Hadi Gokcen | Engineering | Best Researcher Award

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Prof. Hadi Gokcen | Engineering | Best Researcher Award

Professor | Gazi University Industrial Engineering Department | Turkey

Dr. Hadi Gökçen, affiliated with Gazi University, Ankara, Turkey, is a distinguished researcher recognized for his influential contributions to industrial engineering, operations research, and computational intelligence. With 51 published documents, an h-index of 23, and more than 1,920 citations from 1,367 citing documents, his scholarly impact spans data-driven decision systems, intelligent manufacturing, and applied artificial intelligence. His recent works reflect a strong integration of machine learning, optimization, and sustainability in solving real-world industrial and economic problems. In Computational Economics , he introduced a hybrid machine learning model that combines clustering and stacking ensemble approaches for improved real estate price prediction. His research published in Applied Sciences Switzerland, proposed a dynamic scheduling method for identical parallel-machine environments through a multi-purpose intelligent utility framework. In Flexible Services and Manufacturing Journal, he presented innovative balancing and sequencing strategies for mixed-model parallel robotic assembly lines, emphasizing energy-efficient production. Further, his Survey Review paper applied hybrid unsupervised learning to identify sub-real estate markets, enhancing prediction accuracy and market segmentation. His contribution to developing a Digital Transformation Perception Scale underscores his focus on organizational innovation and industrial adaptation within the Industry paradigm. Dr. Gökçen’s interdisciplinary research bridges artificial intelligence, optimization, and digital transformation, advancing the understanding and implementation of intelligent, sustainable, and adaptive systems in engineering and economic domains.

Profiles : ORCID | Scopus | Google Scholar 

Featured Publications

1. Demirel, N. Ö., & Gökçen, H. (2008). A mixed integer programming model for remanufacturing in reverse logistics environment. The International Journal of Advanced Manufacturing Technology, 39(11), 1197–1206.
Cited By : 258

2. Demirel, E., Demirel, N., & Gökçen, H. (2016). A mixed integer linear programming model to optimize reverse logistics activities of end-of-life vehicles in Turkey. Journal of Cleaner Production, 112, 2101–2113.
Cited By : 247

3. Gökçen, H., Ağpak, K., & Benzer, R. (2006). Balancing of parallel assembly lines. International Journal of Production Economics, 103(2), 600–609.
Cited By : 226

4. Gökçen, H. (2007). Yönetim bilgi sistemleri. Ankara: Palme Yayıncılık.
Cited By : 217

5. Erel, E., & Gökçen, H. (1999). Shortest-route formulation of mixed-model assembly line balancing problem. European Journal of Operational Research, 116(1), 194–204.
Cited By : 189

Sakshi Dua | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Sakshi Dua | Engineering | Best Researcher Award

Associate Professor | Lovely Professional University | India

Dr. Sakshi Dua is an accomplished academic and researcher currently serving as Associate Professor at the School of Computer Applications, Lovely Professional University, Jalandhar-Phagwara, Punjab, India. She holds a Ph.D. in Computer Science and has over 14 years of professional experience as Assistant Professor before her current role. Her research interests span artificial intelligence, Internet of Things, Arduino, machine learning, fuzzy systems, network operating systems, and database management systems. She has contributed as Guest Editor for reputed ABDC and Scopus-indexed journals, authored book chapters with CRC Press, Taylor & Francis, and IGI Global, and is actively involved in book editorial projects with CRC Press and Emerald. She has published widely in SCIE, Scopus, ABDC, and UGC-indexed journals, as well as in IEEE and Springer conferences, and has presented her research internationally. Her contributions extend to applied innovation with patents and copyrights in diverse areas such as smart healthcare, ICT, and IoT-based solutions. She has chaired sessions at IEEE conferences, delivered workshops and FDPs, and guided students through impactful academic and research projects. Her skills include advanced data analysis, algorithm design, applied AI and IoT development, research writing, and academic leadership. Dr. Sakshi Dua has earned recognition through her impactful scholarly work, editorial leadership, and strong community engagement. She has received 71 citations by 9 documents with an h-index of 1.

Profile :  Scopus

Featured Publication

1. Dua, S. (2025). Blockchain-based node authentication algorithm for securing electronic health record data transmission.

Yu Cheng Wang | Engineering | Best Research Article Award

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Assoc. Prof. Dr. Yu Cheng Wang | Engineering | Best Research Article Award

Aeronautical Engineering Of Chair at Chaoyang University of Technology | Taiwan

Prof. Dr. Yu Cheng Wang  is a distinguished academic and researcher, currently serving as Associate Professor and Chair of the Department of Aeronautical Engineering at Chaoyang University of Technology, Taiwan. He holds a Ph.D. in Industrial Engineering from Feng Chia University and has built a reputation for advancing research at the intersection of aeronautical systems, intelligent manufacturing, and explainable artificial intelligence. With more than publications in SCI and Scopus-indexed journals, his contributions have made significant impact in manufacturing optimization and decision-support systems. He has an h-index of  with over citations, reflecting the scholarly influence of his work. Prof. Wang also collaborates extensively with colleagues across Taiwan and internationally, bridging academic research and industry practice. His work on Industry 4.0 applications in semiconductor manufacturing showcases his commitment to developing transparent and human-centered AI systems that directly address real-world industrial challenges.

Professional Profile

ORCID Profile | Scopus Profile

Education 

Prof. Dr. Yu Cheng Wang pursued his academic journey with a focus on engineering, systems, and innovation. He earned his Ph.D. in Industrial Engineering from Feng Chia University, Taiwan, where his doctoral research laid the foundation for his expertise in intelligent systems and complex manufacturing processes. His educational background reflects a strong balance between theoretical modeling and applied problem-solving. Dr. Wang’s training emphasized operations research, production systems, and the integration of artificial intelligence into industrial applications, which later expanded into explainable AI frameworks for decision support. His solid grounding in industrial engineering principles has allowed him to extend his research into aeronautical systems and semiconductor manufacturing. With this interdisciplinary academic foundation, he has successfully bridged domains such as fuzzy theory, optimization, and smart manufacturing, enabling him to pursue pioneering research in Industry 4.0. His educational journey demonstrates a commitment to combining engineering rigor with innovative technological applications.

Experience 

Prof. Dr. Yu-Cheng Wang has extensive academic and professional experience that combines leadership, research, and industry collaboration. As Department Chair and Associate Professor at Chaoyang University of Technology, he oversees curriculum development, research strategy, and faculty mentorship in aeronautical engineering. His leadership extends to managing cross-disciplinary projects that integrate aeronautical engineering with intelligent manufacturing and artificial intelligence applications. He has spearheaded major research initiatives, including the Industry 4.0 XAI project for wafer-fab output forecasting, a groundbreaking effort that combines machine learning with interpretability for industrial decision-making. His experience also spans consultancy projects that provide practical solutions for semiconductor manufacturing, aligning academic research with industry needs. Prof. Wang’s editorial contributions over appointments demonstrate his recognition as a peer reviewer and thought leader in his field. Through collaborations with colleagues such as Tin-Chih Toly Chen and Chi-Wei Lin, he has broadened his international research presence and strengthened academia-industry knowledge exchange.

Research Interest

Prof. Dr. Yu-Cheng Wang’s research interests lie at the intersection of aeronautical engineering, smart manufacturing, and artificial intelligence. His primary focus is on explainable AI (XAI), where he develops models that not only achieve predictive accuracy but also provide transparency and interpretability for industrial decision-makers. He applies these methods to semiconductor manufacturing, Industry 4.0 environments, and production planning, ensuring that complex systems are optimized while remaining human-understandable. His work extends to fuzzy theory and decision analytics, particularly in contexts where uncertainty and complexity are critical, such as aerospace systems and large-scale industrial operations. Beyond manufacturing, Dr. Wang also explores applications of XAI in training and maintenance, including VR-based approaches for sustainable engineering education. By linking advanced computational models with practical engineering needs, his research contributes to both academic advancement and industry transformation, ensuring technological innovation supports efficiency, sustainability, and human factors integration.

Award and Honor

Prof. Dr. Yu-Cheng Wang has earned recognition for his scholarly contributions and leadership in the fields of aeronautical engineering and artificial intelligence. His publications in high-impact international journals such as The International Journal of Advanced Manufacturing Technology, Complex & Intelligent Systems, and Decision Analytics Journal highlight his academic influence and earned him strong citation metrics, with an h-index of 15 and more than citations. These achievements reflect his standing in the research community. His editorial appointments  across SCI and Scopus-indexed journals demonstrate the trust placed in him as a global reviewer and evaluator of cutting-edge research. He has also been actively involved in industry-driven projects, bridging academia and practical innovation, which further highlights his leadership. Recognition through research funding, collaborations, and invitations to contribute to international projects underscores his role as a thought leader. Collectively, these honors validate his impact as a forward-looking scientist and educator.

Research Skill

Prof. Dr. Yu Cheng Wang possesses a robust set of research skills that combine technical depth with interdisciplinary application. He is proficient in developing explainable AI frameworks, integrating advanced machine learning models with interpretability methods such as SHAP and rule-based surrogates to improve transparency in industrial decision systems. His expertise extends to fuzzy theory, production planning, and smart manufacturing analytics, making him adept at tackling complex and uncertain problems in both aeronautical and industrial domains. He has successfully applied these skills to semiconductor manufacturing, leading research on wafer-fab output forecasting that directly supports industry needs. In addition to computational modeling, Dr. Wang demonstrates strong skills in data analytics, simulation, and optimization, enabling him to bridge theory with real-world application. His experience with large-scale collaborations and consultancy projects further reflects his ability to integrate technical innovation with industry practices, positioning him as both a problem solver and research leader.

Publication Top Notes

Title: An explainable decision model for selecting facility locations in supply chain networks
Authors: Tin-Chih Toly Chen; Yu-Cheng Wang; Yi-Chi Wang
Journal: Supply Chain Analytics
Year: 2025

Title: Enhancing the effectiveness of output projection in wafer fabrication using an Industry 4.0 and XAI approach
Authors: Tin-Chih Toly Chen; Yu-Cheng Wang; Chi-Wei Lin
Journal: The International Journal of Advanced Manufacturing Technology
Year: 2024

Title: Adapted techniques of explainable artificial intelligence for explaining genetic algorithms on the example of job scheduling
Authors: Yu-Cheng Wang; Toly Chen
Journal: Expert Systems with Applications
Year: 2024

Title: Evaluating innovative future robotic applications in manufacturing using a fuzzy collaborative intelligence approach
Authors: Tin-Chih Toly Chen; Yu-Cheng Wang
Journal: The International Journal of Advanced Manufacturing Technology
Year: 2024

Title: A heterogeneous fuzzy collaborative intelligence approach: Air quality monitor selection study
Authors: Tin-Chih Toly Chen; Yu-Cheng Lin; Yu-Cheng Wang
Journal: Applied Soft Computing
Year: 2023

Title: Prediction of engine failure time using principal component analysis, categorical regression tree, and back propagation network
Authors: Yu-Cheng Wang
Journal: Journal of Ambient Intelligence and Humanized Computing
Year: 2023

Title: Improving people’s health by burning low-pollution coal to improve air quality for thermal power generation
Authors: Tin-Chih Toly Chen; Teng Chieh Chang; Yu-Cheng Wang
Journal: Digital Health
Year: 2023

Title: A selectively calibrated derivation technique and generalized fuzzy TOPSIS for semiconductor supply chain localization assessment
Authors: Toly Chen; Yu-Cheng Wang; Pin-Hsien Jiang
Journal: Decision Analytics Journal
Year: 2023

Title: New XAI tools for selecting suitable 3D printing facilities in ubiquitous manufacturing
Authors: Yu-Cheng Wang; Toly Chen
Journal: Complex & Intelligent Systems
Year: 2023

Title: A modified random forest incremental interpretation method for explaining artificial and deep neural networks in cycle time prediction
Authors: Toly Chen; Yu-Cheng Wang
Journal: Decision Analytics Journal
Year: 2023

Title: 3D Printer Selection for Aircraft Component Manufacturing Using a Nonlinear FGM and Dependency-Considered Fuzzy VIKOR Approach
Authors: Yu-Cheng Wang; Tin-Chih Toly Chen; Yu-Cheng Lin
Journal: Aerospace
Year: 2023

Title: An efficient approximating alpha-cut operations approach for deriving fuzzy priorities in fuzzy multi-criterion decision-making
Authors: Tin-Chih Toly Chen; Yu-Cheng Wang; Min-Chi Chiu
Journal: Applied Soft Computing
Year: 2023

Title: A novel auto-weighting deep-learning fuzzy collaborative intelligence approach
Authors: Yu-Cheng Wang; Tin-Chih Toly Chen; Hsin-Chieh Wu
Journal: Decision Analytics Journal
Year: 2023

Title: An explainable deep-learning approach for job cycle time prediction
Authors: Yu-Cheng Wang; Toly Chen; Min-Chi Chiu
Journal: Decision Analytics Journal
Year: 2023

Conclusion

Dr. Yu-Cheng Wang has consistently demonstrated academic excellence and research innovation across aeronautical engineering, explainable AI, and smart manufacturing systems. In publications in leading SCI/Scopus-indexed journals, an h-index of , and more than  citations, his work bridges theory with impactful industrial applications, particularly in semiconductor manufacturing and Industry 4.0 transformations. His leadership as Department Chair, coupled with collaborations with renowned scholars, highlights his influence on both research and education. Recognized for advancing interpretable AI for real-world adoption, Dr. Wang’s contributions embody the spirit of innovation, making him a strong and deserving candidate for the Best Researcher Award.

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.

Chaoli Zhang | Computer Science | Best Researcher Award

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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.

Salah Mokred | Engineering | Best Researcher Award

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Dr.Salah Mokred | Engineering | Best Researcher Award

PhD Candidate at Southeast university ,China

Salah Mokred is an accomplished electrical engineer and power systems researcher, currently pursuing his Ph.D. in Electrical Engineering at Southeast University, China . With deep expertise in  power system stability, analysis, and planning, he has contributed significantly through high-impact research and international publications . Salah holds a Master’s degree in Electric Power Systems from North China Electric Power University and a Bachelor’s from Sana’a University . He served as a teaching assistant at Sana’a University and has also worked on critical infrastructure projects involving Yemen’s national grid . Known for his commitment to innovation and resilience, Salah combines technical excellence with leadership and collaboration . His work has been recognized with multiple honors and CSC scholarships . Proficient in MATLAB, ETAP, and technical programming , Salah continues to drive forward cutting-edge research in voltage stability and smart grid protection technologies.

Professional Profile

ORCID

GOOGLE SCHOLAR

📘 Education and Experience 

Salah Mokred’s academic path began with a B.Sc. in Electrical Engineering from Sana’a University, Yemen (2009–2013) . He then pursued his M.Sc. in Electric Power Systems at North China Electric Power University (2017–2020) , and is currently finalizing his Ph.D. in Electrical Engineering at Southeast University (2020–2024) . His research focuses on power system stability and voltage collapse prediction . Professionally, he worked as a Teaching Assistant at Sana’a University (2014–2016)  and contributed to Yemen’s national grid security through a project analyzing high-voltage line attacks . Salah also served as an engineering consultant at Garmah Plastic Company in 2016–2017 . His practical experience blends academic excellence with field applications, especially in power grid protection and distribution system enhancement . Salah’s expertise extends to technical tools like MATLAB, ETAP, FORTRAN, and PLC systems .

📈 Professional Development 

Salah Mokred continually expands his professional skills through academic research, international conferences, and specialized training programs . He has completed training in English and programming at SEEDS Education Center , and undertaken advanced technical courses in PLC control, power grid analysis, and power system protection relay selection . Salah has actively participated in IEEE conferences, contributing to papers on voltage stability indices, capacitor bank applications, and intelligent grid technologies . His strong computer proficiency includes MATLAB, ETAP, C, FORTRAN, and MS Office tools . Salah also demonstrates strong leadership, communication, and teamwork skills, enabling him to contribute effectively to multidisciplinary research and collaborative engineering projects . He continues to advance professionally through scholarly publications in top-tier journals (SCI, Q1/Q3) and by collaborating with peers and mentors at Southeast University .

🔬 Research Focus

Salah Mokred’s research is rooted in the domain of Electrical Engineering, particularly in Power Systems . His focus lies in Voltage Stability Assessment, Contingency Ranking, and Optimal Placement of Distributed Generators (DGs) in power grids . Salah develops modern stability indices and collapse prediction methods that support the secure planning and operation of both transmission and distribution systems . His work blends theoretical modeling with real-world applications to improve grid reliability, especially in weak bus identification and dynamic loadability estimation . Salah has also explored series capacitor technologies, smart distribution systems, and intelligent protection schemes using fast-switch devices and relays . His innovative methodologies are helping reshape how engineers evaluate and strengthen power networks in volatile environments. His interdisciplinary approach involves simulation, grid modeling, and data-driven analysis using tools like MATLAB and ETAP .

🏆Awards and Honors 

Salah Mokred’s academic journey has been recognized with multiple prestigious honors . He received the CSC Scholarship twice: once for his Master’s studies (2017) and again for his Ph.D. (2020) in China . From 2021 to 2023, he was awarded Honor Certificates and the Academic Excellence Award by the Embassy of Yemen in recognition of his scholarly performance . Salah was honored with the Excellence Shield from the Yemenis Students Union for his role in academic programs and youth engagement initiatives . He also received a Certificate of Achievement from Garmah Plastic Company in 2017 for his engineering consulting contributions . Additionally, Salah participated in the “Youth in Nanjing” cultural exchange and was recognized for his contributions to international student engagement and creativity through events like “Star-Moon Dream Night” . These accolades highlight both his technical acumen and active involvement in cross-cultural academic life.

Publication of Top Notes

1.Title: Modern voltage stability index for prediction of voltage collapse and estimation of maximum loadability for weak buses and critical lines identification

Authors: S. Mokred, Y. Wang, T. Chen
Journal: International Journal of Electrical Power & Energy Systems
Year: 2023
Citations: 58

2.Title: A novel collapse prediction index for voltage stability analysis and contingency ranking in power systems

Authors: S. Mokred, Y. Wang, T. Chen
Journal: Protection and Control of Modern Power Systems
Year: 2023
Citations: 44

3.Title: Voltage stability assessment and contingency ranking in power systems based on modern stability assessment index

Authors: S. Mokred, Y. Wang
Journal: Results in Engineering
Year: 2024
Citations: 14

4.Title: Comparison of the effect of series and shunt capacitor application in 25kV radial power distribution network

Authors: S. Mokred, Q. Lijun, G. Kamara, T. Khan
Conference: IEEE/IAS I&CPS Asia
Year: 2020
Citations: 10

5.Title: Protection performance during application of an intelligent and fast switch series capacitor to 25kV radial power distribution network

Authors: S. Mokred, Q. Lijun, T. Khan
Conference: IEEE/IAS I&CPS Asia
Year: 2020
Citations: 8

6.Title: Transient and protection performance of a fixed series compensated 500 kV transmission line during various types of faulty conditions

Authors: S. Mokred, Q. Lijun, T. Khan
Journal: Journal of Electrical Engineering & Technology
Year: 2021
Citations: 7

7.Title: Voltage stability estimation for complex power system based on modal analytical techniques

Authors: M.M.A. Seedahmed, S.A.S. Mokred, G. Kamara
Conference: IEEE SPIN Conference
Year: 2019
Citations: 7

8.Title: Smart design of distribution series capacitor bank application for improved voltage quality and motor start

Authors: S. Mokred, Q. Lijun, G. Kamara
Conference: IEEE/IAS I&CPS Asia
Year: 2020
Citations: 6

9.Title: Protection and Impact of Series Compensation Technology in High Voltage Transmission Line

Authors: S.A.S. Mokred, Q. Lijun, M. Ali
Journal: IJIEEE
Year: 2019
Citations: 3

10.Title: A Novel Approach for Voltage Stability Assessment and Optimal Siting and Sizing of DGs in Radial Power Distribution Networks

Authors: S. Mokred, Y. Wang, M. Alruwaili, M.A. Ibrahim
Journal: Processes
Year: 2025
Citations: Not yet available

Conclusion

Dr. Salah Mokred’s consistent academic excellence, strong citation record, impactful contributions to voltage stability and grid protection, and participation in IEEE conferences and journal leadership make him a standout candidate for the Best Researcher Award. His research not only advances theory but provides applicable solutions to power system challenges in both developing and developed countries.