Zhuoying You | Economics of Innovation | Best Researcher Award

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Assist. Prof. Dr. Zhuoying You | Economics of Innovation | Best Researcher Award

Assistant Professor | Fuyao University of Science and Technology | China

Assist. Prof. Dr. Zhuoying You is an emerging scholar in the fields of technological innovation, sustainability, artificial intelligence, and international business. His research bridges the intersections of innovation systems, regional development, and political influences, with a strong emphasis on patent data analysis and large-scale quantitative research. He has built a reputation for impactful, interdisciplinary work that contributes to both academic discourse and policy development

Professional Profile

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Education

Dr. You earned his Ph.D. in Economics and Business from KU Leuven, graduating with distinction and actively contributing as a research member at the KU Leuven Urban Studies Institute. He pursued an MSc in Business Strategy and Innovation Management from the University of Southampton, also with distinction, and completed his undergraduate studies in E-Commerce and English at the Henan University of Economics and Law, where he graduated with distinction. His academic development was further enriched by visiting research positions at the University of Pisa and the London School of Economics

Experience

Dr. You is currently an Assistant Professor at Fuyao University of Science and Technology. He previously held a Postdoctoral Research Fellowship at Bocconi University, contributing to European Commission-funded projects on sustainability and toxic chemical regulation. He has also participated in research projects supported by the Belgian Flanders Government, where he investigated Industry technologies and their impact on economic performance. His teaching experience spans strategic innovation management, business research methods, and innovation and digital transformation, where he has lectured and mentored students across bachelor’s and master’s levels

Research Interests

Dr. You’s primary research interests lie in technological innovation, sustainability transitions, artificial intelligence, and the political economy of innovation. His methodological expertise includes patent and publication data analysis, text mining, spatial regression, and large quantitative dataset modeling. He actively engages in international research collaborations, investigating areas such as green technology specialization, industrial transformation, and the sustainability of small and medium-sized enterprises

Honors

His academic excellence has been recognized through multiple awards and fellowships, including competitive scholarships from the Academy of Management, Bocconi University, the London School of Economics, and KU Leuven. He has also received European mobility funding and summer fellowships for early career researchers, reflecting his strong international recognition and research promise.

Top Noted Publications

The political extremes and innovation: How support for extreme parties shapes overall and green scientific research and technological innovation in Europe – Published in Research Policy, indexed in Scopus and Web of Science, 2025.

Heterogeneous influences of specialization and diversification on regional R&D performance: a China, Europe, and US comparison – Published in Science and Public Policy, indexed in Scopus and Web of Science, DOI: 10.1093/scipol/scae059, 2024.

Specialization in climate technologies at the regional level in Europe: relatedness and the moderating role of policy direction – Published in Technological Forecasting and Social Change, indexed in Scopus and Web of Science, DOI: 10.1016/j.techfore.2024.123348, 2024.

Diversification and Multilevel Policy Support as Enablers of Specialization in Green Technologies – Published in Academy of Management Proceedings, DOI: 10.5465/AMPROC.2023.12074abstract, 2023.

The Double-Edged Sword: The Impact of Covid-19 on Digital Transformation of Chinese SMEs – Published in Journal of Frontiers of Society, Science and Technology, indexed in Crossref, 2021.

Bridging the innovation gap. AI and robotics as drivers of China’s urban innovation – Published by Utrecht University, Department of Human Geography and Planning, selected by CEPR VoxEU and World Commerce Review, 2024

Conclusion

Through his academic journey, Dr. You has established himself as a promising voice in innovation and sustainability research. His international collaborations, strong publication record, and involvement in funded research projects underscore his capacity to advance both scholarly knowledge and policy applications. With a focus on bridging technology, politics, and sustainability, he continues to make significant contributions to global academic and societal debates. His future trajectory points toward becoming a leading figure in the interdisciplinary study of innovation and economic development.

Assoc. Prof. Dr Linchang Zhao | Computer Science | Best Researcher Award |

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Assoc. Prof. Dr Linchang Zhao | Computer Science | Best Researcher Award

Guiyang University, at School of Computer Science, China.

Assoc. Prof. Dr. Linchang Zhao is an accomplished academic and researcher at Guiyang University in China, specializing in machine learning, deep learning, few-shot learning, and optimization algorithms. He holds a Ph.D. in Computer Science from Chongqing University, with additional degrees in Mathematics and Statistics, and Computer Science. Dr. Zhao’s research focuses on data mining, imbalanced learning, and software defect prediction, where he has made significant contributions through innovative techniques like cost-sensitive meta-learning classifiers and deep neural networks. His work has been widely published in prominent journals such as IEEE Access and Neurocomputing, and he holds patents related to small sample data learning and imbalanced data prediction. With experience as a graduate tutor and mentor, Dr. Zhao continues to shape the next generation of researchers while actively contributing to high-impact projects funded by the National Natural Science Foundation of China.

Professional Profile

Scopus

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Education 🎓

Dr. Linchang Zhao completed his Ph.D. in Computer Science from Chongqing University (2017–2021), where he focused on advancements in deep learning and machine learning. He also holds a Master of Engineering in Mathematics and Statistics from Qiannan Normal College for Nationalities (2015–2017) and a Bachelor of Science in Computer Science from Northeast Petroleum University (2009–2013).

Experience 💼

Dr. Zhao currently serves as an Associate Professor and graduate tutor at Guiyang University, where he mentors students and leads research initiatives. His academic career is highlighted by his active participation in several high-impact projects, including those funded by the National Natural Science Foundation of China. His work on machine learning, especially in software defect prediction and optimization, has garnered attention in both academic and industrial circles.

Research Interest 🔬

Dr. Zhao’s research primarily revolves around machine learning, few-shot learning, deep learning, optimization algorithms, and meta-learning. He is particularly interested in data mining, imbalanced learning, and software defect prediction, using cutting-edge techniques such as cost-sensitive meta-learning classifiers and deep neural networks. His work aims to address challenges in real-world applications, particularly in small datasets and imbalanced data contexts.

Award 🏅

Throughout his career, Dr. Zhao has made substantial contributions to his field, earning recognition for his innovative research. He has been awarded various honors for his work on software defect prediction and cost-sensitive machine learning methods. His contributions to machine learning in the context of small sample data and imbalanced datasets have been highly praised.

Top Noted Publication 📑

Design and Implementation of GPU Pass-Through System Based on OpenStack Computation

Authors: Linchang Zhao, Yu Jin, Guoqing Hu, Wenxi Zhou, Hao Wei, Ruiping Li, Xu Zhu, Yongchi Xu, Jiulin Jin, Qianbo Li

Journal: Computation

DOI: 10.3390/computation13020038

Year of Publication: 2025

 

RFAConv-CBM-ViT: Enhanced Vision Transformer for Metal Surface Defect Detection

Authors: Hao Wei, Linchang Zhao, Ruiping Li, Mu Zhang

Journal: The Journal of Supercomputing

DOI: 10.1007/s11227-024-06662-0

Year of Publication: 2025

 

Siamese Dense Neural Network for Software Defect Prediction With Small Data

Authors: Linchang Zhao, Zhaowei Shang, Ling Zhao, Anyong Qin, Yuan Yan Tang

Journal: IEEE Access

DOI: 10.1109/ACCESS.2018.2889061

Year of Publication: 2019

 

A Cost-Sensitive Meta-Learning Classifier: SPFCNN-Miner

Authors: Linchang Zhao

Journal: Future Generation Computer Systems

DOI: 10.1016/j.future.2019.05.080

Year of Publication: 2019

 

Software Defect Prediction via Cost-Sensitive Siamese Parallel Fully-Connected Neural Networks

Authors: Linchang Zhao, Zhaowei Shang, Ling Zhao, Taiping Zhang, Yuan Yan Tang

Journal: Neurocomputing

DOI: 10.1016/j.neucom.2019.03.076

Year of Publication: 2019

Conclusion

Linchang Zhao’s combination of advanced research, practical innovations, and contributions to education makes him a strong candidate for the Best Researcher Award. His ability to address real-world problems through machine learning and his efforts to foster academic growth through mentorship positions him as a leader in his field. To further solidify his position as a top researcher, increased interdisciplinary collaborations and global visibility would be beneficial.