Mokhtar Ferhi | Computer Science and Artificial Intelligence | Research Excellence Award

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Dr. Mokhtar Ferhi | Computer Science and Artificial Intelligence | Research Excellence Award

University of Jendouba | Tunisia

Dr. Mokhtar Ferhi is a researcher at Université de Jendouba, Tunisia, specializing in heat transfer, fluid mechanics, magnetohydrodynamics (MHD), nanofluid convection, and numerical simulation methods, particularly the Lattice Boltzmann Method. He has authored 27 peer-reviewed publications, receiving 140 citations with an h-index of 6 (Scopus). His work focuses on entropy generation, energy optimization, and thermal performance enhancement in cavities and micro-heat exchangers. Ferhi collaborates internationally with experts across North Africa, Europe, and the Middle East, contributing to advances in energy-efficient thermal systems with applications in sustainable engineering and heat exchanger design.

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Saeed Banaeian Far | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Saeed Banaeian Far | Computer Science | Best Researcher Award

Assist. Prof. | Blockchain and Metaverse research lab | Iran

Assist. Prof. Dr. Saeed Banaeian Far is a leading researcher in applied cryptography, blockchain systems, security protocols, and emerging Metaverse technologies. He is affiliated with the Blockchain and Metaverse Research Lab (BMRL) and has made influential contributions to decentralized finance, digital twins, NFTs, Web3, privacy-preserving protocols, and quantum-secure blockchain architectures. With over 44 peer-reviewed publications in high-impact journals and conferences, his work has received 1,045 citations, reflecting strong global academic influence. He actively collaborates with international scholars and interdisciplinary teams, advancing secure digital infrastructures with significant societal impact in finance, governance, healthcare, and next-generation virtual ecosystems.

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Ei Mehdi Chakour | Computer Science | Research Excellence Award

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Dr. Ei Mehdi Chakour | Computer Science | Research Excellence Award

Research Postdoc | Université Sidi Mohamed Ben Abdellah | Morocco

Dr. Ei Mehdi Chakour is a researcher at Université Sidi Mohamed Ben Abdellah, Fez, Morocco, specializing in medical image analysis and deep learning applications for ophthalmology, particularly diabetic retinopathy detection. With four peer-reviewed publications and 16 citations, Dr. Chakour has contributed to advancements in retinal image segmentation, enhancement, and severity classification using dynamic preprocessing, mathematical morphology, and transfer learning techniques. His collaborative work involves 11 co-authors across international conferences and journals, reflecting a strong commitment to interdisciplinary research. Through the development of mobile-based deep learning systems, his work demonstrates significant societal impact by enabling earlier, accessible, and accurate diabetic retinopathy screening.

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Featured Publications


Mobile‑based deep learning system for early detection of diabetic retinopathy.

– Intelligence‑Based Medicine. Advance online publication. (2025). 

Transfer learning for severity and stages detection of diabetic retinopathy.

-Embedded Systems and Artificial Intelligence (ESAI) . (2024).

Blood vessel segmentation of retinal fundus images using dynamic preprocessing and mathematical morphology.

– International Conference on Control, Decision and Information Technologies (CoDIT). (2022). 

Yirga Munaye | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Yirga Munaye | Computer Science | Best Researcher Award

Postdoctoral Researcher | Bahir Dar University | Ethiopia

Dr. Yirga Munaye is a distinguished researcher at Bahir Dar University, Ethiopia, specializing in wireless communication, UAV systems, artificial intelligence, IoT, and cybersecurity. With 36 publications and 599 citations, he has made significant contributions to UAV positioning, indoor/outdoor localization, deep learning for resource management, and secure network infrastructures. His collaborations span 36 international co-authors, reflecting strong interdisciplinary and global engagement. Dr. Munaye’s research addresses critical societal challenges, including smart connectivity, network optimization, and AI-driven security solutions, advancing both theoretical knowledge and practical applications in emerging technologies worldwide.

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Aiyshwariya Devi | Artificial Intelligence | Best Researcher Award

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Dr. R. Aiyshwariya Devi | Artificial Intelligence | Best Researcher Award

RMK College Of Engineering and Technology| India

The author demonstrates strong research leadership in IoT security, AI, and data-driven systems, supported by 30+ scholarly documents, 129 citations, and an h-index of 4, reflecting consistent academic impact and relevance. Strengths include interdisciplinary research output, funded project leadership, patent-oriented innovation, editorial and reviewer experience, and sustained contributions to high-quality journals and conferences. Areas for improvement include expanding publications in higher-impact Q1 journals, increasing international co-authorship, and translating research prototypes into large-scale real-world deployments. The author’s future potential is significant, particularly in advancing secure AI-enabled IoT architectures, quantum-enhanced machine learning, and industry–academia collaborative research, positioning them as a strong candidate for research excellence and innovation-focused awards.

Dr. R. Aiyshwariya Devi
Associate Professor, RMK College of Engineering & Technology

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Featured Publications


Energy-efficient cluster head selection scheme based on FMPDM for MANETs


– International Journal of Innovative Research in Science, Engineering and Technology, 2014 · 13 citations


IoT device security for smart card fraud detection for credit cards


– 2nd International Conference on Advancements in Electrical & Electronics Engineering, 2023 · 5 citations


An IoT Security-Based Electronic Aid for Visually Impaired Detection with Navigation Assistance System


– International Journal of Advanced Science and Technology, 2020 · 4 citations

Mahmood ul Hassan | Computer Science | Editorial Board Member

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Assist. Prof. Dr. Mahmood ul Hassan | Computer Science | Editorial Board Member

Assistant Professor | Najran University | Saudi Arabia

Dr. Mahmood ul Hassan is a distinguished researcher and academic affiliated with the National Industrial Training Institute, TÜV Rheinland Arabia in the Kingdom of Saudi Arabia, with a verified scholarly association at Jazan University (ju.edu.sa). His research expertise spans Wireless Sensor Networks (WSN), Vehicular Ad Hoc Networks (VANET), mobile cloud computing, AI-driven smart systems, and ICT applications in education and healthcare. Over his career, he has built a strong interdisciplinary footprint across computer engineering, artificial intelligence, cybersecurity, and applied networking.Dr. Hassan has authored 157 scholarly documents with over 909 citations, an h-index of 17, and an i10-index of 31, reflecting both the breadth and impact of his contributions. His notable publications include influential works on smart agriculture using AI, tumor classification in MRI using wavelets and SVM, ANN-based secure routing protocols for VANETs, image segmentation models, glioma classification using deep CNNs, and lightweight security frameworks for WSNs. Several of his papers in Energies, Sensors, IEEE Access, Computers, Materials & Continua, and Wireless Communications and Mobile Computing have been widely cited and integrated into ongoing global research.His collaborations with multidisciplinary teams across Saudi Arabia, Pakistan, and international institutions highlight his commitment to advancing digital transformation in critical sectors. Dr. Hassan’s work on intelligent connectivity restoration, blockchain-based secure information routing, microservice optimization, fog computing, and IoT-enabled education systems demonstrates a consistent alignment with emerging technological challenges. Beyond core engineering, he has also contributed research in health informatics, public-sector project planning, archaeology, and medical studies, showcasing his broad academic versatility.Dr. Mahmood ul Hassan’s research has substantive societal impact, particularly in enhancing network reliability, secure communication, healthcare diagnostics, smart agriculture, and technology-driven education. His sustained scholarly productivity and cross-disciplinary influence continue to position him as a leading academic voice in next-generation networked systems and intelligent computing solutions.

Profiles : Googlescholar | Scopus | ORCID

Featured Publications

1. Smart agriculture cloud using AI-based techniquesJunaid, M., Shaikh, A., Hassan, M. U., Alghamdi, A., Rajab, K., Al Reshan, M. S., & … (2021). Smart agriculture cloud using AI-based techniques. Energies, 14(16), 5129. Cited By: 58

2. Classification of tumors in human brain MRI using wavelet and support vector machineAhmad, M., Hassan, M., Shafi, I., & Osman, A. (2012). Classification of tumors in human brain MRI using wavelet and support vector machine. IOSR Journal of Computer Engineering, 8(2), 25–31. Cited By: 53

3. ANN-based intelligent secure routing protocol in vehicular ad hoc networks (VANETs) using enhanced AODVHassan, M. U., Al-Awady, A. A., Ali, A., Sifatullah, Akram, M., Iqbal, M. M., Khan, J., & … (2024). ANN-based intelligent secure routing protocol in vehicular ad hoc networks (VANETs) using enhanced AODV. Sensors, 24(3). Cited By: 44

4. A weighted spatially constrained finite mixture model for image segmentationAhmed, M. M., Shehri, S. A., Arshed, J. U., Hassan, M. U., & Hussain, M. (2021). A weighted spatially constrained finite mixture model for image segmentation. Computers, Materials & Continua, 67(1), 171–185. Cited By: 42

5. A CNN-model to classify low-grade and high-grade glioma from MRI imagesHafeez, H. A., Elmagzoub, M. A., Abdullah, N. A. B., Al Reshan, M. S., Gilanie, G., & … (2023). A CNN-model to classify low-grade and high-grade glioma from MRI images. IEEE Access, 11, 46283–46296. Cited By: 37

Dr. Mahmood ul Hassan’s research advances secure, intelligent, and resilient networked systems that enhance healthcare diagnostics, smart agriculture, and sustainable digital infrastructure. His work bridges AI, wireless communication, and cloud technologies, delivering innovative solutions with direct societal and economic impact.

Yongbin Zhao | Computer Science | Best Researcher Award

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Dr. Yongbin Zhao | Computer Science | Best Researcher Award

School of Information Science and Technology | Shijiazhuang Tiedao University | China

Dr. Yongbin Zhao is a researcher at Shijiazhuang Tiedao University, China, recognized for his growing contributions to computational science, network analysis, and data-driven systems research. With a Scopus-indexed publication record comprising 27 scholarly documents and 67 citations across 66 citing sources, he has established an emerging academic profile characterized by interdisciplinary inquiry and collaborative engagement. His current h-index of 5 reflects the consistent impact and relevance of his research in both theoretical and applied domains.Dr. Zhao’s work spans multiple high-value fields including blockchain security complex network modeling and agricultural trade analytics. His recent publication on multi-key fully homomorphic encryption algorithms introduces secure computation frameworks tailored for blockchain environments contributing to the advancement of privacy-preserving technologies in decentralized systems. Another notable study focusing on the evolution and robustness of the global soybean trade network demonstrates his ability to integrate physics-based modeling with international agricultural economics offering meaningful insights for global trade stability and food-system resilience.He has collaborated with more than 40 co-authors reflecting a strong international and interdisciplinary research network. His contributions extend beyond academic outputs providing analytical tools and conceptual frameworks that support secure data infrastructures enhance trade-network understanding and contribute to more resilient socio-economic systems.Through his sustained research activity and collaborative leadership Dr. Yongbin Zhao continues to contribute to scientific knowledge with societal and technological relevance strengthening the interface between computational innovation and global system analysis.

Profiles : Scopus | Research Gate

Featured Publications

1.Author(s). (2025). Research on multi-key fully homomorphic encryption algorithms suitable for blockchain. Cluster Computing.

2.Author(s). (2024). The evolution and robustness analysis of global soybean trade network. International Journal of Modern Physics C. Cited By : 2

Dr. Zhao’s contributions in homomorphic encryption and network robustness drive innovation in blockchain security and international supply-chain analytics. His research supports industry in building safer digital platforms and more efficient global trade systems.

RaulJavier ChangTam | Data Science and Analytics | Best Researcher Award

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Prof. Dr. RaulJavier ChangTam | Data Science and Analytics | Best Researcher Award

Profesor Investigador | Universidad Latina de Costa Rica | Costa Rica

Prof. Dr. RaulJavier ChangTam  is a multidisciplinary researcher whose work connects technology adoption, entrepreneurship, and sustainable innovation in Latin America. His research explores how emerging technologies influence entrepreneurial ecosystems, digital transformation, and user behavior within both business and social contexts. Drawing upon models such as UTAUT2, his studies provide empirical insights into the acceptance and use of new technologies by entrepreneurs, SMEs, and professionals in fields like healthcare and finance. He also contributes to studies on sustainable finance and FinTech, emphasizing the role of digital platforms and neobanks in promoting environmentally responsible entrepreneurship. Beyond business and technology, his work extends into socio-cultural domains examining global consumption patterns such as sneaker culture and analyzing trade dynamics in ornamental species markets. Chang-Tam’s ongoing research reflects a strong orientation toward understanding the intersection of innovation, digitalization, and sustainability, with an applied perspective that links academic insight to real-world economic and cultural transformations. His research has received 3 citations across 9 documents, with an h-index of 1.

Profiles : ORCID | Scopus  | ResearchGate

Featured Publications

1. Taboada Álvarez, J. E., Chang-Tam, R. J., Rueda Varón, M. J., & Hunter Torrealba, R. (2025). Analysis of the entrepreneurial motivational demand in a learning management process in incubators.

2. Araya, J. L. G., Robles Herrera, A. E., & Chang-Tam, R. J. (2025). Analysis of trends in exports and imports of continental and marine ornamental species of aquariums in Costa Rica.

3. Chang-Tam, R. J., Caldera-Gutiérrez, V., & Rivera Shaik, V. (2025). Influence of IT technology on the development of SME entrepreneurs in Costa Rica: Applied study of the adapted model of the Unified Theory of Acceptance and Use of Technology (UTAUT2).

4. Chang-Tam, R. J., Garita Quesada, R., Masís Muñoz, R., & Chang Caldera, A. P. (2025). Influence of new IT technology trends in dental care processes between dental professionals and patients: An analysis of the UTAUT2 theory.

5. Palos-Sanchez, P. R., Chang-Tam, R. J., & Folgado-Fernández, J. A. (2025). The role of neobanks and fintech in sustainable finance and technology: The customer/user perspective for entrepreneurs. Sustainable Technology and Entrepreneurship, 100109.

Deqian Fu | Data Science and Analytics | Best Researcher Award

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Prof. Dr. Deqian Fu | Data Science and Analytics | Best Researcher Award

Professor | Linyi University | China

Prof. Dr. Deqian Fu is a prominent researcher at Linyi University, China, with a strong focus on logistics, data exchange, and trust management in supply chain and intermodal transport systems. His research explores innovative methods for secure and efficient data sharing in the logistics industry, integrating advanced technologies such as blockchain, edge computing, and ontology-based frameworks. Fu has made notable contributions in developing trusted data access control mechanisms and non-intrusive data exchange models that enhance collaboration and operational efficiency across complex logistics networks. He has authored 39 publications, which have collectively garnered 127 citations, reflecting the growing impact of his work in the fields of applied sciences and industrial informatics. His research outputs demonstrate a commitment to advancing the intersection of information technology and logistics, emphasizing both theoretical development and practical applications. With an h-index of 7, Fu’s scholarly contributions have been recognized for their relevance and innovation, particularly in promoting secure and intelligent data-sharing frameworks within the logistics sector. Selected works include “Trusted Data Access Control Based on Logistics Business Collaboration Semantics” in Applied Sciences (2024), alongside conference papers such as “Data Exchange and Sharing Framework for Intermodal Transport Based on Blockchain and Edge Computing” and “Trusted Non-intrusive Data Exchange based on Ontology in Logistics Industry,” underscoring his focus on reliable, technology-driven logistics solutions.

Profiles : ORCID | Scopus 

Featured Publications

1. Wang, W., Li, Q., Jiang, Z., Fu, D., & Camacho, D. (2025). An efficient framework for general long-horizon time series forecasting with Mamba and diffusion probabilistic models. Engineering Applications of Artificial Intelligence.

2.Liu, Z., Shi, Z., Wang, W., Kong, R., Fu, D., & Qiu, J. (2025). Research on data ownership and controllable sharing schemes in the process of logistics data flow.

3.Wang, L., Zhang, X., Xu, L., Fu, D., & Qiu, J. (2024). Data exchange and sharing framework for intermodal transport based on blockchain and edge computing. In Communications in Computer and Information Science. Springer.

4.Zhang, X., Jing, C., Chen, Y.-C., Wang, L., Xu, L., & Fu, D. (2024). Trusted data access control based on logistics business collaboration semantics.

5.Zhang, X., Wang, L., Xu, L., & Fu, D. (2023). A distributed logistics data security sharing model based on semantics and CP-ABE. In Proceedings of the ACM International Conference (pp. 1–8).

Nikolay Kiktev | Computer Science | Best Researcher Award

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Dr. Nikolay Kiktev | Computer Science | Best Researcher Award

Associate Professor at National University of Life and Environmental of Ukraine, Ukraine

Dr.  Nikolay Kiktev  Ukraine, is a dedicated Associate Professor and Candidate of Technical Sciences specializing in automation and robotic systems . With over 25 years of professional and academic experience, he has played key roles in developing information-management systems for industries such as food, coal, and energy. He has contributed extensively to digital transformation projects in educational institutions across Donetsk . Currently serving at both the Taras Shevchenko National University of Kyiv and the National University of Bioresources and Environmental Management, he teaches a range of cutting-edge subjects in automation, robotics, and data analytics . A prolific researcher with over 120 publications, 41 indexed in Scopus, he holds two patents and continues to mentor students in various engineering disciplines . His work bridges academic excellence and industrial innovation, particularly in AI-integrated systems and sustainable technologies .

Professional Profile

ORCID Profile | Google Scholar 

Education

Dr.  Nikolay Kiktev holds a Specialist Diploma in Systems Engineering  from Donetsk State Technical University , majoring in “Automated Information Processing and Control Systems” . He earned his Ph.D. (Candidate of Technical Sciences)  from the National University of Food Technologies, specializing “Automation of Management Processes” . His dissertation focused on automating technological processes involving carbon dioxide salt production . In 2020, he received the title of Associate Professor in the Department of Automation and Robotic Systems . His academic journey reflects deep technical expertise and a strong foundation in process automation, cyber-physical systems, and advanced engineering methodologies . His educational background has been pivotal in his successful teaching and research career, allowing him to train the next generation of engineers in Ukraine and contribute to national technological development .

Experience

Dr.  Nikolay Kiktev began his career as a software engineer  at the Temp Defense Industry Association in Donetsk . He pursued graduate studies while engaging in research projects related to automation in chemical processes . From 1999–2002, he taught at Donetsk National Technical University and other institutes. From 2002–2010, he served as Director of the Donetsk City Council’s Methodological Center for Computerization, leading large-scale digital education infrastructure projects . He briefly worked in private industry supplying IT and telecom solutions for coal and power sectors . He has held academic posts at the National University of Bioresources and Environmental Management and Taras Shevchenko National University of Kyiv, advancing to Associate Professor. He teaches diverse automation and robotics courses, supervises theses, and delivers specialized lectures across several Ukrainian universities .

Research Interest

Dr.  Nikolay Kiktev research revolves around intelligent automation and computer-integrated technologies . His focus areas include automated information-management systems for agriculture , electrochemical industries , compound feed production, and mining systems . He works on developing distributed information systems and software-hardware complexes that enhance control, efficiency, and sustainability of industrial processes . His interests extend into industrial and agricultural robotics, applying smart technologies to real-world production systems. He integrates geoinformatics, AI, and CAD into engineering curricula and projects . His interdisciplinary approach merges technical innovation with practical needs in automation, data processing, and system modeling . His international research footprint includes publications in journals from Bulgaria, Poland, Russia, and Switzerland , reflecting a strong commitment to global knowledge exchange. With a focus on advancing Industry 4.0 applications in Ukraine, Kiktev’s work contributes significantly to both academic knowledge and applied engineering development .

Award and Honor

Dr.  Nikolay Kiktev has received several distinctions over his career that recognize both academic excellence and applied innovation . He holds the official title of Associate Professor (2020) and earned his Candidate of Technical Sciences degree in 2011 for his pioneering work on electrochemical process automation . He was awarded two patents and three copyright certificates, demonstrating inventive contributions to process automation and information systems . With over 50 peer reviews  journals (such as MDPI) , he is an internationally recognized evaluator of scientific excellence. His extensive publication record includes 41 Scopus-indexed articles, reflecting high academic impact . He has contributed to national technology projects such as Ukraine’s “Digital City” education initiative . His leadership in these projects has had a transformative effect on digital infrastructure and education across Donetsk. With an h-index of 14, his influence in engineering research is substantial and growing .

Research Skill

Dr.  Nikolay Kiktev possesses robust research skills spanning automation, control systems, data analytics, and software-hardware integration . He is highly skilled in designing and modeling technological processes using modern CAD tools, developing distributed control systems, and implementing intelligent automation solutions . His expertise in electrochemical process modeling, experimental design, and algorithm development makes him a multidisciplinary innovator . He actively engages in patent drafting, system simulation, and software architecture for process management systems . With strong programming and data handling skills, he supervises student projects in data analytics and smart technology integration . His research involves cross-platform system development, geoinformatics, and IoT-based autonomous systems . As a seasoned educator, he imparts practical research techniques and computational methods to graduate and doctoral students . His contributions have strengthened Ukraine’s capacity in smart infrastructure and AI-enhanced automation systems .

Publication Top Notes

Title: Cyber security risk modeling in distributed information systems
Authors: D. Palko, T. Babenko, A. Bigdan, N. Kiktev, T. Hutsol, M. Kuboń, H. Hnatiienko, …
Journal: Applied Sciences, 2023
Citations: 43

Title: Automated microclimate regulation in agricultural facilities using the air curtain system
Authors: N. Kiktev, T. Lendiel, V. Vasilenkov, O. Kapralуuk, T. Hutsol, S. Glowacki, …
Journal: Sensors, 2021
Citations: 30

Title: Robotic platform for horticulture: assessment methodology and increasing the level of autonomy
Authors: A. Kutyrev, N. Kiktev, M. Jewiarz, D. Khort, I. Smirnov, V. Zubina, T. Hutsol, …
Journal: Sensors, 2022
Citations: 27

Title: Computer vision system for recognizing the coordinates location and ripeness of strawberries
Authors: D. Khort, A. Kutyrev, I. Smirnov, V. Osypenko, N. Kiktev
Conference: Int’l Conf. on Data Stream Mining and Processing, 2020
Citations: 27

Title: Robotized platform for picking of strawberry berries
Authors: D. Khort, A. Kutyrev, R. Filippov, N. Kiktev, D. Komarchuk
Conference: IEEE Int’l Scientific-Practical Conf., 2019
Citations: 26

Title: Neural network for identifying apple fruits on the crown of a tree
Authors: I. Smirnov, A. Kutyrev, N. Kiktev
Journal: E3S Web of Conferences, 2021
Citations: 25

Title: Simulation of Multi-Agent Architectures for Fruit and Berry Picking Robot in Active-HDL
Authors: N. Kiktev, A. Didyk, M. Antonevych
Conference:IEEE PIC S&T, 2020
Citations: 22

Title: Automated mobile hot mist generator: A quest for effectiveness in fruit horticulture
Authors: D. Khort, A. Kutyrev, N. Kiktev, T. Hutsol, S. Glowacki, M. Kuboń, T. Nurek, …
Journal: Sensors, 2022
Citations: 21

Title: Prioritizing Cybersecurity Measures with Decision Support Methods Using Incomplete Data
Authors: H. Hnatiienko, N.A. Kiktev, T. Babenko, A. Desiatko, L. Myrutenko
Conference: ITS, 2021
Citations: 21

Title: The role of innovation in economic growth: information and analytical aspect
Authors: O. Kalivoshko, V. Kraevsky, K. Burdeha, I. Lyutyy, N. Kiktev
Conference: IEEE PIC S&T, 2021
Citations: 19

Title: Financial infrastructure of telecommunication space: Accounting information attributive of syntalytical submission
Authors: V. Kraevsky, O. Kostenko, O. Kalivoshko, N. Kiktev, I. Lyutyy
Conference: IEEE Int’l Conf., 2019
Citations: 19

Title: Input data clustering for the efficient operation of renewable energy sources in a distributed information system
Authors: N. Kiktev, V. Osypenko, N. Shkurpela, A. Balaniuk
Conference: IEEE CSIT, 2020
Citations: 16

Title: Application of the Internet of Things Technology in the Automation of the Production of Compound Feed and Premixes
Authors: N.A. Kiktev, T. Lendiel, V. Osypenko
Journal/Conference: IT&I, 2020
Citations: 14

Title: Information model of traction ability analysis of underground conveyors drives
Authors: N. Kiktev, H. Rozorinov, M. Masoud
Conference: IEEE PTMR, 2017
Citations: 14

Conclusion

Dr. Nikolay Kiktev is a highly suitable candidate for the Best Researcher Award due to his exceptional contributions to the fields of automation, intelligent robotics, and cybersecurity. His research portfolio demonstrates a rare blend of interdisciplinary strength, combining advanced machine learning techniques with practical applications in agricultural robotics, computer vision, and distributed systems security. Notably, his works such as “Cybersecurity Risk Modeling in Distributed Information Systems” and “Computer Vision for Recognizing Strawberry Ripeness” have been widely cited, reflecting both academic recognition and practical relevance. Dr. Kiktev has consistently focused on solving real-world problems developing automated systems for climate control in agriculture, intelligent subsystems for feed accounting, and IoT-driven architectures for horticultural monitoring.