Ziwen Zhao | Technology | Best Researcher Award

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Assoc. Prof. Dr. Ziwen Zhao | Technology | Best Researcher Award

Associate Researcher | Northwest A&F University, China

Ziwen Zhao, is a Chinese associate researcher at Northwest A&F University, specializing in hydropower system stability, pumped storage, and renewable energy integration. With an H-index of 12 and over 390 citations, he is a prolific contributor to high-impact journals like Applied Energy, Journal of Cleaner Production, and Renewable Energy. His scholarly pursuits focus on enhancing the flexibility and decarbonization potential of hydropower systems during China’s energy transition. Zhao actively engages in national research projects funded by NSFC and other major foundations and serves as an editorial board member and reviewer for top journals. He also contributes to national standards and co-authored a widely used textbook. Besides research, he supports engineering projects on turbine upgrades and renewable energy deployment in major Chinese provinces. Recognized for his academic and professional service, Zhao was named an Outstanding Doctoral Dissertation Advisor in 2023.

Publication Profile

Scholar

🎓 Education

Ziwen Zhao pursued his entire higher education at Northwest A&F University. He earned a Ph.D. in Hydraulic Engineering between September 2019 and June 2023, building on a Master’s degree in the same field (September 2017 – June 2019). His graduate and doctoral studies laid the foundation for his research in pumped hydro storage, energy transition modeling, and the coordination of hydropower with renewable energy systems. His academic rigor and technical proficiency were evident early on, leading to multiple high-impact publications even before completing his Ph.D. His solid educational background in hydraulic engineering has positioned him to contribute both theoretically and practically to the optimization of multi-energy systems and hydropower technologies. Throughout his academic journey, Zhao demonstrated a blend of fundamental engineering knowledge and data-driven analysis, which now underpins his postdoctoral and faculty-level research. His involvement in curriculum development also reflects a strong academic orientation.

🧪 Experience

Ziwen Zhao has accumulated substantial academic and practical experience in hydropower engineering. Since June 2023, he has served as an Associate Researcher at Northwest A&F University. Prior to this, he contributed to research and teaching activities during his doctoral and master’s studies, often leading publications as the first or corresponding author. Zhao is deeply involved in major research initiatives, serving as the principal investigator for projects funded by NSFC, China Postdoctoral Science Foundation, and regional innovation centers. His practical expertise includes evaluating turbine upgrades and contributing to renewable energy transmission strategies in provinces like Chongqing. He lectures on Hydropower Plant Engineering and is the deputy editor of a national-level hydraulic turbine textbook. His engineering applications span vibration analysis in hydrogenerators and optimization of pumped storage systems. Zhao also holds multiple patents related to dynamic regulation and power generation, exemplifying his ability to bridge academic research and industrial practice.

🏆 Awards & Honors

Ziwen Zhao has received several prestigious accolades in recognition of his academic and professional excellence. He was awarded the “Outstanding Doctoral Dissertation Advisor” title by Northwest A&F University in 2023. His technical expertise also earned him co-authorship on China’s national standard GB/T 44786-2024 for hydropower automation. Zhao is actively involved in professional societies, serving on the Youth Editorial Board of Water Resources Development Research, the Editorial Board of Discover Energy, and as a reviewer for leading journals such as Applied Energy, Renewable Energy, and Energy Conversion and Management. His leadership roles include organizing committee member for international conferences and Technology Manager for the “Kechuang China” innovation initiative. As deputy editor of a nationally endorsed textbook and a recognized university lecturer, Zhao’s impact spans research, education, and policy. These honors reflect his outstanding contribution to hydropower engineering, multi-energy system integration, and academic service.

🔬 Research Focus

Ziwen Zhao’s research centers on the safe, stable, and flexible operation of hydropower and pumped storage units, particularly their integration with renewable energy systems. His work addresses rapid transitions between pumping and generation modes, low-frequency vibration control, and coordination of multi-energy systems under uncertainty. He has proposed novel models and optimization frameworks to enhance hydropower’s role in China’s decarbonization goals. Zhao also investigates energy storage technologies’ capacity to stabilize electricity during coal phase-outs and renewable variability. His interdisciplinary approach fuses hydraulic mechanics, data-driven simulation, and energy systems modeling. As principal investigator on NSFC and postdoctoral-funded projects, Zhao is developing mechanism-data fusion methods for performance enhancement in pumped storage. His research supports national strategies for power system transition and infrastructure modernization. Through publications in top-tier journals and patents on control methods, Zhao contributes cutting-edge solutions for improving energy resilience and sustainability.

✅ Conclusion

Dr. Ziwen Zhao exemplifies academic excellence, technical innovation, and societal relevance in energy systems research. His multidisciplinary contributions—spanning flexible hydropower operation, renewable integration, and system stability—are not only timely but also transformative. With his strong publishing record, research leadership, and practical engineering applications, Dr. Zhao is highly deserving of the Best Researcher Award and is poised to become a global thought leader in sustainable energy engineering.

📚 Top Publications with Notes

Title: Overcoming the uncertainty and volatility of wind power: Day-ahead scheduling of hydro-wind hybrid power generation system by coordinating power regulation and frequency
Year: 2023
Authors: S. Han, M. He, Z. Zhao, D. Chen, B. Xu, J. Jurasz, F. Liu, H. Zheng
Citations: 60

Title: Stability and efficiency performance of pumped hydro energy storage system for higher flexibility
Year: 2022
Authors: Z. Zhao, Y. Yuan, M. He, J. Jurasz, J. Wang, M. Egusquiza, E. Egusquiza, …
Citations: 41

Title: The potential assessment of pump hydro energy storage to reduce renewable curtailment and CO₂ emissions in Northwest China
Year: 2023
Authors: J. Li, Z. Zhao, D. Xu, P. Li, Y. Liu, M.A. Mahmud, D. Chen
Citations: 40

Title: The importance of flexible hydropower in providing electricity stability during China’s coal phase-out
Year: 2023
Authors: Z. Zhao, X. Ding, P. Behrens, J. Li, M. He, Y. Gao, G. Liu, B. Xu, D. Chen
Citations: 35

Title: Unlocking potential contribution of seasonal pumped storage to ensure the flexibility of power systems with high proportion of renewable energy sources
Year: 2023
Authors: P. Li, Z. Zhao, J. Li, Z. Liu, Y. Liu, M.A. Mahmud, Y. Sun, D. Chen
Citations: 28

Title: A novel day-ahead scheduling model to unlock hydropower flexibility limited by vibration zones in hydropower-variable renewable energy hybrid system
Year: 2024
Authors: S. Han, Y. Yuan, M. He, Z. Zhao, B. Xu, D. Chen, J. Jurasz
Citations: 24

Title: Comprehensive benefit evaluations for integrating off-river pumped hydro storage and floating photovoltaic
Year: 2023
Authors: J. Li, Z. Zhao, P. Li, M.A. Mahmud, Y. Liu, D. Chen, W. Han
Citations: 20

Title: Optimal operation of cascade hydro-wind-photovoltaic complementary generation system with vibration avoidance strategy
Year: 2022
Authors: R. Jia, M. He, X. Zhang, Z. Zhao, S. Han, J. Jurasz, D. Chen, B. Xu
Citations: 20

Title: Performance analysis of pumped-storage plant from condenser mode to generating process
Year: 2020
Authors: Z. Zhao, D. Chen, H. Li, H. Wei
Citations: 17

Title: Optimization and decision making of guide vane closing law for pumped storage hydropower system to improve adaptability under complex conditions
Year: 2023
Authors: L. Lei, D. Chen, C. Ma, Y. Chen, H. Wang, H. Chen, Z. Zhao, Y. Zhou, …
Citations: 13

 

Dr. Biao Zhang | Technology | Best Researcher Award

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Dr. Biao Zhang | Technology | Best Researcher Award

Xi’an Research Institute of High-Tech, China

Zhang Biao is a promising doctoral student specializing in Nuclear Science and Technology at the PLA Rocket Force Engineering University, Xi’an, China. With a focus on advancing safety and efficiency in nuclear environments, his research emphasizes radiation field reconstruction and dose-optimized path planning. He has authored multiple peer-reviewed articles in top-tier journals like Annals of Nuclear Energy and Nuclear Technology. Zhang’s contributions to computational modeling and intelligent algorithms mark him as an emerging innovator in his field 🧠⚛️.

Publication Profile

ORCID

🎓 Education Background:

Zhang Biao pursued his higher education at the esteemed PLA Rocket Force Engineering University in Xi’an, Shaanxi, China 🎓. Currently engaged in his doctoral studies, his academic journey is rooted in nuclear science with an inclination toward computational applications in radiation detection and safety mechanisms.

💼 Professional Experience:

Although still in academia, Zhang has demonstrated notable professional-level impact through his published works. He is affiliated with the Xi’an Research Institute of High-Tech and is a proud member of the Chinese Nuclear Society 🧪. His hands-on experience with mathematical modeling and radiation path optimization contributes to future applications in nuclear facility safety.

🏆 Awards and Honors:

While formal accolades are pending, Zhang’s scholarly output—particularly his recent algorithmic improvements in radiation path planning—have earned recognition in high-impact journals and among nuclear technology scholars. His nomination for the Best Researcher Award by the Computer Scientists Awards underscores his rising prominence in scientific research 🥇📚.

🔬 Research Focus:

Zhang Biao’s work revolves around enhancing the safety of radiation environments through efficient detection and computational path planning. His innovations include a modified A* algorithm for minimizing radiation dose exposure and improved reconstruction techniques for gamma-ray source fields using interpolation and mathematical modeling 🔍🛰️.

🔚 Conclusion:

Zhang Biao represents the new generation of nuclear technologists who integrate artificial intelligence with radiation safety science. With multiple first-author publications, innovative algorithms, and a clear vision for nuclear safety, he is well on track to make substantial contributions to science and society 🌏💡.

📚 Top Publications:

A modified A* algorithm for path planning in the radioactive environment of nuclear facilities – Annals of Nuclear Energy, 2025.
Cited by: Referenced in dose optimization and nuclear safety path planning studies.

Path planning of PRM based on artificial potential field in radiation environments – Annals of Nuclear Energy, 2024.
Cited by: Utilized in advanced robotics navigation within hazardous nuclear zones.

Minimum dose walking path planning in a nuclear radiation environment based on a modified A* algorithm –Annals of Nuclear Energy, 2024.
Cited by: Recognized for efficient personnel routing in nuclear facilities.

A comparative study of different radial basis function interpolation algorithms in the reconstruction and path planning of γ radiation fields – Nuclear Engineering and Technology, 2024.
Cited by: Referenced in computational gamma field modeling research.

Reconstruction of γ Dose Rate Field and Algorithm Validation Based on Inverse Distance Weight Interpolation – Nuclear Technology, 2024.
Cited by: Applied in gamma dose field reconstruction validations.

Obsa Gilo Wakuma | Computer Science | Best Researcher Award

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Dr. Obsa Gilo Wakuma | Computer Science | Best Researcher Award

Ass. Prof, Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated computer scientist specializing in deep learning and domain adaptation. With extensive experience in academia, he has contributed significantly to the field through his research and teaching. Dr. Obsa has held various positions at Wallaga University, Ethiopia, and currently serves as a research scholar at the Indian Institute of Technology Patna, India. His expertise spans multiple programming languages and database management systems, making him a versatile and valuable contributor to the field of computer science.

Profile

Strengths for the Award:

  1. Extensive Research Background: Dr. Obsa Gilo has a robust academic background, culminating in a Ph.D. in Computer Science and Engineering with a focus on deep learning approaches for efficient domain adaptation. His research in domain adaptation, particularly in sensor data and image classification, showcases his innovative contributions to the field.
  2. Publications: Dr. Gilo has a significant number of publications in reputed journals and conference proceedings. Notable among them are:
    • “Kernel bures metric for domain adaptation in sensor data” in Expert System with Applications (2024)
    • “Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation” in Pattern Analysis and Applications (2024)
    • “Rdaot: Robust unsupervised deep sub-domain adaptation through optimal transport for image classification” in IEEE Access (2023)
  3. Teaching and Mentoring: His employment history includes roles such as Lecturer and Graduate Assistant at Wallaga University, demonstrating his commitment to education and mentoring the next generation of scholars.
  4. Skills and Competencies: Dr. Gilo possesses strong technical skills in various programming languages, databases, and web development technologies, along with proficiency in English, Afaan Oromoo, and Amharic. This multilingual ability enhances his capacity to engage with diverse communities.
  5. Community Service: His experience includes academic research, teaching, training, consultation, and community service, reflecting a well-rounded professional dedicated to both academic and societal contributions.

Areas for Improvement:

  1. Practical Community Impact: While Dr. Gilo has an impressive academic and research portfolio, there could be more emphasis on the practical application of his research directly benefiting local communities. Highlighting specific projects or initiatives where his work has directly impacted community development would strengthen his case.
  2. Collaboration with Local Institutions: Greater collaboration with local institutions and involvement in projects addressing community-specific issues could further enhance his profile. Establishing partnerships with local universities, NGOs, or governmental bodies to implement his research findings in real-world settings would be beneficial.
  3. Visibility and Outreach: Increasing the visibility of his work through public lectures, community workshops, or outreach programs can help in demonstrating the broader societal impact of his research. Engaging with the community through these platforms can showcase the practical benefits of his research.

 

Education: 🎓

Dr. Obsa Gilo Wakuma holds a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, with a thesis on “Deep Learning Approaches for Efficient Domain Adaptation.” He earned his M.Sc. in Computer Science from Wallaga University, where he developed an Information Extraction Model for Afaan Oromo news texts. Dr. Obsa also holds a B.Sc. in Computer Science from Wallaga University and has a strong foundation from Sibu Sire Preparatory and High School.

Experience: 💼

Dr. Obsa’s professional journey includes roles such as Recorder and Laboratory Technician at Wallaga University. He progressed to become a Graduate Assistant, Lecturer, and finally a Research Scholar at IIT Patna. His career reflects a blend of administrative, technical, and academic responsibilities, showcasing his diverse skill set and commitment to the field.

Research Interests: 🔍

Dr. Obsa’s research interests lie in deep learning, domain adaptation, and unsupervised learning. He has focused on developing efficient methods for domain adaptation in sensor data and image classification, contributing to several high-impact publications. His work aims to enhance the applicability and robustness of machine learning models in diverse environments.

Awards: 🏆

Dr. Obsa has been recognized for his academic excellence and research contributions throughout his career. He has received accolades for his innovative work in domain adaptation and deep learning, highlighting his role as a prominent researcher in the field of computer science.

Publications

  1. Unsupervised Sub-Domain Adaptation Using Optimal Transport. Journal of Visual Communication and Image Representation, 94, 103857. Cited by: 1 article.
  2. Kernel Bures Metric for Domain Adaptation in Sensor Data. Expert System with Applications, 255(Part C), 124725. Cited by: 1 article.
  3. Subdomain Adaptation via Correlation Alignment with Entropy Minimization for Unsupervised Domain Adaptation. Pattern Analysis and Applications, 27(1), 13. Cited by: 1 article.
  4. RDAOT: Robust Unsupervised Deep Sub-Domain Adaptation through Optimal Transport for Image Classification. IEEE Access. Cited by: 1 article.
  5. Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation. In 2022 IEEE 19th India Council International Conference (INDICON), pp. 1–6. Cited by: 1 article.