Asim Sinan Yuksel | Artificial Intelligence | Research Excellence Award

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Research Excellence Award

Asim Sinan Yuksel

Department of Computer Engineering, Süleyman Demirel University, Turkey

Asim Sinan Yuksel
Affiliation Süleyman Demirel University
Country Turkey
Scopus ID 36999050000
Documents 25
Citations 441
h-index 7
Subject Area Artificial Intelligence
Event Research Awards and Recognitions
ORCID 0000-0003-1986-5269
Google Scholar 1-asL00AAAAJ

Asim Sinan Yuksel is a Turkish computer engineer, researcher, academic administrator, and Associate Professor in the Department of Computer Engineering at Süleyman Demirel University. His scholarly activities encompass artificial intelligence, natural language processing, large language models, vision-language systems, machine learning, cybersecurity, intelligent transportation systems, and multi-agent technologies. Through academic supervision, research leadership, editorial service, and scientific publication, he has contributed to the advancement of applied artificial intelligence and computational research in Türkiye and internationally.[1]

Abstract

This article presents an academic profile of Asim Sinan Yuksel, highlighting his educational background, academic appointments, supervised graduate research, funded projects, scholarly publications, editorial activities, and institutional service. His work spans artificial intelligence, machine learning, natural language processing, cybersecurity, intelligent transportation systems, and emerging large language model applications. The profile also evaluates his suitability for recognition within the context of research excellence and academic achievement.[1]

Keywords

Artificial Intelligence, Natural Language Processing, Large Language Models, Vision-Language Models, Machine Learning, Multi-Agent Systems, Cybersecurity, Intelligent Transportation Systems, Deep Learning, Academic Research.

Introduction

Asim Sinan Yuksel has pursued a multidisciplinary academic career integrating software engineering, intelligent systems, cybersecurity, and data-driven computational methods. Following undergraduate education in Computer Engineering at Ege University, graduate studies at Indiana University Bloomington, and doctoral research at Istanbul University, he developed expertise in software-based security analysis for mobile applications and advanced artificial intelligence applications. His academic trajectory demonstrates a consistent focus on applied research, graduate supervision, and institutional development.[1]

Research Profile

Asim Sinan Yuksel received his Ph.D. in Computer Engineering from Istanbul University on 10 June 2015. His doctoral dissertation, entitled Design of a Software-Based Service for Analyzing the Security Risks of Mobile Applications, was supervised by Prof. Ahmet Sertbaş. Prior to doctoral completion, he earned a master’s degree in Computer Science from Indiana University Bloomington and a bachelor’s degree in Computer Engineering from Ege University.

His academic appointments at Süleyman Demirel University include Research Assistant (2012–2016), Assistant Professor (2016–2021), and Associate Professor (2021–present). He also served as Vice Chair of the Department of Computer Engineering between 2016 and 2018, contributing to departmental administration and academic planning.

Research Contributions

The research portfolio of Asim Sinan Yuksel includes principal investigator and researcher roles in projects related to machine learning, text mining, transportation analytics, cybersecurity awareness, robotic coordination, electric vehicle optimization, and large language model-driven expert systems. These initiatives demonstrate engagement with both theoretical and applied dimensions of artificial intelligence research.

  • Machine learning-based modeling of driver behaviors.
  • Knowledge discovery in social networks using text mining techniques.
  • Large language model-based multi-agent systems for animal health applications.
  • Victim localization in earthquake debris through multi-robot coordination.
  • Energy-efficient route optimization for electric vehicle fleets.
  • Cybersecurity education and awareness initiatives.

Graduate supervision activities include five completed master’s theses and three completed doctoral dissertations addressing machine learning, deep learning, text mining, video summarization, optimization, and educational analytics. These supervisory contributions have supported capacity building within computer science and artificial intelligence research.

Publications

The publication record of Asim Sinan Yuksel spans artificial intelligence, optimization, intelligent transportation systems, educational technologies, and computer vision. Notable contributions include machine learning-based driver risk assessment, hybrid optimization algorithms, blended learning evaluation, deep learning applications, and augmented reality navigation systems, reflecting interdisciplinary research impact and scholarly dissemination.[2][3][4][5]

The publication record includes international conference proceedings, peer-reviewed journal articles, book chapters, and national conference papers. Representative publications include the following works.[2][3]

  1. A novel hybrid PSO–GWO algorithm for optimization problems.
  2. Evaluation of blended learning approach in computer engineering education.
  3. Driver’s black box: A system for driver risk assessment using machine learning and fuzzy logic.
  4. Derin öğrenme teknikleri ile nesne tespiti ve takibi üzerine bir inceleme.
  5. Mobile indoor navigation system in iOS platform using augmented reality.

In addition to research publications, Asim Sinan Yuksel serves as an Editorial Board Member of PLOS ONE, an internationally recognized SCI-Expanded indexed journal. This role reflects participation in scholarly quality assurance and international academic publishing activities.

Research Impact

The research impact of Asim Sinan Yuksel can be observed through interdisciplinary publication activity, graduate supervision, funded project leadership, editorial responsibilities, and sustained contributions to artificial intelligence and software engineering. His research has addressed practical problems in transportation safety, educational analytics, optimization, cybersecurity, and intelligent information systems.[2][4]

His professional experience as a contract software developer for the Social Security Institution of Türkiye further complements his academic work by providing experience in enterprise-level public-sector software development, e-government services, and secure digital infrastructures.

Award Suitability

Consideration for a Research Excellence Award may be supported by several measurable indicators, including sustained academic service, funded research leadership, interdisciplinary publication output, doctoral and master’s supervision, editorial responsibilities, and institutional engagement. His record demonstrates continued participation in national and international research initiatives while contributing to the development of emerging artificial intelligence technologies.

Additional recognition includes the Publication Incentive Award granted by Süleyman Demirel University in 2019. Combined with ongoing TÜBİTAK-supported projects and scholarly leadership activities, this profile aligns with common evaluation criteria used in research recognition programs.

Conclusion

Asim Sinan Yuksel represents a scholarly profile characterized by academic advancement, interdisciplinary research, graduate mentorship, project leadership, editorial service, and applied innovation. His contributions to artificial intelligence, machine learning, natural language processing, cybersecurity, and intelligent systems support his recognition within academic research and innovation communities. Continued involvement in emerging fields such as large language models and multi-agent systems positions his work within contemporary directions of computer science research.

References

  1. Elsevier. (n.d.). Scopus author details: Asim Sinan Yuksel, Author ID 36999050000. Scopus. https://www.scopus.com/authid/detail.uri?authorId=36999050000
  2. Şenel, F. A., Gökçe, F., Yüksel, A. S., & Yiğit, T. (2019). A novel hybrid PSO–GWO algorithm for optimization problems. Engineering with Computers. DOI/URL: https://link.springer.com/article/10.1007/s00366-018-0668-5
  3. Yiğit, T., Koyun, A., Yüksel, A. S., & Cankaya, I. A. (2014). Evaluation of blended learning approach in computer engineering education. Procedia – Social and Behavioral Sciences. DOI: https://doi.org/10.1016/j.sbspro.2014.05.140
  4. Yüksel, A. S., & Atmaca, Ş. (2020). Driver’s black box: A system for driver risk assessment using machine learning and fuzzy logic. Journal of Intelligent Transportation Systems. DOI: https://doi.org/10.1080/15472450.2020.1852083
  5. Cankaya, I. A., Koyun, A., Yiğit, T., & Yüksel, A. S. (2015). Mobile indoor navigation system in iOS platform using augmented reality. International Conference on Application of Information and Communication Technologies. DOI: https://doi.org/10.1109/ICAICT.2015.7338563

Jidan Huang | Artificial Intelligence | Innovative Research Award

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Innovative Research Award

Jidan Huang

Donghua University, China

Jidan Huang
Affiliation Donghua University
Country China
Scopus ID 57193425191
Documents 10
Citations 36
h-index 4
Subject Area Artificial Intelligence
Event Research Awards and Recognitions
ORCID 0000-0003-2547-0212

Jidan Huang is a Chinese academic affiliated with Donghua University whose research combines artificial intelligence, tourism decision-making, logistics management, and multi-objective fuzzy evaluation. His scholarly activities focus on sustainability assessment, intelligent decision-support systems, and advanced multi-criteria evaluation methodologies applied across tourism, management, and operations research disciplines.[1]

Abstract

This article presents a concise academic overview of Jidan Huang, Associate Professor and Senior Experimentalist at Donghua University. His work spans artificial intelligence, tourism management, logistics decision-making, sustainability evaluation, and fuzzy multi-criteria analysis, emphasizing quantitative frameworks that support evidence-based planning and intelligent decision processes across interdisciplinary research environments.[1]

Keywords

Artificial Intelligence; Tourism Management; Multi-Criteria Decision-Making; Fuzzy TOPSIS; Sustainability Assessment; Green Logistics; Decision Support Systems; Cultural Heritage Tourism; Evaluation Systems; Operations Management.

Introduction

Jidan Huang earned a Bachelor of Engineering from Shanghai Maritime University, followed by a Master of Science in Mathematics and a Doctor of Philosophy in Management Science and Engineering from Donghua University. His interdisciplinary educational background supports research integrating mathematics, management science, artificial intelligence, and applied decision analytics.[2]

Research Profile

As Associate Professor at the Glorious Sun School of Business and Management, Donghua University, Huang supervises graduate students and conducts research in tourism decision-making, logistics optimization, artificial intelligence applications, and multi-objective fuzzy evaluation. He also serves as a peer reviewer for several systems science and operations research journals.[2]

Research Contributions

  • Development of three-interval TOPSIS and fuzzy evaluation methodologies.
  • Research on sustainable tourism assessment and optimization strategies.
  • Green logistics evaluation supporting carbon peaking and carbon neutrality goals.
  • Application of artificial intelligence and neural networks in recognition systems.
  • Multi-criteria decision-making frameworks for regional and industrial evaluation.

Publications

Jidan Huang’s publication record includes research on sustainability evaluation, tourism optimization, green logistics, fuzzy decision-making, and artificial intelligence. Representative studies demonstrate the application of TOPSIS, Delphi methods, fuzzy AHP, and convolutional neural networks to address complex evaluation and recognition problems across multiple sectors.[3][4][5][6]

  1. Integrating Life Cycle Assessment and TOPSIS for Product-Level Sustainability Evaluation of Automotive Vehicles.
  2. Evaluation and Development Path Optimization of Rural Low-Altitude Tourism Using a Triangular Fuzzy TOPSIS Approach.
  3. A Model Based on Delphi and Three-Interval TOPSIS: Sustainable Evaluation of Green Logistics Under the Goals of Carbon Peaking and Carbon Neutrality.
  4. Assessing the Sustainable Development of the Tourism Industry Based on Fuzzy AHP and Grey Relational TOPSIS.
  5. Recognition Method for Stone Carved Calligraphy Characters Based on a Convolutional Neural Network.

Research Impact

According to available author metrics, Jidan Huang has produced 10 indexed publications, accumulated 36 citations, and achieved an h-index of 4. His studies contribute to sustainability evaluation, intelligent decision-making, tourism development analysis, and logistics optimization through rigorous quantitative methodologies.[1]

Award Suitability

Jidan Huang’s combination of interdisciplinary research, scholarly publication, postgraduate supervision, and educational achievements supports recognition within research award programs. His contributions to artificial intelligence applications, sustainability assessment, and decision-support methodologies demonstrate continued engagement with contemporary academic and societal challenges.[2]

Conclusion

Jidan Huang maintains an active academic profile centered on artificial intelligence, tourism management, logistics decision-making, and fuzzy evaluation systems. His research outputs, teaching achievements, and methodological contributions highlight a sustained commitment to interdisciplinary scholarship and practical decision-support research.[1]

References

  1. Elsevier. (n.d.). Scopus Author Details: Jidan Huang, Author ID 57193425191. Scopus Author Profile. https://www.scopus.com/authid/detail.uri?authorId=57193425191
  2. Zheng, M., Chen, H., & Huang, J. (2026). Integrating Life Cycle Assessment and TOPSIS for Product-Level Sustainability Evaluation of Automotive Vehicles. Sustainability. DOI: https://doi.org/10.3390/su18115615
  3. Huang, J., Chen, Y., & Pan, W. (2026). Evaluation and Development Path Optimization of Rural Low-Altitude Tourism Using a Triangular Fuzzy TOPSIS Approach. Sustainability. DOI: https://doi.org/10.3390/su18115534
  4. Li, R., Huang, J., Dai, T., & Yang, Q. (2026). A Model Based on Delphi and Three-Interval TOPSIS: Sustainable Evaluation of Green Logistics Under the Goals of Carbon Peaking and Carbon Neutrality. Sustainability. DOI: https://doi.org/10.3390/su18041920
  5. Yang, Q., Huang, J., & Pan, W. (2026). Assessing the Sustainable Development of the Tourism Industry Based on Fuzzy AHP and Grey Relational TOPSIS. Sustainability. DOI: https://doi.org/10.3390/su17219799
  6. Huang, J., Cheng, G., Zhang, J., & Miao, W. (2022). Recognition Method for Stone Carved Calligraphy Characters Based on a Convolutional Neural Network. Neural Computing and Applications. https://link.springer.com/article/10.1007/s00521-022-08049-9

Yao Li | Artificial Intelligence | Best Researcher Award

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Mr. Yao Li | Artificial Intelligence | Best Researcher Award

Mr. Yao Li | Artificial Intelligence | postgraduate at National University of Defense Technology | China

Mr. Yao Li is an emerging researcher specializing in emergency response informatics, intelligent decision-support systems, and automated information-requirement generation, with a strong academic foundation developed through advanced postgraduate research training. Mr. Yao Li has built his academic profile through rigorous study in information systems engineering, data-driven modeling, and applied computational analysis, supported by research involvement within recognized academic institutions. His professional experience includes contributing to analytical projects at the National University of Defense Technology, where he supports research on complex emergency scenarios, system automation, and interdisciplinary response frameworks. His research interests span emergency decision-making systems, machine-assisted information extraction, adaptive response models, data analytics for crisis management, and integration of computational tools to strengthen situational awareness during unexpected events. Mr. Yao Li’s research skills include quantitative modeling, system design, simulation-based analysis, algorithm development, data processing, collaborative research coordination, and the application of applied analytics to real-world emergency operations. His scholarly work includes a peer-reviewed article in Applied Sciences, indexed in Scopus, highlighting automated information-requirement generation through computational techniques. Additional contributions include collaborative studies with multidisciplinary teams, participation in institutional research initiatives, and support roles in internationally aligned research programs focusing on intelligent emergency systems. Throughout his academic journey, Mr. Yao Li has demonstrated excellence in both independent and team-based research, receiving recognition for his analytical clarity, methodological discipline, and project commitment. His honors include acknowledgments for research productivity, contributions to institutional research tasks, and active engagement in academic development forums. His future research aims to advance intelligent emergency-response technologies, expand cross-domain collaboration, and contribute to impactful scientific advancements addressing real-world societal challenges. Mr. Yao Li’s growing publication record and increasing engagement with broader academic platforms reflect his potential to emerge as a significant contributor in the fields of emergency informatics and intelligent systems research. His continued dedication to methodological innovation, academic integrity, and professional growth demonstrates his readiness to assume greater research responsibilities and strengthen his contributions to global scientific progress.

Academic Profile: ORCID

Featured Publications:

Li, Y., Guo, C., Lu, Z., Zhang, C., Gao, W., Liu, J., & Yang, J. (2025). Research on the automatic generation of information requirements for emergency response to unexpected events. Applied Sciences.

 

Vishal Gupta | Artificial Intelligence | Best Researcher Award

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Dr. Vishal Gupta | Artificial Intelligence | Best Researcher Award

Dr. Vishal Gupta | Artificial Intelligence | Assistant Professor at CGC University, Mohali | India

Dr. Vishal Gupta is an accomplished researcher and academician specializing in Web Accessibility, Assistive Technologies, Website Usability, and AI-driven web evaluation frameworks. He earned his Ph.D. from Guru Nanak Dev University, where he developed expertise in accessibility evaluation and applied computing techniques. Dr. Gupta has extensive professional experience in higher education and research, currently serving at Chandigarh Group of Colleges, where he leads research initiatives and mentors students in computer science and web accessibility projects. His research interests focus on enhancing web usability, accessibility compliance for educational and healthcare institutions, and integrating artificial intelligence for industrial and security frameworks. Dr. Gupta possesses strong research skills in website quality assessment, bi-level decision tree methodologies, AI-based vulnerability analysis, and accessibility evaluation metrics, supported by a solid record of international publications and collaborations. He has collaborated with esteemed colleagues such as Hardeep Singh, Parminder Kaur, and I. Kaur on multidisciplinary projects, reflecting his ability to lead and contribute to global research initiatives. Dr. Gupta has actively participated in professional organizations including IEEE and ACM, contributing to conferences, peer reviews, and academic committees, highlighting his leadership and community engagement. His work has been recognized with multiple awards and honors for excellence in research, innovation, and contributions to accessibility studies, reflecting his impact in the academic community. Strengths include his consistent publication record, strong interdisciplinary collaboration, and practical implementation of research findings in real-world settings. Areas for improvement involve exploring larger-scale international projects and further integrating emerging technologies into web accessibility studies. Suggestions for future work include policy-level impact analysis, open-source accessibility frameworks, and AI-enhanced methodologies for inclusive digital platforms. Dr. Gupta’s dedication, scholarly rigor, and innovative approach position him as a leader in his field with promising potential for future research contributions and societal impact, making him a highly suitable candidate for recognition in research and academic excellence.

Academic Profile: ORCID | Google Scholar

Featured Publications:

  1. Gupta, V., & Singh, H. (2021). Web Content Accessibility Evaluation of Universities’ Websites-A Case Study for Universities of Punjab State in India. 8th International Conference on Computing for Sustainable Global Development, 9 citations.

  2. Gupta, V., & Singh, H. (2022). Website Readability, Accessibility, and Site Security: A Survey of University Websites in Punjab. International Journal of Mechanical Engineering, 7(6), 1-9, 3 citations.

  3. Gupta, V., Singh, H., & Kaur, P. (2024). Accessibility Evaluation of Hospital Websites in India. International Journal of Computer Applications & Information Technology, 14, 1 citation.

  4. Gupta, V., Kaur, I., Singh, S., Kumar, V., & Kaur, P. (2025). Artificial Intelligence-empowered Industrial Framework for Extreme Vulnerability Analysis. Future Generation Computer Systems, 108127, citation data not available.

  5. Gupta, V., Kaur, P., & Singh, H. (2024). Bi-Level Decision Tree Approach for Web Quality Assessment. IEEE Access, citation data not available.

 

Prerna Chaudhary | Machine Learning | Best Researcher Award

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Ms. Prerna Chaudhary | Machine Learning | Best Researcher Award

Ms. Prerna Chaudhary | Machine Learning | PhD student at IIT DELHI | India

Ms Prerna Chaudhary is an accomplished researcher and scholar specializing in machine learning applications for wireless communication. She earned her Ph.D. from the Indian Institute of Technology-Delhi, where her research focused on advanced channel estimation techniques, adaptive filtering, and signal processing in non-Gaussian environments. Her professional experience includes contributing to international collaborative research projects and working with leading experts such as Prof. Manav R. Bhatnagar and B.R. Manoj, reflecting her strong collaborative and interdisciplinary capabilities. Ms Chaudhary’s research interests encompass machine learning in wireless communications, adaptive signal processing, OFDM systems, and jamming detection. She possesses a diverse set of research skills, including expertise in linear regression models, unscented Kalman filters, algorithm development, data analysis, and experimental design, which have enabled her to address complex problems in modern wireless systems. Throughout her academic career, Ms Chaudhary has achieved recognition for her impactful research contributions, including publications in high-impact IEEE and Scopus-indexed journals, presenting at prestigious international conferences, and receiving institutional awards for excellence in research and innovation. Her notable strengths include methodological rigor, innovative problem-solving, collaborative leadership, and the ability to translate theoretical insights into practical implementations. Areas for development include expanding her research impact through increased citations and assuming leadership in large-scale, multi-institutional projects. Ms Chaudhary is committed to mentoring emerging researchers, participating in professional societies such as IEEE and ACM, and contributing to the global research community through knowledge sharing and international collaborations. Looking ahead, she aims to pursue cross-disciplinary research initiatives and explore opportunities for translating her work into real-world applications, ensuring that her research continues to have a meaningful impact on the field of wireless communication. Ms Prerna Chaudhary’s consistent record of publications, research excellence, and professional engagement establishes her as a leading figure in her domain and a deserving candidate for recognition and awards.

Academic Profile: Google Scholar

Featured Publications:

  1. Chaudhary, P., Chauhan, I., Manoj, B. R., & Bhatnagar, M. R. (2024). Linear Regression-Based Channel Estimation for Non-Gaussian Noise. IEEE 99th Vehicular Technology Conference (VTC2024-Spring). Citation: 2

  2. Chaudhary, P., Manoj, B. R., Chauhan, I., & Bhatnagar, M. R. (2025). Channel Estimation using Linear Regression with Bernoulli-Gaussian Noise.

  3. Srivastava, S., Chaudhary, P., & Bhatnagar, M. R. (2024). Comparative Analysis of Machine Learning Algorithms for Pulse Jammer Detection. IEEE International Conference on Advanced Networks and …. Citation: 0

  4. Chaudhary, P., Manoj, B. R., Patidar, V. K., & Bhatnagar, M. R. (2024). Adaptive Unscented Kalman Filter for Time Varying Channel Estimation in OFDM Systems. IEEE International Conference on Advanced Networks and ….

 

Henry Ogbu | Artificial Intelligence | Best Researcher Award

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Mr. Henry Ogbu | Artificial Intelligence | Best Researcher Award

Mr. Henry Ogbu | Artificial Intelligence | Assistant Lecturer at Covenant University | Nigeria

Mr Henry Ogbu is an emerging scholar and researcher in the field of Computer and Information Science whose academic journey and professional achievements demonstrate a strong commitment to advancing artificial intelligence and computational intelligence. He pursued his higher education at Covenant University, Nigeria, where he specialized in Computer and Information Science, acquiring a solid academic foundation that enabled him to explore machine learning, optimization algorithms, and recommender systems in depth. Through his education and research training, Mr Henry Ogbu developed expertise in algorithm design, neural network optimization, and intelligent systems modeling, positioning himself as a promising academic with innovative contributions to technology-driven solutions. Professionally, Mr Henry Ogbu has participated actively in research projects, presenting his work at international conferences and publishing in peer-reviewed journals and conference proceedings indexed in Scopus and IEEE databases. His professional experience reflects a dedication to solving practical problems through artificial intelligence applications, including automated grading systems, operating system evaluation, and optimization strategies in computational models. His research interests cover deep learning, neural networks, optimization techniques, artificial intelligence, and intelligent recommender systems, with an emphasis on designing models that are efficient, scalable, and adaptable to modern computational challenges. In his published works, such as iAttention Transformer: An Inter-Sentence Attention Mechanism for Automated Grading and Application of Optimization Techniques in Recommender Systems, he demonstrates both technical rigor and practical applicability, thereby contributing to the global body of knowledge in artificial intelligence. His skills extend across several domains including advanced algorithm development, optimization modeling, neural network training, data-driven analysis, and collaborative research across interdisciplinary domains. Mr Henry Ogbu is adept in employing mathematical foundations, coding skills, and machine learning frameworks to design and evaluate systems, making his research highly relevant to academia and industry. Alongside his research expertise, he has also participated in academic leadership roles, contributing to collaborative projects and engaging with the broader research community through conference presentations and knowledge-sharing forums.

Academic Profile: ORCID | Google Scholar

Featured Publications:

Ogbu, H. N., Dada, I. D., Akinwale, A. T., Osinuga, I. A., & Tunde-Adeleke, T. J. (2025). iAttention Transformer: An inter-sentence attention mechanism for automated grading. Mathematics, 13(18), 2991.

Ogbu, H. N. (2024). Application of optimization techniques in recommender systems. Proceedings of the International Conference on Computer Science.

Ogbu, H. N. (2024). Training neural network model using an improved three-term conjugate gradient algorithm. In Proceedings of the 1st International Conference & Research Showcase on Science, Technology & Innovation (ICRS-STI 2024).

Ogbu, H. N. (2021). Comparative study of operating system quality attributes. IOP Conference Series: Materials Science and Engineering, 1107(1), 012061. — Citations: 6

Serdar kırışoğlu | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Serdar kırışoğlu | Artificial Intelligence | Best Researcher Award

Assoc. Prof. Dr. Serdar kırışoğlu | Artificial Intelligence – Academic Staff at Duzce University, Turkey

Assoc. Prof. Dr. Serdar KIRIŞOĞLU is a prominent scholar and researcher whose work bridges artificial intelligence, machine learning, blockchain systems, and data-driven analytics. As a faculty member at Düzce University’s Department of Computer Engineering, he has contributed significantly to advancing technology in economic forecasting, smart systems, and secure networks. Over the course of his academic career, he has guided multiple research initiatives, mentored graduate and doctoral students, and published impactful research recognized by leading journals and conferences worldwide.

Academic Profile:

ORCID

Education:

Dr. KIRIŞOĞLU earned his Ph.D. in Electrical-Electronics and Computer Engineering in 2018 from Düzce University, where his dissertation introduced a novel dynamic VLAN approach to optimize the systematic design of corporate networks. He previously obtained a Master’s degree in Electrical Education in 2009 from Abant İzzet Baysal University, focusing on FPGA-based hardware solutions for secure digital image data embedding and extraction, and a Bachelor’s degree in Electrical-Electronics Engineering in 2000 from Kahramanmaraş Sütçü İmam University, laying the groundwork for his expertise in computer engineering and digital systems.

Experience:

With a career rooted in academia and research, Dr. KIRIŞOĞLU has been an integral part of Düzce University since 2018, serving as an Associate Professor and leading various roles, including Head of the IT Department, where he drives digital transformation and technological innovation. His experience spans leadership in high-impact national and international projects, including initiatives on big data infrastructure, augmented reality applications, AI-based economic crisis detection, and advanced cybersecurity measures. He has also served as a dedicated supervisor for numerous master’s and doctoral theses, fostering future researchers in cutting-edge fields like financial analytics, machine learning, and natural language processing.

Research Interest:

Dr. KIRIŞOĞLU’s research interests encompass artificial intelligence, machine learning, blockchain-based systems, big data analytics, and network optimization. His current projects involve developing predictive models for stock markets using AI, applying NLP to detect economic crises, enhancing cybersecurity through intelligent threat detection, and integrating augmented reality with web-based systems. His interdisciplinary approach consistently merges theoretical innovation with practical applications, benefiting sectors such as finance, education, and healthcare.

Award:

His dedication to advancing computer engineering has positioned him as a strong nominee for the Best Researcher Award 2025, with recognition stemming from his leadership in research-driven projects, his impactful publications indexed in Scopus and IEEE, and his ongoing contributions to mentoring future scholars and innovators in AI and technology.

Publications:

Detection of Economic Crises With Language Models and Comparative Analysis of Simple Time Series Analysis Models and Machine Learning Algorithms on the Stock Market – IEEE Access, 2025.
Determination of Gold Purity Degrees Using Audio Features with Machine Learning Algorithms – Applied Acoustics, July 2025.
Cyclical Hybrid Imputation Technique for Missing Values in Data Sets – Scientific Reports, February 2025.
Sustainable Economic Development Through Crisis Detection Using AI Techniques – Sustainability, February 2025.
GSelf-MapReduce: A Method for Enhancing MapReduce Performance in Distributed Heterogeneous Data Centers – IEEE Access, 2024.
Pandemi Sürecinde Uzaktan Eğitimde Senkron, Asenkron ve Hibrit Yapılmış Derslerde Veri Madenciliği ile Öğrenci Performans Analizi – Düzce Üniversitesi Bilim ve Teknoloji Dergisi, January 2024.
Çok Katmanlı Algılayıcı ile Ağ Trafiği Sınıflandırma Analizi – Düzce Üniversitesi Bilim ve Teknoloji Dergisi, April 2022.

Conclusion:

Assoc. Prof. Dr. Serdar KIRIŞOĞLU’s career exemplifies academic excellence, impactful research, and forward-thinking innovation, making him an ideal candidate for the Best Researcher Award 2025. His pioneering work in artificial intelligence, big data, and blockchain, combined with his dedication to mentoring and leading research initiatives, underscores his substantial contributions to both science and society. With a growing body of influential publications and leadership in transformative projects, he continues to shape the future of computer engineering and remains committed to expanding his global academic impact through further collaborations and innovations.

 

 

Wai Kin Victor Chan | Artificial Intelligence | Best Researcher Award

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Prof. Wai Kin Victor Chan | Artificial Intelligence | Best Researcher Award

Prof. Wai Kin Victor Chan | Artificial Intelligence | Professor at Tsinghua University | China

Prof. Wai Kin Victor Chan is a distinguished academic and researcher at Tsinghua University’s Tsinghua-Berkeley Shenzhen Institute, widely recognized for his expertise in agent-based simulation, discrete-event systems, intelligent transportation networks, and sustainable energy applications. Over his career, he has made significant strides in computational modeling, deep learning frameworks, blockchain systems, and manufacturing optimization, earning more than 2,600 citations across his research portfolio. His work addresses pressing technological challenges by bridging simulation science, artificial intelligence, and smart city innovation, establishing him as a thought leader and collaborator in advancing next-generation technologies for global benefit.

Academic Profile

ORCID

Google Scholar

Education

Prof. Chan earned his Ph.D. in Systems Engineering, focusing on discrete-event simulation modeling and optimization techniques for complex industrial systems. His doctoral research, supported by international collaborations, laid the foundation for his future breakthroughs in multi-cluster scheduling, simulation-based energy analysis, and AI-driven forecasting frameworks. Building upon his early academic achievements, his continuous learning through postdoctoral engagements and research residencies allowed him to refine expertise in transportation systems modeling, sustainable manufacturing, and decentralized technologies.

Experience

Prof. Chan has built an extensive research career through faculty roles, international research collaborations, and industry-linked projects that merge academic rigor with real-world impact. At Tsinghua University, he leads interdisciplinary initiatives connecting simulation, artificial intelligence, and smart infrastructure, partnering with global institutions to develop computational frameworks for blockchain energy modeling, emergency transportation planning, and AI-powered traffic systems. His experience spans conference leadership, workshop facilitation, and mentoring graduate researchers, while his advisory roles for industrial partners have enabled the application of his models to enhance supply chains, urban planning, and energy-efficient manufacturing systems.

Research Interest

Prof. Chan’s research interests are anchored in agent-based and discrete-event simulations, Monte Carlo computational techniques, AI-enabled traffic prediction, blockchain-driven sustainability, and system optimization for smart cities and industrial processes. He is particularly focused on developing hybrid modeling approaches that combine simulation and artificial intelligence to manage complex, dynamic systems. His contributions to the study of emergent behavior modeling, electricity market simulations, and multi-cluster scheduling have influenced the design of scalable frameworks for both academic research and applied engineering solutions worldwide.

Award

Prof. Chan’s exceptional academic trajectory, marked by his citation index of 2,634, h-index 24, and i10-index 49, positions him as a strong nominee for the Best Researcher Award. His contributions have advanced transportation system resilience, sustainable blockchain adoption, and AI-driven optimization techniques, earning recognition within academic and professional networks such as IEEE and ACM. His role as a collaborative leader in international research projects exemplifies the kind of global impact celebrated by this award category.

Publications

  • “Cost modeling and optimization of a manufacturing system for mycelium-based biocomposite parts”
    Published year: 2016 | Citations: 77

  • “Agent-Based Simulation Tutorial: Simulation of Emergent Behavior”
    Published year: 2010 | Citations: 240

  • “Optimal Scheduling of Multicluster Tools Part I”
    Published year: 2010 | Citations: 154

  • “Spatial-Temporal Attention Wavenet for Traffic Prediction”
    Published year: 2021 | Citations: 117

  • “Evaluation of Energy Consumption in Blockchains”
    Published year: 2020 | Citations: 109

  • “Monte Carlo Simulations Applied to Uncertainty in Measurement”
    Published year: 2013 | Citations: 125

  • “Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization”
    Published year: 2023 | Citations: 107

Conclusion

Prof. Wai Kin Victor Chan’s research career embodies the qualities celebrated by the Best Researcher Award, blending theoretical innovation, high-impact publications, and interdisciplinary leadership. His pioneering studies in agent-based systems, AI-driven simulations, and sustainable technologies not only advance the state of knowledge but also provide solutions for urban resilience, energy efficiency, and digital innovation. With a strong publication record, global collaborations, and a vision for expanding AI-integrated sustainability and smart infrastructure frameworks, he continues to shape the future of computational science, making him a deserving recipient of this recognition.