Changxin Yu | Digital technology | Best Researcher Award

Dr. Changxin Yu | Digital technology
|Best Researcher Award

 

Dr at Beijing Institute of Technology ,China.

Changxin Yu is a Ph.D. candidate in Applied Economics at Beijing Institute of Technology. Her research bridges agricultural economics and digital technology, focusing on their combined impact on productivity, sustainability, and innovation. She has investigated public perceptions of GMOs, the role of R&D in Chinese pesticide firms, and the productivity effects of modern biotechnology. Yu applies empirical models, including machine learning, to analyze how digital technologies—such as industrial robots and digital trade—contribute to green development and economic transformation. Her work is published in leading journals, including Technological Forecasting and Social Change. With interdisciplinary expertise, she continues to explore how digital tools can enhance agricultural and manufacturing sector performance, contributing to China’s sustainable economic growth.


🌍 Professional Profile:

Scopus

🏆 Suitability for the Best Researcher Award

 

Changxin Yu exemplifies the qualities sought in a Best Researcher Award recipient. Her work seamlessly integrates applied economics, digital innovation, and sustainability—a rare and valuable interdisciplinary nexus. She has produced high-impact research on topics such as industrial robots’ role in green growth and the effect of digital trade on agricultural productivity. Her ability to apply cutting-edge empirical and machine learning techniques enhances the credibility and applicability of her findings. With several prestigious publications and international collaborations, her research has advanced understanding of sustainable development and digital adoption in agriculture and manufacturing. Yu’s academic rigor, innovative approach, and commitment to real-world challenges position her as a strong candidate for the award.

🎓 Education 

Changxin Yu has a robust academic background that spans economics, management, and agriculture. She is currently pursuing a Ph.D. in Applied Economics at Beijing Institute of Technology (2019–present), focusing on digital and green economic development. She also holds a Master’s degree in Management Science and Engineering (2017–2019) from the same institution. Her undergraduate education was completed at Beijing Forestry University, where she earned a Bachelor’s degree in Agricultural and Forestry Economic Management (2013–2017). Her multidisciplinary training enables her to address complex challenges across agricultural economics, digital transformation, and environmental sustainability. Through this academic trajectory, Yu has cultivated a deep understanding of the socioeconomic implications of digital tools in agriculture and industry, strengthening her research versatility.

🏢 Work Experience 

Changxin Yu has a diverse range of research experience rooted in interdisciplinary projects. She has worked on USDA-funded studies examining the impact of public and private R&D investment on total factor productivity in China. Her academic and project-based research focuses on digital adoption in agriculture, industrial innovation, and environmental sustainability. She has analyzed the economic effects of GMOs, digital trade, and robotics in manufacturing. Through these experiences, she has developed strong skills in data analysis, policy assessment, and empirical modeling. Yu’s contributions extend beyond academia to inform policy and innovation strategies in agriculture and industry. Her professional journey is marked by her involvement in internationally collaborative projects and publications in well-regarded scientific journals.

🏅 Awards and Honors 

While specific awards are not listed, Changxin Yu has earned academic recognition through her involvement in high-impact research projects and publications in reputable journals such as Technological Forecasting and Social Change. Her selection for a USDA-funded research initiative reflects her capabilities and potential for influencing policy and practice. Additionally, her ongoing doctoral research incorporates advanced econometric and machine learning techniques, distinguishing her in the field of applied economics. Yu’s research contributions have gained attention in academic and policy circles for their relevance to green development, digital transformation, and agricultural innovation. Given the scope and impact of her work, she is likely to be a strong contender for academic and research honors in the near future.

🔬 Research Focus 

Changxin Yu’s research sits at the intersection of applied economics, digital transformation, and sustainable development. She focuses on how digital technologies, such as industrial robots and digital trade platforms, impact agricultural productivity and green growth. Her current doctoral research investigates the effects of modern biotechnology on agricultural total factor productivity (TFP), using robust empirical and machine learning methods. Yu also examines the economic implications of public and private R&D investments, particularly in agriculture and manufacturing. Her work has explored public attitudes toward GMOs and the economic impact of carbon abatement via digitalization. By analyzing how emerging technologies reshape economic systems, her research provides valuable insights for policy makers, academics, and industries working toward sustainable innovation.

📊 Publication Top Notes:

Citation:
Deng, H., Yu, C., Pray, C. E., & Jin, Y. (Forthcoming). How is China Shaping Global Food Supply Chains? Insights from the Seed Industry. European Review of Agricultural Economics.

Authors:

  • Haiyan Deng

  • Changxin Yu

  • Carl E. Pray

  • Yanhong Jin* (Corresponding author)

Year:
Forthcoming (Accepted, not yet published)

Citation:
Deng, H., Huang, Z., Wu, J., Güneri, F., Shen, Z., & Yu, C.* (2025). Harnessing the power of industrial robots for green development: Evidence from China’s manufacturing industry. Technological Forecasting and Social Change, 215, 124099. https://doi.org/10.1016/j.techfore.2025.124099

Authors:

  • Haiyan Deng

  • Zhonghua Huang

  • Jian Wu

  • Fatma Güneri

  • Zhiyang Shen

  • Changxin Yu* (Corresponding author)

Year:
2025

Citation:
Hu, R., Yu, C., Jin, Y., Pray, C., & Deng, H. (2022). Impact of government policies on research and development (R&D) investment, innovation, and productivity: Evidence from pesticide firms in China. Agriculture, 12(5), 709. https://doi.org/10.3390/agriculture12050709

Authors:

  • Ruifa Hu

  • Changxin Yu

  • Yanhong Jin

  • Carl Pray

  • Haiyan Deng

Year:
2022

Hazrat Bilal | Robotics Engineering | Young Scientist Award

Dr. Hazrat Bilal |Robotics Engineering
| Young Scientist Award

Postdoctoral Research Fellow at Shenzhen University, China .

Dr. Hazrat Bilal is a highly accomplished researcher and Postdoctoral Fellow at Shenzhen University, China. With a Ph.D. in Control Science & Engineering from the University of Science & Technology of China, he brings exceptional expertise in intelligent robotics, deep learning, and fault diagnosis. Dr. Bilal has authored over 30 high-impact publications and has earned 1200+ citations (h-index: 12). His outstanding academic record is complemented by rich industry experience and several prestigious fellowships and awards. A dedicated IEEE member and registered engineer with PEC, he is passionate about pushing the boundaries of intelligent automation. His remarkable early-career accomplishments and leadership in research make him a strong candidate for the Young Scientist Award.

🌍 Professional Profile:

Scopus 

Orcid

Google scholar

🏆 Suitability for the Best Researcher Award


Dr. Hazrat Bilal is a highly deserving candidate for the Young Scientist Award, with an exceptional academic record (Ph.D., USTC, GPA 3.88/4.00; M.S., NUST, GPA 3.85/4.00). As a Postdoctoral Fellow at Shenzhen University, he has made significant contributions to intelligent robotics, fault diagnosis, and AI-driven control systems. With over 15 high-impact Q1/Q2 journal publications—including in the IEEE IoT Journal, Soft Computing, Bioengineering, and Human-centric Computing—his research demonstrates innovation and practical value. His interdisciplinary work in blockchain-enabled IoRT, fuzzy-ADRC control, and AI for medical and UAV systems reflects his leadership in emerging technologies. With over 1200 citations and global collaborations, Dr. Bilal stands out as a promising young researcher committed to advancing intelligent and sustainable technologies.

🎓 Education 

Dr. Hazrat Bilal’s academic journey reflects a commitment to excellence in engineering and research. He earned his Ph.D. in Control Science & Engineering from the University of Science & Technology of China (2018–2024), maintaining an exceptional GPA of 3.88/4.00. Prior to that, he completed his Master’s degree in the same field at Nanjing University of Science & Technology (2015–2018) with a GPA of 3.85/4.00 and received an Outstanding Graduate Certificate. His undergraduate studies in Electrical (Electronics) Engineering were completed at FUUAST Islamabad, Pakistan (2010–2014), earning a GPA of 3.18/4.00. This strong academic foundation underpins his work in robotics, automation, and advanced control systems.

🏢 Work Experience 

Dr. Bilal brings interdisciplinary and global experience from academia and industry. He worked as a Performance Software Engineer at ZF Friedrichshafen, Shanghai, where he developed vision algorithms and optimized embedded system performance. Prior to that, he served as a Telecom Engineer at Real Solution Pvt. Ltd., Pakistan, contributing to 3G system installations and RF optimization. He also worked at Dargai Hydropower Plant as a Control Engineer, where he led power generation and preventive maintenance operations. Additionally, he completed internships and technical training at the National Telecommunication Corporation, University of Tennessee (USA), and CAE Pakistan. These roles have refined his expertise in automation, control systems, robotics, and smart grid technologies.

🏅 Awards and Honors 

Dr. Hazrat Bilal has received numerous awards recognizing his academic excellence and innovation. He is a recipient of the CAS-TWAS Fellowship Award at USTC and the NMG-NUST Joint Scholarship for his master’s studies. His exceptional performance earned him the Outstanding Graduate Certificate from Nanjing University of Science & Technology. As an undergraduate, he was awarded scholarships from Akhuwat Foundation and Pakistan Bait-ul-Mal, along with a Prime Minister’s Laptop under the national scheme. He secured funding for his final-year project through the National Grassroots ICT R&D Program. Dr. Bilal also received a Letter of Appreciation from IEEE FUUAST and continues to excel as an IEEE member and professional contributor to engineering societies.

🔬 Research Focus 

Dr. Hazrat Bilal’s research lies at the intersection of robotic control systems, artificial intelligence, and fault diagnosis. His recent works emphasize hybrid deep learning algorithms for the Internet of Robotic Things (IoRT), adaptive control of flexible manipulators, and trajectory tracking. He has proposed advanced techniques integrating fuzzy logic, ADRC, CNNs, LSTMs, and blockchain for secure, intelligent, and resilient systems. His current research includes generative AI for traffic simulation, nanorobot control, and intelligent medical diagnosis using AI. Dr. Bilal’s work contributes significantly to the future of smart manufacturing, healthcare, and autonomous vehicles. His focus on interdisciplinary, experimental, and data-driven approaches positions him as a leader in intelligent control systems.

📊 Publication Top Notes:

  • Title: A data-driven approach for intrusion and anomaly detection using automated machine learning for the Internet of Things
    Authors: H. Xu, Z. Sun, Y. Cao, H. Bilal
    Journal: Soft Computing, 27(19), 14469–14481
    Citations: 172
    Year: 2023

  • Title: Pruning filters with L1-norm and capped L1-norm for CNN compression
    Authors: A. Kumar, A. M. Shaikh, Y. Li, H. Bilal, B. Yin
    Journal: Applied Intelligence, 51(2), 1152–1160
    Citations: 147
    Year: 2021

  • Title: A practical study of active disturbance rejection control for rotary flexible joint robot manipulator
    Authors: H. Bilal, B. Yin, M. S. Aslam, Z. Anjum, A. Rohra, Y. Wang
    Journal: Soft Computing, 27(8), 4987–5001
    Citations: 128
    Year: 2023

  • Title: Jerk-bounded trajectory planning for rotary flexible joint manipulator: an experimental approach
    Authors: H. Bilal, B. Yin, A. Kumar, M. Ali, J. Zhang, J. Yao
    Journal: Soft Computing, 27(7), 4029–4039
    Citations: 118
    Year: 2023

  • Title: Experimental validation of fuzzy PID control of flexible joint system in presence of uncertainties
    Authors: H. Bilal, W. Yao, Y. Guo, Y. Wu, J. Guo
    Conference: 2017 36th Chinese Control Conference (CCC), 4192–4197
    Citations: 115
    Year: 2017

  • Title: Real-time lane detection and tracking for advanced driver assistance systems
    Authors: H. Bilal, B. Yin, J. Khan, L. Wang, J. Zhang, A. Kumar
    Conference: 2019 Chinese Control Conference (CCC), 6772–6777
    Citations: 101
    Year: 2019

  • Title: Regional feature fusion for on-road detection of objects using camera and 3D-LiDAR in high-speed autonomous vehicles
    Authors: Q. Wu, X. Li, K. Wang, H. Bilal
    Journal: Soft Computing, 27(23), 18195–18213
    Citations: 90
    Year: 2023

  • Title: Reduction of multiplications in convolutional neural networks
    Authors: M. Ali, B. Yin, A. Kunar, A. M. Sheikh, H. Bilal
    Conference: 2020 39th Chinese Control Conference (CCC), 7406–7411
    Citations: 85
    Year: 2020

  • Title: Second-order convolutional network for crowd counting
    Authors: L. Wang, Q. Zhai, B. Yin, H. Bilal
    Conference: Fourth International Workshop on Pattern Recognition, 11198, 158–163
    Citations: 83
    Year: 2019

  • Title: A hybrid CEEMD-GMM scheme for enhancing the detection of traffic flow on highways
    Authors: H. Dou, Y. Liu, S. Chen, H. Zhao, H. Bilal
    Journal: Soft Computing, 27(21), 16373–16388
    Citations: 82
    Year: 2023

  • Title: Advanced efficient strategy for detection of dark objects based on spiking network with multi-box detection
    Authors: M. Ali, B. Yin, H. Bilal, A. Kumar, A. M. Shaikh, A. Rohra
    Journal: Multimedia Tools and Applications, 83(12), 36307–36327
    Citations: 50
    Year: 2024