from Kremnica, Slovakia. With a robust background in computer network administration and ERP systems, he has contributed significantly to the field of applied informatics since 1995. His dedication to technology and innovation has positioned him as a key player in developing internal information systems and enhancing client-server applications. 🖥️

Publication Profile

ORCID

Education

Ladislav holds a Ph.D. in Environmental and Manufacturing Technology from the Technical University in Zvolen, where he focused on text recognition in images and its applications in manufacturing processes. He also earned his Ing. (MSc) degree in Applied Informatics from the University of Žilina, specializing in information and control systems. 🎓

Experience

Since 1995, Ladislav has been working as a computer programmer and systems designer at Mint Kremnica, where he manages database servers, designs information systems, and develops client-server applications. His extensive experience includes web programming and administration of ERP systems, making him a versatile professional in the tech industry. 💻

Research Focus

Ladislav’s research interests lie in the fields of image processing, particularly focusing on text recognition methods, data matrix codes, and character recognition technologies. He is dedicated to optimizing production processes through innovative technological solutions and is involved in various research projects that explore the applications of image recognition in manufacturing. 🔍

Awards and Honours

Ladislav has been recognized for his contributions to the field of informatics and manufacturing technology through various publications and collaborative projects. His work is highly regarded in academic circles, showcasing his commitment to advancing technology in practical applications. 🏅

Publication Top Notes

 Data Matrix Code Location Marked with Laser on Surface of Metal Tools. Acta Facultatis Technicae, XXII, 2017 (2), 29–38. – Cited by 1

 Data matrix code location in images acquired by camera. In Manufacturing and automation technology: book of abstracts, 15. – Cited by 0

The analysis of various methods for location of Data matrix codes in images. In ELEKTRO 2018: conference proceedings. – Cited by 2

 Comparing the impact of different cameras and image resolution to recognize the data matrix codes. Journal of Electrical Engineering, 286-292. – Cited by 4

 Optimizatio of manipulation logistics using data matrix codes. Advances in Science and Technology Research Journal, 173-180. – Cited by 3

 Recognition of Data Matrix Codes in Images and their Applications in Production Processes. Management Systems in Production Engineering, 154-161. – Cited by 5

 Using Different Types of Artificial Neural Networks to Classify 2D Matrix Codes and Their Rotations — A Comparative Study. J. Imaging, 188. – Cited by 1

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.

NEHA KATIYAR | Machine Learning | Best Research Article Award

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MS. NEHA KATIYAR | Machine Learning | Best Research Article Award

RESEARCH SCHOLAR, Bennett university, India

 

Neha Katiyar is an Assistant Professor at Noida Institute of Technology, Greater Noida, India. With a robust background in Information Technology and Computer Science, she has contributed significantly to academia through teaching, research, and project management.

Profile

Scopus

Education

🎓 Doctorate
Bennett University, Greater Noida (July 2023 – Present)
Department: Computer Science & Engineering

🎓 Master of Technology
Madan Mohan Malviya University of Technology, Gorakhpur (Aug 2018 – July 2020)
Department: Information Technology and Computer Application
Percentage: 69% (First Division)

🎓 Bachelor of Technology
Sir Chootu Ram Institute of Engineering & Technology, Meerut (July 2015 – June 2018)
University: Chaudhary Charan Singh University, Meerut, U.P
Course: Information Technology
Percentage: 74% (First Division)

🎓 Diploma in Engineering
Government Girls Polytechnic, Lucknow (July 2010 – December 2013)
University: Board of Technical Education, Lucknow UP
Course: Information Technology
Percentage: 70% (First Division)

🎓 High School
Soni Pariya Inter College, Farrukhabad (Apr 2009 – Mar 2010)
Board: Board of High School and Intermediate Education, U.P.
Percentage: 58% (Second Division)

Experience

💼 Assistant Professor
Noida Institute of Technology, Greater Noida (11 April 2022 – 17 May 2023)
Responsibilities included evaluation of copies, research work, academic work, and preparation of question banks and presentations.

💼 Academic Associate
Indian Institute of Management, Rohtak (22 July 2021 – 7 April 2022)
Assisted faculties, conducted empirical research, managed conferences, and evaluated copies.

💼 Research Assistant
Ajay Kumar Garg Engineering College, Ghaziabad (12 Oct 2020 – 16 Jul 2021)
Worked on a project titled “Compressed parallel wavelet tree based on semantic search” funded by the Council of Science And Technology, Uttar Pradesh (UPCST).

Research Interest

🔬 Neha’s research interests include Cyber Security, Internet of Things (IoT), Machine Learning, and Artificial Intelligence. She has actively participated in various projects and research works, contributing to advancements in these fields.

Publications Top Notes

📚 Neha has authored several research papers and articles in reputed journals and conferences. Below are some of her notable publications:

Diabetes detection using IoT techniques and platform: A Survey – Published in the 1st International Conference on Recent Trends in Computer Science and Information Technology (ICRCSIT-20) at St. Martin’s Engineering College Secunderabad Telangana, on 17-18 June 2020.

A review: Target Based Sentiment Analysis using Machine Learning – Published in the 4th International Conference on Microelectronics and Telecommunications at SRM Institute of Science and Technology NCR Campus, on 26-27 Sept. 2020 (Springer Conference).

Index Optimization using Wavelet Tree and Compression – Published in the 2nd International Conference on Data Analytics and Management Conference (ICDAM 2021) at Panipat Institute of Engineering and Technology, on 26 June 2021.

A Survey on Wavelet Tree ensembles with Machine Learning and its classification – Published in 2021 at Sreyas Institute of Engineering and Technology, Hyderabad, on 9-10 July 2021.

A perspective towards 6G Networks – Published in the 5th ICMETE21 at SRM Institute of Science and Technology NCR Campus, on 24-25 Sept. 2021 (Springer Conference).

Trending IoT platform Middleware layer – Published in Taylor and Francis Group Journal on 3 May 2023.

S Anita Shanthi | Fuzzy sets and systems | Best Researcher Award

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Dr. S Anita Shanthi | Fuzzy sets and systems | Best Researcher Award

Associate Professor, Annamalai University, India

Dr. S Anita Shanthi, an Associate Professor at Annamalai University, India, has been honored with the prestigious Best Researcher Award for her pioneering work in the field of fuzzy sets and systems. 🏆 Her research contributions have significantly advanced our understanding of fuzzy logic and its applications, particularly in the realms of decision-making, pattern recognition, and artificial intelligence. Dr. Shanthi’s dedication to pushing the boundaries of knowledge and her commitment to excellence in research have garnered widespread recognition within the academic community. Her innovative approaches and insights continue to inspire and shape the future of fuzzy logic research. 🌟

Profile

Google Scholar

Educational Details 📚

Dr. S. Anita Shanthi pursued her Doctor of Philosophy in Mathematics at Annamalai University, Chidambaram, after completing her Master of Philosophy in Mathematics at Ramanujan Institute for Advanced Study in Mathematics, Madras University, Chennai. Her academic journey began with a Master of Science in Mathematics from Seethalakshmi Ramasamy College, Bharathidasan University, Thiruchirapalli.

Experience Details 💼

Dr. S. Anita Shanthi has been serving as an Associate Professor in Engineering Mathematics at Annamalai University, Tamilnadu, since January 2018. Prior to this, she held the position of Assistant Professor at the same institution for thirteen years, from January 2005 to 2018.

Research Interests 🔍

Dr. Shanthi’s research interests primarily focus on fuzzy mathematics, particularly in the areas of fuzzy normed linear spaces, intuitionistic fuzzy sets, fuzzy topology, and their applications in decision-making and pattern recognition.

Publications Top Notes  📝

“Interval valued fuzzy nnormed linear space” (2008)

“Some fixed point theorems in intuitionistic fuzzy n-normed linear spaces” (2009)

“On lacunary statistical convergence in intuitionistic fuzzy n-normed linear spaces” (2011)

“A decision making method based on similarity measure of interval valued intuitionistic fuzzy soft set of root type” (2015)

“A Study on Q-Level Subsemiring of (Q,L)- Fuzzy Subsemiring of a Semiring” (2015)