Nikolay Kiktev | Computer Science | Best Researcher Award

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.

Chaoli Zhang | Computer Science | Best Researcher Award

Assist. Prof. Dr ChaoliZhang | Computer Science | Best Researcher Award

Lecturer at Zhejiang Normal University, China

Dr. Chaoli Zhang is a Lecturer at the College of Computer Science and Technology, Zhejiang Normal University . He received his Ph.D. in Computer Science and Technology from Shanghai Jiao Tong University  and has previously worked at Alibaba DAMO Academy as a Senior Engineer . With deep expertise in time series anomaly detection, intelligent systems, and wireless data center networks , he has authored several influential papers in top-tier conferences and journals like IEEE ToN, KDD, and CIKM . He holds multiple patents in AI-driven fault detection and data analysis . Known for blending academic excellence with industrial innovation , he actively contributes to national and provincial-level research projects. His work has earned him prestigious recognitions, including a championship in a global 5G fault localization challenge . Dr. Zhang continues to push the boundaries of AI applications in realworld intelligent systems .

🔹Professional Profile

GOOGLE SCHOLAR

🎓 Education & Experience

Dr. Zhang obtained his bachelor’s degree in Information Security and Law from Nankai University (2011–2015)  and earned his Ph.D. from Shanghai Jiao Tong University (2015–2020) in Computer Science and Technology . After completing his doctorate, he worked from 2020 to 2023 at the Machine Intelligence Lab of Alibaba DAMO Academy , where he led advanced AI projects related to anomaly detection and intelligent monitoring . Since January 2024, he has served as a Lecturer at Zhejiang Normal University, where he continues research in AI and teaches advanced computing topics . His education blends theoretical depth with multidisciplinary training, while his work experience bridges top-tier academia and cutting-edge industry R&D . This combination allows him to explore highly applied, intelligent systems with real-world impact .

📈 Professional Development

Dr. Zhang has demonstrated rapid professional growth through impactful roles in both academia and industry . At Alibaba DAMO Academy, he focused on intelligent systems for real-time anomaly detection in large-scale infrastructure . He has since transitioned into academia, taking a faculty role at Zhejiang Normal University where he now leads funded research projects on smart healthcare analytics and IoT anomaly diagnostics . His professional development is characterized by an emphasis on translational research—converting algorithms into deployable solutions for real-world systems . As a project leader, he has secured competitive funding from the Zhejiang Natural Science Foundation and municipal science programs . Dr. Zhang regularly presents at global conferences (e.g., KDD, CIKM), reflecting his active engagement with the international research community . With a strong portfolio of publications, patents, and leadership, his professional path exemplifies AI-driven innovation and academic-industrial synergy .

🧠 Research Focus

Dr. Chaoli Zhang’s research interests lie at the intersection of time series anomaly detection, intelligent computing, and wireless data center networks . He develops novel algorithms for fault root cause analysis, time-frequency decomposition, and multivariate data analysis . His work on models like TFAD and DCdetector introduces advanced methods combining attention mechanisms, contrastive learning, and decomposition techniques for real-time monitoring . His recent projects also explore heterogeneous IoT anomaly detection and healthcare time series analysis, contributing to the development of robust, interpretable, and scalable AI systems . These innovations support applications in smart cities, cloud platforms, and industrial diagnostics ⚙️. With a foundation in graph modeling and deep learning, Dr. Zhang’s research aims to enhance system resilience, operational intelligence, and automation reliability across complex environments .

🏅 Awards & Honors

Dr. Zhang has earned several notable awards that reflect the excellence and impact of his research work . He was the champion of the 2022 SP Grand Challenge on 5G network fault root cause localization, prevailing over 338 global teams . His practical AI deployment solutions earned him the AAAI/IAAI’23 Deployed Application Innovation Award, one of only 10 globally recognized projects that year . He holds multiple Chinese patents related to time series analysis and cloud-based diagnostic methods 🔬, underscoring his ability to translate theory into tangible technological advances. His papers have been featured in leading journals and conferences, where he served as first or co-first author (IEEE ToN, CIKM, KDD, TCS) . These accolades highlight his cross-domain innovation, commitment to real-world impact, and leadership in the intelligent systems community .

🔹Publication of Top Notes

1.Transformers in Time Series: A Survey

Authors: Q. Wen, T. Zhou, C. Zhang, W. Chen, Z. Ma, J. Yan, L. Sun
Year: 2023
Citations: 1328

2.DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection

Authors: Y. Yang, C. Zhang, T. Zhou, Q. Wen, L. Sun
Year: 2023
Citations: 225

3.Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

Authors: K. Zhang, Q. Wen, C. Zhang, R. Cai, M. Jin, Y. Liu, J.Y. Zhang, Y. Liang, …
Year: 2024
Citations: 222

4.Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook

Authors: M. Jin, Q. Wen, Y. Liang, C. Zhang, S. Xue, X. Wang, J. Zhang, Y. Wang, …
Year: 2023
Citations: 166

5. Large Language Models for Education: A Survey and Outlook

Authors: S. Wang, T. Xu, H. Li, C. Zhang, J. Liang, J. Tang, P.S. Yu, Q. Wen
Year: 2024
Citations: 146

6.TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis

Authors: C. Zhang, T. Zhou, Q. Wen, L. Sun
Year: 2022
Citations: 106

7.A Survey on Diffusion Models for Time Series and Spatio-Temporal Data

Authors: Y. Yang, M. Jin, H. Wen, C. Zhang, Y. Liang, L. Ma, Y. Wang, C. Liu, B. Yang, …
Year: 2024
Citations: 76

8.LogiCoT: Logical Chain-of-Thought Instruction-Tuning

Authors: H. Liu, Z. Teng, L. Cui, C. Zhang, Q. Zhou, Y. Zhang
Year: 2023
Citations: 51

9. Transformers in Time Series: A Survey (arXiv version)

Authors: Q. Wen, T. Zhou, C. Zhang, W. Chen, Z. Ma, J. Yan, L. Sun
Year: 2022
Citations: 45

10. Bringing Generative AI to Adaptive Learning in Education

Authors: H. Li, T. Xu, C. Zhang, E. Chen, J. Liang, X. Fan, H. Li, J. Tang, Q. Wen
Year: 2024
Citations: 43

11.Pricing and Allocation Algorithm Designs in Dynamic Ridesharing System

Authors: C. Zhang, J. Xie, F. Wu, X. Gao, G. Chen
Year: 2020
Citations: 35

12.Transformers in Time Series: A Survey (repeat entry, possibly updated citation)

Authors: Q. Wen, T. Zhou, C. Zhang, W. Chen, Z. Ma, J. Yan, L. Sun
Year: 2023
Citations: 23

13.AHPA: Adaptive Horizontal Pod Autoscaling on Alibaba Cloud Kubernetes

Authors: Z. Zhou, C. Zhang, L. Ma, J. Gu, H. Qian, Q. Wen, L. Sun, P. Li, Z. Tang
Year: 2023
Citations: 22

14.Free Talk in the Air: A Hierarchical Topology for 60 GHz Wireless Data Center Networks

Authors: C. Zhang, F. Wu, X. Gao, G. Chen
Year: 2017
Citations: 19

15.Logical Reasoning in Large Language Models: A Survey

Authors: H. Liu, Z. Fu, M. Ding, R. Ning, C. Zhang, X. Liu, Y. Zhang
Year: 2025
Citations: 14

16.Online Auctions with Dynamic Costs for Ridesharing

Authors:C. Zhang, F. Wu, X. Gao, G. Chen
Year:2017
Citations:14

17.NetRCA: An Effective Network Fault Cause Localization Algorithm

Authors: C. Zhang, Z. Zhou, Y. Zhang, L. Yang, K. He, Q. Wen, L. Sun
Year: 2022
Citations: 13

📌 Conclusion 

Dr. Chaoli Zhang exemplifies the ideal recipient of the Best Researcher Award due to his proven research excellence, industry-validated innovations, and impactful contributions across multiple disciplines. His work seamlessly bridges the gap between theoretical advancements and real-world applications, particularly in artificial intelligence, anomaly detection, and time series analysis. With a strong publication record in top-tier journals and conferences, and recognized achievements such as the SP Grand Challenge 2022 and the AAAI/IAAI Innovation Award, Dr. Zhang has demonstrated both academic depth and practical relevance. His leadership in developing AI-driven solutions for complex, large-scale systems solidifies his standing as one of the top emerging voices in the field. These accomplishments collectively make him exceptionally worthy of recognition as a Best Researcher Award.