Tomohiro Hayashida | Machine Learning | Best Researcher Award

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Prof. Tomohiro Hayashida | Machine Learning
| Best Researcher Award

Professor at Hiroshima University , Japan.

Professor Tomohiro Hayashida is a distinguished scholar in decision-making, machine learning, and optimization, currently serving at Hiroshima University. After earning his Master’s and Ph.D. in Engineering from the same institution, he joined the university as a Research Associate in 2006 and steadily rose to Full Professor by 2024. With over 80 academic publications, Prof. Hayashida has led competitive national research grants and worked on practical innovations in transportation and scheduling algorithms. His interdisciplinary collaborations span across academia and industry, reflecting his commitment to both theoretical advancements and real-world applications. His citation record, leadership in JSPS-funded projects, and role in applied AI solutions exemplify his deep impact in computational engineering and operations research.

🌍 Professional Profile:

Scopus

🏆 Suitability for the Best Researcher Award :

Prof. Tomohiro Hayashida exemplifies the qualities deserving of the Best Researcher Award. He has produced over 50 peer-reviewed journal papers, many in top-tier SCI/Scopus-indexed journals. As Principal Investigator of multiple JSPS KAKEN-funded projects, including those in evolutionary computing and dynamic systems, he has shown consistent research leadership. His collaborative work with industry, such as optimizing dispatch algorithms with SmartRyde Inc., demonstrates strong translational research. With an h-index around 11–12 and 442+ citations, he balances scholarly excellence and societal impact. His active role in multi-disciplinary collaborations—both domestic and international—further reinforces his stature as an innovative and impactful researcher, making him highly suitable for the Best Researcher Award.

🎓 Education :

Prof. Hayashida received his entire higher education from Hiroshima University. He completed his Master’s degree in Engineering in 2006 and subsequently pursued and earned his Ph.D. in Engineering. His academic training focused on optimization theory, intelligent systems, and operations research, equipping him with a robust foundation in both theoretical and applied research. The university’s focus on computational intelligence and engineering sciences helped shape his research vision early in his career. His seamless transition from student to researcher within the same academic institution showcases his consistent excellence and growth as a scholar. This strong academic grounding laid the basis for his long-term contributions to machine learning, decision sciences, and interdisciplinary engineering research.

🏢 Work Experience :

Prof. Tomohiro Hayashida began his academic career in 2006 as a Research Associate at Hiroshima University, immediately after earning his Master’s degree. He was promoted to Assistant Professor in 2007, Associate Professor in 2015, and Full Professor in 2024. He has over 18 years of academic experience in teaching, research, and supervision. Beyond academic duties, he is active in government-funded research and industry collaborations, such as the ride-hailing optimization project with SmartRyde Inc. He also contributes to the Digital Manufacturing Education and Research Center at Hiroshima University. His extensive experience in both research project leadership and educational innovation showcases a balanced, impactful academic career with national and international influence.

🏅Awards and Honors

While specific award titles are not publicly listed, Prof. Hayashida’s selection as Principal Investigator for multiple highly competitive JSPS KAKEN Grants—including Young Researcher awards and Scientific Research (C) projects—reflects significant national recognition of his research excellence. His promotion to Full Professor at Hiroshima University, a top-tier Japanese institution, itself is a mark of academic distinction. He has been entrusted with strategic roles in collaborative projects, some of which have gained media coverage, such as the SmartRyde dispatch algorithm. These achievements, combined with a strong citation record and presence in high-impact journals, serve as implicit acknowledgment of his contributions to AI, optimization, and applied decision-making sciences within both academic and practical domains.

🔬 Research Focus :

Prof. Hayashida’s research centers on decision-making, machine learning, optimization, and evolutionary computation. His work addresses complex real-world problems like multi-objective scheduling, group decision analysis, and dynamic system optimization. Through JSPS-funded projects, he has developed algorithms for adaptive agents, cooperative enterprises, and evolutionary scheduling. His recent collaborations include intelligent systems for ride-hailing and dynamic dispatching. He integrates mathematical modeling with practical applications, focusing on AI-driven solutions for industries such as energy systems and transportation. His interdisciplinary approach merges operations research, computer science, and systems engineering. With over 80 publications and national/international partnerships, his research advances both academic knowledge and technological innovation, particularly in adaptive, data-driven decision systems.

📊 Publication Top Notes:

📘 Integrated Optimization Method for Task Allocation and Hierarchical Reinforcement Learning in Cargo Transport Robots
🗓️ Year: 2025 | 📚 Journal: IEEJ Transactions on Electronics Information and Systems |

📄 Constrained-multiobjective Evolutionary Algorithm for Distribution System Reconfiguration under Severe Constraints
🗓️ Year: 2025 | 📚 Conference Paper |

🚚 Integrating Task Allocation and Hierarchical Reinforcement Learning for Optimized Cargo Transport Routing
🗓️ Year: 2025 | 📚 Conference Paper |

⚡ Distribution System Reconfiguration by an Evolutionary Algorithm using Constraint-Guided Dominance and Archive-Based Individual Preservation Strategy
🗓️ Year: 2024 | 📚 IEEJ Transactions on Power and Energy |

📊 Expectation and Fractile Models for Decentralised Distribution Systems under Demand Uncertainty and their Computational Methods
🗓️ Year: 2024 | 📚 International Journal of Operational Research |

🎓 WIP: Machine Learning Models for Predicting Student Performance in IoT-Enhanced Education
🗓️ Year: 2024/2025 | 📚 Conference Paper |

📈 WIP: Study on a Data-Driven Adaptive Learning Support System Design for Individualized Optimal Learning
🗓️ Year: 2024/2025 | 📚 Conference Paper |

Jyh-Rong Chou | Emerging Technologies | Best Researcher Award

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Prof. Dr. Jyh-Rong Chou | Emerging Technologies
| Best Researcher Award

Professor at I-Shou University, Taiwan.

Dr. Jyh-Rong Chou is a distinguished professor in the Department of Creative Product Design and the Dean of the College of Communication and Design at I-Shou University, Taiwan. He has been serving as the Executive Director of the International Association of Organizational Innovation (IAOI, USA) since 2007. With a Ph.D. and M.S. in Industrial Design from National Cheng Kung University, Dr. Chou has contributed extensively to creative design research, user experience, and decision-making methodologies using Fuzzy and Gray theories. He has published prolifically in top-tier international journals and actively reviews for prestigious publications in design, engineering, and decision sciences. Dr. Chou’s interdisciplinary approach bridges design innovation with usability and sustainability, earning him national and international recognition.

🌍 Professional Profile:

ORCID

Scopus

🏆 Suitability for the Best Researcher Award :

Dr. Jyh-Rong Chou is an exemplary candidate for the Best Researcher Award due to his sustained academic excellence, innovative research contributions, and leadership in design education. His pioneering work in integrating Fuzzy Set Theory, TRIZ, and usability engineering into creative product design has advanced both theory and practice. As a prolific author and active reviewer for high-impact journals, he significantly influences global research trends. His role as Dean and Executive Director of IAOI reflects his commitment to fostering academic and industrial collaboration. Dr. Chou’s dedication to interdisciplinary research, user-centered innovation, and sustainable design aligns perfectly with the award’s values, showcasing his impactful contributions to design science and technology.

🎓 Education :

Dr. Jyh-Rong Chou completed his academic training entirely at the prestigious National Cheng Kung University in Tainan, Taiwan. He earned his Ph.D. in Industrial Design between 2002 and 2004, focusing on innovation methodologies and human-centered design. Prior to that, he obtained an M.S. in Industrial Design (1992–1994), where he developed his foundational knowledge in ergonomics and product development. His undergraduate studies were also in the Department of Industrial Design at the same institution (1989–1992), laying the groundwork for his academic and professional journey. This rigorous and consistent educational background has shaped Dr. Chou into a multifaceted expert in creative design, decision science, and usability engineering.

🏢 Work Experience :

Dr. Chou has over two decades of academic and professional experience in industrial and product design. He currently serves as Professor in the Department of Creative Product Design and as Dean of the College of Communication and Design at I-Shou University. Since 2007, he has also held the role of Executive Director at the International Association of Organizational Innovation (IAOI, USA), promoting global research collaboration. His experience spans teaching, academic leadership, industry consultancy, and editorial duties for top journals. He has supervised numerous research projects, published widely, and contributed to curriculum development in creative design and usability. His extensive experience demonstrates his capacity to lead research and education with innovation and interdisciplinary impact.

🏅 Awards and Honors :

Dr. Jyh-Rong Chou has received numerous recognitions for his research excellence and academic leadership. He is a frequent reviewer for internationally reputed journals such as Journal of Mechanical Design, Journal of Cleaner Production, Advanced Engineering Informatics, and others. His appointment as Executive Director of IAOI (USA) since 2007 highlights his leadership in fostering global innovation. Dr. Chou has been repeatedly invited to international conferences and editorial boards, reflecting peer recognition of his expertise in fuzzy logic, decision-making, and product-service systems. Though specific award names are not listed, his record of publications, professional appointments, and peer recognition positions him among the most influential scholars in creative industrial design and applied decision science.

🔬 Research Focus :

Dr. Chou’s research is centered on integrating advanced decision-making tools like Fuzzy Set Theory and Gray Theory into creative product design and innovation processes. His work spans TRIZ methodology, usability engineering, ergonomics, and user experience (UX) optimization. He also explores Life Cycle Engineering and Product-Service Design, contributing to sustainable and human-centric innovations. His interdisciplinary research bridges design theory and engineering practice, enabling more intelligent, efficient, and user-friendly products. By applying quantitative methods to subjective user perceptions and complex design problems, Dr. Chou advances both academic knowledge and practical solutions in product development. His research fosters innovation that is both technically sound and emotionally resonant with users.

📊 Publication Top Notes:

📘 A TRIZ-based product-service design approach for developing innovative products
Year: 2021 📑 Cited by: [Check Crossref/Scopus] 🛠️💡

🌍 A Scoping Review of Ontologies Relevant to Design Strategies in Response to the UN Sustainable Development Goals (SDGs)
Year: 2021 📑 Cited by: [Check Crossref] 🌱🎯

📊 A psychometric user experience model based on fuzzy measure approaches
Year: 2018 📑 Cited by: [Check Scopus] 🤖🧠

📉 Performance evaluation of special education in China based on Data Envelopment Analysis
Year: 2018 📑 Cited by: [Check Scopus] 📚🇨🇳

🔍 Kansei Clustering Using Fuzzy and Grey Relation Algorithms
Year: 2015 📑 Cited by: [Check Journal Metrics] 🎨📈

Senghor Tagouegni | Complex Systems | Best Researcher Award

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Dr. Senghor Tagouegni | Complex Systems
| Best Researcher Award

 Doctor at The University of Yaounde 1 (UY1), Cameroon.

Dr. Senghor TAGOUEGNI, a Cameroonian physicist, holds a Ph.D. in Physics from the University of Yaoundé I, with a specialization in Mechanics, Materials, and Complex Systems. As a dedicated educator at GBHS Akono, he contributes to academic excellence while pursuing advanced research in nonlinear dynamics, quantum processing, and parity-time symmetry systems. His scholarly contributions span electrical transmission lines, oscillators, and condensed matter physics. Fluent in both French and English, Dr. TAGOUEGNI is also a proficient programmer and scientific software user. His recent work on PT/APT-symmetric electronic systems demonstrates originality, rigor, and relevance to emerging technologies. These qualities, along with his consistent academic growth and leadership, make him a strong candidate for the Best Researcher Award.

🌍 Professional Profile:

ORCID

Scopus

🏆 Suitability for the Best Researcher Award :

Dr. Senghor TAGOUEGNI is a dedicated physicist whose research combines advanced theoretical physics with practical applications in nonlinear dynamics, parity-time symmetry systems, and quantum processing. His Ph.D. work, awarded with the distinction “Very Honourable,” focused on PT/APT-symmetric electronic systems and their implications in wave transport phenomena—an area of growing global interest. In addition to his teaching role at GBHS Akono, he actively engages in research, science education, and academic leadership. Fluent in French and English and highly proficient in scientific computing tools like Matlab, Maple, and LTSpice, Dr. TAGOUEGNI demonstrates consistent innovation and commitment to scientific advancement. His interdisciplinary expertise and impactful contributions make him a highly suitable candidate for the Best Researcher Award

🎓 Education :

Dr. Senghor TAGOUEGNI earned his Ph.D. in Physics in December 2022 from the University of Yaoundé I, specializing in Fundamental Mechanics and Complex Systems. His thesis explored PT/APT-symmetric electronic systems in wave transport phenomena, addressing critical topics like Anderson Localization and Electromagnetically Induced Transparency. He previously obtained a Master of Science degree in Fundamental Mechanics and Complex Systems in January 2015, also from the University of Yaoundé I. His academic journey began with a Bachelor of Science in Physics in 2010, followed by a professional teaching diploma (DIPES I) from the Higher Teacher Training School (ENS), Yaoundé. His solid academic background lays a strong foundation for advanced interdisciplinary research and effective science education.

🏢 Work Experience :

Dr. Senghor TAGOUEGNI currently serves as a Physics, Chemistry, and Technology teacher at GBHS Akono in the Mefou and Akono Division. He has several years of experience teaching science subjects at the secondary and high school levels, effectively combining pedagogy with research. His educational background from ENS and advanced degrees in physics have enabled him to design and implement complex scientific concepts in classrooms with clarity. He also plays a leadership role as General Secretary of AMIPLYBAK, contributing to staff welfare and educational coordination. Beyond his academic roles, he is an active science communicator and mentor, fostering a research-driven culture among students and peers while maintaining active involvement in national scientific networks.

🏅 Awards and Honors :

Dr. Senghor TAGOUEGNI received the grade “Very Honourable” for his Ph.D. in Physics from the University of Yaoundé I in December 2022, reflecting his academic excellence and research depth. His work has garnered recognition for addressing advanced and emerging physics topics such as parity-time symmetry and quantum transport phenomena. As General Secretary of AMIPLYBAK, he has been acknowledged for his leadership and organizational service within the education sector. His commitment to scientific rigor and community engagement has earned him respect among peers and educators. Though formal awards beyond academia may be limited, his scholarly achievements and continued contributions to scientific education position him as a rising figure in physics research in Cameroon.

🔬 Research Focus :

Dr. Senghor TAGOUEGNI’s research interests span electrical transmission lines, oscillators, nonlinear dynamics, and parity-time (PT) symmetry in optical, mechanical, and electronic systems. He explores advanced physics topics such as quantum processing, condensed matter, and atomic systems, particularly in relation to wave transport phenomena. His doctoral thesis addressed Anderson localization and electromagnetically induced transparency in PT/APT-symmetric systems—an area of growing significance in quantum physics and photonics. His work blends theoretical modeling with computational tools like Matlab, Maple, and LTSpice, advancing understanding of complex systems. This interdisciplinary focus not only contributes to fundamental science but also supports technological innovation in areas like energy transmission, quantum electronics, and material science.

📊 Publication Top Notes:

  • 📘 Localization behavior in a thresholdless PT symmetric electrical transmission line
    Year: 2024
    Journal: Physica B: Condensed Matter
    DOI: 10.1016/j.physb.2024.416630

  • 📗 PT-symmetric electronic dimer without gain material
    Year: 2023
    Journal: Communications in Theoretical Physics
    DOI: 10.1088/1572-9494/acf28

  • 📙 Non-Hermitian electronics multipods of Electromagnetically Induced Transparency (EIT) and Absorption (EIA)
    Year: 2022
    Journal: Optical and Quantum Electronics
    DOI: 10.1007/s11082-022-03629-4

  • 📕 Energy transport and Anderson-like localization in non-Hermitian electrical transmission line
    Year: 2020
    Journal: Physica Scripta
    DOI: 10.1088/1402-4896/abacfc

  • 📒 Thresholdless characterization in space and time reflection symmetry electronic dimers
    Year: 2017
    Journal: Journal of the Optical Society of America B
    DOI: 10.1364/JOSAB.34.000658

  • 📄 Experimental observation of real spectra in Parity-Time symmetric ZRC dimers with positive and negative frequencies
    Year: 2020
    Platform: arXiv Preprint
    arXiv ID: arXiv:2007.01999

Changxin Yu | Digital technology | Best Researcher Award

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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

	


	

	






	
	

		


Zhiying Mu| Neural Networks | Best Researcher Award
			

				Published on  by Engineering Scientist			

		
	


	

		
Dr. Zhiying Mu| Neural Networks

|Best Researcher Award




Dr . Zhiying Mu  Northwestern Polytechnical University, China .




Zhiying Mu, a Ph.D. candidate in Cyberspace Security at Northwestern Polytechnical University, is a distinguished young scholar dedicated to AI safety and intelligent system security. With a rigorous academic foundation and cross-disciplinary insight from her mathematics background at the University of Connecticut and the University of Nebraska–Lincoln, she has contributed to multiple national-level research projects, including the “New Generation Artificial Intelligence” initiative. Her publications in top-tier journals like IEEE IoT Journal and Neural Processing Letters demonstrate high academic impact. She leads multiple research and data-driven modeling projects with outstanding results. Her innovative mindset, strong leadership, and publication record make her an exceptional candidate for the Best Researcher Award.




🌍 Professional Profile:


Scopus


🏆 Suitability for the Best Researcher Award


 




















Zhiying Mu, a Ph.D. candidate in Cyberspace Security at Northwestern Polytechnical University, is a distinguished young scholar dedicated to AI safety and intelligent system security. With a rigorous academic foundation and cross-disciplinary insight from her mathematics background at the University of Connecticut and the University of Nebraska–Lincoln, she has contributed to multiple national-level research projects, including the “New Generation Artificial Intelligence” initiative. Her publications in top-tier journals like IEEE IoT Journal and Neural Processing Letters demonstrate high academic impact. She leads multiple research and data-driven modeling projects with outstanding results. Her innovative mindset, strong leadership, and publication record make her an exceptional candidate for the Best Researcher Award.




















🎓 Education 


Zhiying Mu earned her Ph.D. in Cyberspace Security (2021–2025) from Northwestern Polytechnical University, under the supervision of Academician He Dequan. Her curriculum includes machine learning, optimization, complex networks, and academic ethics. She actively contributed to major national and industrial research projects related to AI safety and power systems. She previously earned a Master’s degree in Mathematics from the University of Connecticut (2017–2019), and a Bachelor’s degree in Mathematics from the University of Nebraska–Lincoln (2013–2017). Her academic performance has been consistently excellent, with a GPA of 3.8/4.0 during her Ph.D. Her multidisciplinary training bridges cybersecurity and data science, laying a robust foundation for her research excellence and interdisciplinary innovation.


🏢 Work Experience 


Zhiying Mu has led and participated in various high-impact research projects involving AI safety, network attack modeling, and climate risk forecasting. Notable projects include storm damage prediction using regression models, ACI index modeling via time-series analysis, and optimal strategy evaluation in Tic-Tac-Toe using generalized linear models. She has also organized institutional reading programs, promoting interdisciplinary knowledge sharing. Her responsibilities typically involve end-to-end project management: problem formulation, data collection and preprocessing, statistical modeling, visualization, and outcome documentation. She is proficient in R and Python and applies advanced analytics and machine learning techniques. Her blend of theoretical depth and practical implementation reflects a versatile and impactful research profile in both academic and applied contexts.


🏅 Awards and Honors 


Zhiying Mu has received significant recognition for her research and academic contributions. She was the top borrower of the year at her university library, reflecting her deep engagement with academic literature. She has been entrusted with leadership roles in national projects funded under China’s “New Generation Artificial Intelligence” program and major horizontal projects with the State Grid Corporation of China. Her peer-reviewed publications in top SCI-indexed journals such as IEEE IoT Journal, Neurocomputing, and Neural Processing Letters highlight her academic excellence. She has also served as a project lead in multiple interdisciplinary modeling initiatives. Her academic and extracurricular leadership underscores her status as an emerging thought leader in AI security and intelligent systems.


🔬 Research Focus 
































































Zhiying Mu’s research centers on artificial intelligence security, multi-task learning, risk modeling, and network attack analysis. She investigates adversarial learning techniques, identity-preserving dialogue generation, and neural machine translation enhancement using syntactic features. Her work integrates mathematical modeling, machine learning, and cybersecurity to address challenges in intelligent power systems, social network robustness, and data-driven decision-making. She has explored both black-box and white-box vulnerabilities in AI systems and proposed defense mechanisms with theoretical grounding. Her interdisciplinary focus also includes time-series forecasting for insurance risk and strategic modeling in game theory. She actively contributes to national AI safety platforms and is committed to advancing secure, interpretable, and reliable AI technologies for critical infrastructures.




























































































📊 Publication Top Notes:


Prompt-enhanced Neural Machine Translation with POS Tags


Authors:
Mu, Zhiying; Lin, Shengchuan; Guo, Sensen; Yu, Shanqing; Gao, Dehong


Journal:
Neurocomputing, 2025


Citations:
0 (as of now)

	


	

	






	
	

		


Hazrat Bilal | Robotics Engineering  | Young Scientist Award
			

				Published on  by Engineering Scientist			

		
	


	

		
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
    

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    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
    

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    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
    

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    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
    

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    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
    

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    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
    

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    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
    

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    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
    

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    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
    

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    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
    

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