Huan Zhang | Econometrics and Finance | Best Researcher Award

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Ms. Huan Zhang | Econometrics and Finance | Best Researcher Award

Associate Professor | Guangdong Ocean University | China

Ms. Huan Zhang is an accomplished associate professor specializing in tourism, cultural creativity, and communication studies. She has a strong academic background, holding advanced degrees in economics and labor studies, and is completing her doctoral studies in tourism and hospitality management. Over her career, she has led multiple research projects at national, provincial, and university levels, demonstrating leadership and an ability to translate research into practical impact. Her work has been recognized both academically and publicly, with reports adopted by local authorities and online courses featured on national platforms. She has published a monograph and several papers in SSCI, CSSCI, and core journals, reflecting a consistent research trajectory. Ms. Zhang also excels in mentoring students, guiding them to achieve national and provincial awards. According to Scopus, her measurable research impact includes 3 documents, 3 citations, and an h-index of 1, showcasing her growing influence in her field, with total citations at 33.

Profiles: Scopus | ORCID

Featured Publications

1. Mei, D., & Zhang, H. (2025). Impact of global tensions on commodity futures from a geopolitical risk perspective. Finance Research Letters. https://doi.org/10.1016/j.frl.2025.108605

2. Khalil, M. L., Abd Aziz, N., Long, F., & Zhang, H. (2023). What factors affect firm performance in the hotel industry post-Covid-19 pandemic? Examining the impacts of big data analytics capability, organizational agility and innovation. Journal of Open Innovation: Technology, Market, and Complexity. https://doi.org/10.1016/j.joitmc.2023.100081

Qian Qiao | Materials Science | Best Researcher Award 

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Dr. Qian Qiao | Materials Science | Best Researcher Award 

R&D Manager | IDQ Science and Technology (Hengqin Guangdong) Co | China

Dr. Qian Qiao is a dedicated researcher specializing in electromechanical and mechanical engineering, with extensive experience in materials science, surface technology, and smart manufacturing. She has authored numerous papers in reputable international journals and holds multiple patents that highlight her innovative approach to engineering challenges. Her academic achievements, including several prestigious scholarships and awards, reflect consistent excellence and commitment to research advancement. Dr. Qian has actively participated in global academic conferences, contributing to the dissemination and exchange of cutting-edge knowledge. Her current research focuses on the structural and performance analysis of advanced manufacturing components, integrating intelligent systems and automation to enhance efficiency and reliability. With a strong foundation in both theoretical and applied research, she demonstrates outstanding potential for leading future developments in material innovation, corrosion science, and intelligent engineering solutions, contributing meaningfully to technological progress and industrial transformation.

Profiles: Google Scholar | Scopus | ORCID 

Featured Publications

1. Qiao, Q., Qian, H., Li, Z., Guo, D., Kwok, C. T., Jiang, S., Zhang, D., & Tam, L. M. (2025). Microstructure evolution and mechanical performance of AA6061-7075 heterogeneous composite fabricated via additive friction stir deposition. Alloys, 4(4), 21.

2. Lam, W. I., Leong, K. K., Tam, C. W., Qiao, Q., Lin, Y., Yang, G., Guo, D., & Kwok, C. T. (2025). A high performance mechanically alloyed stainless steel composite coating via friction surfacing. Surface and Coatings Technology, 132685.

3. Qiao, Q., Gong, X., Guo, D., Qian, H., Li, Z., Zhang, D., Kwok, C., & Tam, L. M. (2025). Influence of tool head geometry on in situ monitoring of temperature, force, and torque during additive friction deposition of aluminum alloy 2219. Materials Science in Additive Manufacturing, 4(4), 025280060.

4. Qiao, Q., Tam, C. W., Lam, W. I., Wang, K., Guo, D., Kwok, C. T., Lin, Y., Yang, G., & Zhang, D. (2025). Hybrid heat-source solid-state additive manufacturing: A method to fabricate high performance AA6061 deposition. Journal of Materials Science & Technology, 228, 107–124.

5. Wu, Z., Qian, H., Chang, W., Zhu, Z., Lin, Y., Qiao, Q., Guo, D., Zhang, D., & Kwok, C. T. (2025). Enhanced corrosion resistance by Pseudomonas aeruginosa on 2219 aluminum alloy manufactured through additive friction stir deposition. Acta Metallurgica Sinica (English Letters), 1–18.

Christopher Koroneos | Environmental Management | Distinguished Scientist Award

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Prof. Dr. Christopher Koroneos | Environmental Management | Distinguished Scientist Award

Doctor | University of West Attica | Greece

Prof. Dr. Christopher Koroneos is a distinguished researcher whose work spans energy engineering, renewable energy systems, and environmental management. His research integrates chemical and environmental engineering principles to advance sustainable energy solutions, low-exergy systems, and lifecycle-based environmental optimization. Over his career, he has contributed significantly to international collaborations, mentored numerous graduate and undergraduate students, and held leadership roles in global scientific programs. His publications demonstrate both depth and breadth, influencing policy, technology, and academic discourse in renewable energy and environmental sustainability. Prof. Koroneos’ scholarship is recognized worldwide, reflecting his ability to bridge theory and practical applications in energy and environmental systems. His measurable research impact, as reflected in Scopus, includes 99 documents, 4,568 citations, and an h-index of 35, highlighting both the quality and influence of his scientific contributions across the global research community.

Profile: Scopus | Google Scholar | ORCID

Featured Publications

1. Tsakiridis, P. E., Papadimitriou, G. D., Tsivilis, S., & Koroneos, C. (2008). Utilization of steel slag for Portland cement clinker production. Journal of Hazardous Materials, 152(2), 805–811.

2. Koroneos, C., Dompros, A., Roumbas, G., & Moussiopoulos, N. (2004). Life cycle assessment of hydrogen fuel production processes. International Journal of Hydrogen Energy, 29(14), 1443–1450.

3. Christopher, K., & Dimitrios, R. (2012). A review on exergy comparison of hydrogen production methods from renewable energy sources. Energy & Environmental Science, 507.

4. Koroneos, C., Spachos, T., & Moussiopoulos, N. (2003). Exergy analysis of renewable energy sources. Renewable Energy, 28(2), 295–310.

5. Koroneos, C., & Dompros, A. (2007). Environmental assessment of brick production in Greece. Building and Environment, 42(5), 2114–2123.

Geng-Long Hsu | Medicine and Dentistry | Best Researcher Award

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Prof. Dr. Geng-Long Hsu | Medicine and Dentistry | Best Researcher Award

Director | Hsu’s Andrology | Taiwan

Prof. Dr. Geng-Long Hsu is a distinguished urologist and microsurgical potency reconstruction specialist with decades of experience in clinical practice, research, and education. He has pioneered innovative surgical techniques and contributed significant anatomical and physiological insights in male reproductive medicine. His leadership in multiple research centers and academic institutions has fostered a strong culture of mentorship and collaboration. Dr. Hsu is recognized internationally through memberships in professional societies and numerous awards for both basic and clinical research, highlighting the global impact of his work. His research demonstrates a consistent focus on advancing urological science, integrating clinical expertise with experimental innovation. Through his contributions, he has influenced treatment protocols and surgical outcomes in male reproductive health. His measurable research impact is reflected in Scopus, with 1,521 citations across 68 documents and an h-index of 22, underscoring the significance and reach of his scholarly work.

Profiles: Scopus | ORCID

Featured Publications

1. G.-L. Hsu, “Combining erection restoration and factual penile enhancement based on revolutionary penile fibro-vascular assembly,” Archivos Espanoles De Urologia, 2025.

2. G.-L. Hsu, “A detailed analysis of the penile fibro-vascular assembly,” Journal of Sexual Medicine, 2025.

3. G.-L. Hsu, “Coil embolization is not justified for treating patients with veno-occlusive dysfunction: Case series and narrative literature review,” Life, 2024.

4. G.-L. Hsu, “Emergent penile venous stripping for treating adolescent impotence,” Life, 2024.

5. G.-L. Hsu, “A case report of right cardiac ventricle perforation by uncontrolled embolization coil inserted for treating penile veno-occlusive dysfunction,” Urology Case Reports, 2022.

Mingliang Luo | Geographical Sciences | Best Researcher Award

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Prof. Mingliang Luo | Geographical Sciences | Best Researcher Award

Vice Dean | China West Normal University | China

Prof. Mingliang Luo is a distinguished researcher in geographic and environmental sciences, specializing in urbanization, ecosystem services, hydrological modeling, and environmental assessment. His work integrates advanced spatial analysis, digital elevation modeling, and soil-erosion studies, providing practical insights for sustainable regional development and environmental management. Over the years, he has contributed extensively to high-impact journals, demonstrating methodological rigor and innovation, particularly in interdisciplinary research that bridges environmental science, geoinformatics, and ecosystem modeling. Prof. Luo’s research not only addresses critical scientific questions but also offers actionable solutions for real-world environmental challenges, reflecting his commitment to both academic excellence and societal impact. His collaborative projects and leadership in research teams have further strengthened his influence in the field. According to Scopus, his measurable research impact includes 395 citations, 47 documents, and an h-index of 9, highlighting his significant contributions and scholarly recognition in the scientific community.

Profile: Scopus

Featured Publications

1. T. Wang, M. Luo, L. Bai, and W. Li, “Urbanization and Ecosystem Services Supply–Demand Mismatches Across Diverse Resource-Based Cities: Evidence from Sichuan, China,” Sustainability, Switzerland, 2025.

2. X. Wang, Y. Wu, M. Luo, K. Katsanou, J. Wenninger, and R. Bol, “Exports of organic matter, phosphorus and nitrogen from Sichuan Basin: A critical region regulating water quality of the Upper Yangtze River, China,” Journal of Hydrology, 2025.

3. Y. He, M. Luo, H. Yang, L. Bai, and Z. Chen, “Variability of Interpolation Errors and Mutual Enhancement of Different Interpolation Methods,” Applied Sciences, Switzerland, 2024.

4. J. Jiang, M. Luo, L. Bai, Y. Sang, S. Yang, and H. Yang, “Study of slope length (L) extraction based on slope streamline and the comparison of method results,” Scientific Reports, 2024.

Panagiota Koutsimani | Neuropsychology | Best Researcher Award

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Dr. Panagiota Koutsimani | Neuropsychology | Best Researcher Award

Adjunt Lecturer | University of Western Macedonia | Greece

Dr. Panagiota Koutsimani is a cognitive neuropsychologist specializing in burnout, cognitive functioning, and mental health. She holds a PhD in Cognitive Psychology from the University of Macedonia and is currently a postdoctoral researcher at Aristotle University of Thessaloniki. Her research has significantly contributed to understanding the relationships between burnout, depression, and anxiety, notably through her widely cited meta-analysis published in Frontiers in Psychology. She has also investigated cognitive performance in non-clinical burnout populations, highlighting the role of family support as a protective factor. Her work employs rigorous methodologies, including longitudinal studies and meta-analyses, reflecting a strong commitment to advancing psychological research. In addition to her research, Dr. Koutsimani has extensive teaching and dissertation supervision experience, mentoring emerging researchers in both cognitive and neuropsychology fields. According to her Google Scholar profile, total citations 1903, since 2020 citations 1854, h-index 8, i10-index 7.

Profile: Scopus | Google Scholar

Featured Publications

1. P. Koutsimani, A. Montgomery, and K. Georganta, “The relationship between burnout, depression, and anxiety: A systematic review and meta-analysis,” Frontiers in Psychology, vol. 10, p. 429219, 2019.

2. A. Kariou, P. Koutsimani, A. Montgomery, and O. Lainidi, “Emotional labor and burnout among teachers: A systematic review,” International Journal of Environmental Research and Public Health, vol. 18, no. 23, p. 12760, 2021.

3. P. Koutsimani, A. Montgomery, E. Masoura, and E. Panagopoulou, “Burnout and cognitive performance,” International Journal of Environmental Research and Public Health, vol. 18, no. 4, p. 2145, 2021.

4. P. Koutsimani, A. Montgomery, and K. Georganta, “The relationship between burnout, depression, and anxiety: A systematic review and meta-analysis,” Frontiers in Psychology, vol. 10, p. 284, 2019.

5. P. Koutsimani and A. Montgomery, “A two-wave study on the associations of burnout with depression and anxiety: The mediating and moderating role of perceived family support,” Psychological Reports, vol. 126, no. 1, pp. 220–245, 2023.

Yang Han | Computer Science | Best Researcher Award

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Dr. Yang Han | Computer Science | Best Researcher Award

Associate Researcher at Tianjin University, China

Yang Han is an emerging researcher with a strong academic background in mathematics, having completed both his Master’s and PhD at Nankai University, followed by a research position at Tianjin University. His work bridges mathematical theory and practical applications in engineering, focusing on areas such as topological data analysis, signal processing, and intelligent fault diagnosis. In recent years, he has published extensively in high-impact journals like IEEE Transactions on Instrumentation and Measurement and Chaos, Solitons & Fractals, and presented at reputable international conferences such as IEEE PESGM and ACPEE. His interdisciplinary research is marked by innovation and relevance, especially in appliance identification, load forecasting, and fault detection using advanced mathematical tools. Though early in his research career, Yang has demonstrated strong potential and a clear trajectory of growth. His dedication, academic rigor, and collaborative approach position him as a promising candidate for the Best Researcher Award.

🔹Professional Profile 

Google Scholar
ORCID Profile 

🏆Strengths for the Award

Yang Han demonstrates a highly impressive academic and research trajectory. With a strong foundation in mathematics from Nankai University, progressing through a Master’s and PhD (2015–2023), and currently holding an associate researcher position at Tianjin University, he shows continuity and growth in academic rigor. His research spans interdisciplinary areas, merging topological data analysis, signal processing, machine learning, and fault diagnosis—fields of significant importance in both academia and industry. Notably, his recent publications in high-impact journals such as IEEE Transactions on Instrumentation and Measurement and Chaos, Solitons & Fractals reflect both quality and innovation. Additionally, his contributions to top-tier conferences like IEEE PESGM and ACPEE signal strong peer recognition. The combination of applied AI techniques and deep mathematical theory shows versatility, a rare and commendable strength for a young researcher.

Areas for Improvement

While the publication record is strong and growing, most of the impactful work is very recent (primarily in 2024–2025), indicating that Yang Han is in the early stages of building a long-term research profile. Sustained contributions over a longer timeline will better establish him as a leading authority. Another point of improvement would be to take on more lead or sole authorship roles in future publications, as many current works are collaborative with shared credit, which can make it harder to isolate individual impact. Additionally, while his interdisciplinary work is a strength, expanding his network internationally through collaborations beyond China and participating in global research programs could enhance the visibility and influence of his work.

Conclusion

Yang Han is a highly promising and impactful early-career researcher with a unique blend of mathematical depth and applied AI-driven engineering. His recent output demonstrates a clear upward trajectory, both in productivity and innovation. While there is room to further solidify his independent research identity and global presence, his current achievements strongly support his candidacy for the Best Researcher Award. Given his solid grounding, interdisciplinary focus, and growing impact, he is indeed a suitable and deserving nominee for this recognition.

🎓Education

Yang Han began his academic journey at Nankai University, a prestigious institution known for mathematical excellence. From 2015 to 2018, he completed his Master’s degree at the School of Mathematical Sciences and LPMC, focusing on advanced mathematical theories and computational techniques. His strong academic performance and deep interest in topology, algebra, and their applications led him to continue his research as a PhD student in the same department from 2019 to 2023. During his doctoral studies, he expanded his expertise into applied mathematics and began to explore connections with engineering systems and data-driven problem solving. His doctoral research provided the foundation for his transition into interdisciplinary areas such as topological data analysis and graph signal processing. His time at Nankai University was marked by academic growth, critical thinking, and active participation in scholarly research. This rigorous educational background prepared him for a successful research career bridging mathematics and electrical engineering.

💼Experience

Yang Han currently holds the position of Associate Researcher at the School of Electrical and Information Engineering, Tianjin University. Since assuming this role in 2023, he has actively contributed to research in intelligent systems, signal processing, and data analytics. Before this, he spent nearly a decade at Nankai University, where he completed his Master’s and PhD studies, engaging in teaching support and foundational research. His experience spans a variety of projects focused on non-intrusive load monitoring, equipment fault diagnosis, and appliance identification—often leveraging advanced mathematical tools like topological data analysis and fast Fourier transforms. He has contributed to both national and international research collaborations, presented at prestigious conferences, and published in leading journals. His ability to blend abstract mathematical methods with real-world engineering challenges exemplifies his versatile experience. His role also involves mentoring junior researchers and contributing to interdisciplinary innovation at the intersection of mathematics, artificial intelligence, and electrical engineering.

🏆Awards and Honors

While formal individual awards are not explicitly listed in the available data, Yang Han’s growing list of high-impact publications and conference presentations serves as strong evidence of professional recognition. His work has been published in top-tier journals such as IEEE Transactions on Instrumentation and Measurement, Chaos, Solitons & Fractals, and Engineering Applications of Artificial Intelligence, reflecting a high level of peer recognition. He has also contributed to leading international conferences, including IEEE PESGM and the Asia Conference on Power and Electrical Engineering (ACPEE), where selection itself is a mark of merit. These platforms are known for their rigorous review processes, indicating that his work meets and often exceeds international research standards. Additionally, his involvement in collaborative, interdisciplinary projects and authorship in multiple papers shows that he is a valued team member in academic and industrial circles. As his career progresses, further formal awards and honors are likely to follow.

🔬 Research Focus on Computer Science

Yang Han’s research is centered at the intersection of applied mathematics, artificial intelligence, and electrical engineering. His primary focus lies in topological data analysis, signal processing, and machine learning techniques for complex system monitoring and fault detection. He has contributed significantly to non-intrusive load monitoring (NILM), using graph signal processing to identify energy consumption patterns without intrusive sensors. He also works on fault diagnosis through time-frequency analysis and the application of mathematical topology in real-world engineering systems. His innovative approach often involves transforming abstract mathematical concepts—such as Betti curves and topological invariants—into practical tools for appliance identification and power grid analysis. Furthermore, Yang Han is exploring adaptive methods for equipment behavior modeling and data-driven forecasting. This unique research blend offers both theoretical advancements and immediate practical value, demonstrating his ability to tackle emerging challenges in intelligent energy systems and industrial diagnostics with precision and depth.

📚 Publications Top Notes

  • Title: Energy dissipation analysis of elastic–plastic materials
    Authors: H Yang, SK Sinha, Y Feng, DB McCallen, B Jeremić
    Year: 2018
    Citations: 94

  • Title: Study on the mechanical behavior of sands using 3D discrete element method with realistic particle models
    Authors: WJ Xu, GY Liu, H Yang
    Year: 2020
    Citations: 46

  • Title: Nonlinear finite elements: Modeling and simulation of earthquakes, soils, structures and their interaction
    Authors: B Jeremić, Z Yang, Z Cheng, G Jie, N Tafazzoli, M Preisig, P Tasiopoulou, …
    Year: 2018
    Citations: 37

  • Title: The real-ESSI simulator system
    Authors: B Jeremić, G Jie, Z Cheng, N Tafazzoli, P Tasiopoulou, F Pisanò, JA Abell, …
    Year: 1988
    Citations: 35

  • Title: Study on the meso-structure development in direct shear tests of a granular material
    Authors: H Yang, WJ Xu, QC Sun, Y Feng
    Year: 2017
    Citations: 28

  • Title: Energy dissipation analysis for inelastic reinforced concrete and steel beam-columns
    Authors: H Yang, Y Feng, H Wang, B Jeremić
    Year: 2019
    Citations: 27

  • Title: Time domain intrusive probabilistic seismic risk analysis of nonlinear shear frame structure
    Authors: H Wang, F Wang, H Yang, Y Feng, J Bayless, NA Abrahamson, B Jeremić
    Year: 2020
    Citations: 22

  • Title: Seismic resonant metamaterials for the protection of an elastic-plastic SDOF system against vertically propagating seismic shear waves (SH) in nonlinear soil
    Authors: C Kanellopoulos, N Psycharis, H Yang, B Jeremić, I Anastasopoulos, …
    Year: 2022
    Citations: 21

  • Title: Energy dissipation in solids due to material inelasticity, viscous coupling, and algorithmic damping
    Authors: H Yang, H Wang, Y Feng, F Wang, B Jeremić
    Year: 2019
    Citations: 20

  • Title: 3-d non-linear modeling and its effects in earthquake soil-structure interaction
    Authors: SK Sinha, Y Feng, H Yang, H Wang, B Jeremic
    Year: 2017
    Citations: 19

  • Title: Plastic-energy dissipation in pressure-dependent materials
    Authors: H Yang, H Wang, Y Feng, B Jeremić
    Year: 2020
    Citations: 18

  • Title: Relationship between multifunctionality and rural sustainable development: Insights from 129 counties of the Sichuan Province, China
    Authors: X Li, J Liu, J Jia, H Yang
    Year: 2022
    Citations: 17

  • Title: Modeling and simulation of earthquake soil structure interaction excited by inclined seismic waves
    Authors: H Wang, H Yang, Y Feng, B Jeremić
    Year: 2021
    Citations: 17

  • Title: An energy-based analysis framework for soil structure interaction systems
    Authors: H Yang, H Wang, B Jeremić
    Year: 2022
    Citations: 14

  • Title: A robust and efficient federated learning algorithm against adaptive model poisoning attacks
    Authors: H Yang, D Gu, J He
    Year: 2024
    Citations: 11

Dr. Amir Hossein Poursaeed | Engineering | Best Researcher Award

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Dr. Amir Hossein Poursaeed | Engineering | Best Researcher Award

Phd Candidate at University of Exeter, United Kingdom

Amir Hossein Poursaeed is an accomplished researcher in electrical engineering with a specialization in power systems, machine learning applications, and renewable energy integration. Holding a Master’s degree from Lorestan University, he has developed a strong academic foundation complemented by an exceptional research portfolio. His work focuses on power system protection, stability, and optimization using advanced AI techniques such as explainable deep learning and quantum neural networks. With over 17 peer-reviewed journal publications, many in Q1 journals, and multiple IEEE conference contributions, his research demonstrates both depth and innovation. He collaborates with leading academics internationally and has contributed to interdisciplinary studies in environmental modeling and water resource management. Amir’s commitment to cutting-edge research in inverter-based power grids, fault diagnosis, and energy systems places him among the promising young scholars in the field. His achievements reflect a rare blend of technical expertise, research leadership, and forward-looking vision essential for shaping the future of smart grids.

Professional Profile 

Google Scholar
ORCID Profile 

Education

Amir Hossein Poursaeed has a solid educational background in electrical engineering with a focus on power systems. He earned his Master of Science degree from Lorestan University, Iran, where he specialized in Digital Power System Protection and Power System Dynamics. His M.Sc. thesis, supervised by Professor Farhad Namdari, focused on using Support Vector Machines for wide-area protection against voltage and transient instabilities. He previously obtained his Bachelor of Science in Electrical Engineering from the same university, where he explored the optimal placement of phasor measurement units using metaheuristic algorithms. His academic performance was commendable, with a GPA of 18.87/20 in his M.Sc. program, demonstrating both technical strength and research capability. Throughout his education, he consistently focused on high-voltage systems, optimization, and smart grid technologies, laying the foundation for his research in AI-based power system protection and stability. His educational journey highlights a continuous commitment to excellence and innovation in energy systems.

Professional Experience

Amir Hossein Poursaeed has developed a robust professional profile centered around advanced power system research and academic collaboration. While specific institutional roles aren’t explicitly mentioned, his extensive list of high-impact publications indicates active involvement in collaborative research projects, particularly with institutions such as Lorestan University and international partners. He has co-authored multiple studies with recognized scholars, including Professor Farhad Namdari and Dr. P.A. Crossley, highlighting his integration into the global research community. His contributions include the design of advanced fault detection systems, AI-driven stability analysis tools, and renewable energy integration models. Additionally, his work in inter-turn fault diagnosis and real-time system protection showcases applied engineering skills with a focus on practical solutions for modern grid challenges. His experience spans theoretical research, model development, and algorithm implementation in live or simulated systems, establishing him as a well-rounded researcher in academia and an emerging leader in AI-enabled power engineering technologies.

Research Interest

Amir Hossein Poursaeed’s research interests are rooted in the intersection of electrical power systems and artificial intelligence. His primary focus includes power system stability, digital protection systems, fault detection, and the integration of renewable energy sources. He is especially passionate about leveraging advanced machine learning and explainable AI techniques for enhancing grid reliability and system monitoring. His recent work involves deep learning, support vector machines, and quantum neural networks applied to inverter-based power systems and DC microgrids—fields gaining global relevance due to the rise of decentralized energy systems. Optimization algorithms, transient analysis, and wide-area protection schemes are other key domains of his expertise. He also extends his knowledge into environmental systems, working on AI-based models for water quality assessment. This multidisciplinary approach underlines his goal of developing intelligent, robust, and real-time frameworks for smart grid operations, making his research both innovative and impactful in addressing contemporary and future challenges in energy systems.

Award and Honor

Although specific awards and honors are not listed, Amir Hossein Poursaeed’s academic and research accomplishments position him as a candidate deserving of high recognition. His publication record in prestigious Q1 journals, such as Applied Soft Computing, Energy Reports, and Sustainable Energy Technologies and Assessments, reflects scholarly excellence. His papers have introduced novel contributions to power system protection and AI-based monitoring, often co-authored with leading international experts—an indication of his growing reputation in the field. His research has also been accepted at major IEEE conferences, including the International Universities Power Engineering Conference and the International Conference on Electric Power and Energy Conversion Systems, which highlights peer recognition of his work. Moreover, his interdisciplinary research in water resource management using machine learning models demonstrates his versatility and impact beyond core power engineering. Given these achievements, he is highly deserving of academic awards, particularly those that celebrate emerging researchers and innovators in smart energy systems.

Conclusion

Amir Hossein Poursaeed is an emerging thought leader in the field of power systems and intelligent energy technologies. With a strong educational background and a research focus on AI-driven solutions for grid stability and protection, he has consistently demonstrated excellence in both theoretical innovation and practical application. His contributions span power engineering, machine learning, and even environmental sciences—showcasing his ability to bridge disciplines for impactful solutions. Through numerous high-impact publications and international conference engagements, he has established himself as a respected voice in the global research community. His work addresses critical challenges in inverter-based grids, renewable integration, and real-time monitoring, aligning perfectly with the global shift toward sustainable and resilient energy systems. Amir’s trajectory reflects not only technical brilliance but also research leadership, collaboration, and a vision for smarter, safer, and more efficient power systems. He is undoubtedly a strong candidate for honors such as the Best Researcher Award.

Publications Top Notes

  • Title: An Ultra-Fast Directional Protection Scheme for DC Microgrids Based on High-Order Synchrosqueezing Transform
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2023
    Citations: 7

  • Title: Online Transient Stability Assessment Implementing the Weighted Least-Square Support Vector Machine with the Consideration of Protection Relays
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2025
    Citations: 6

  • Title: A New Strategy for Prediction of Water Qualitative and Quantitative Parameters by Deep Learning-Based Models with Determination of Modelling Uncertainties
    Authors: M. Poursaeid, A.H. Poursaeed
    Year: 2024
    Citations: 6

  • Title: Online Voltage Stability Monitoring and Prediction by Using Support Vector Machine Considering Overcurrent Protection for Transmission Lines
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2020
    Citations: 6

  • Title: High‐Speed Algorithm for Fault Detection and Location in DC Microgrids Based on a Novel Time–Frequency Analysis
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2024
    Citations: 3

  • Title: Hydraulic Modeling of the Water Resources Using Learning Techniques
    Authors: M. Poursaeid, A.H. Poursaeed, S. Shabanlou
    Year: 2022
    Citations: 3

  • Title: Explainable AI-Driven Quantum Deep Neural Network for Fault Location in DC Microgrids
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2025
    Citations: 2

  • Title: Simulation Using Machine Learning and Multiple Linear Regression in Hydraulic Engineering
    Authors: M. Poursaeid, A.H. Poursaeed, S. Shabanlou
    Year: 2023
    Citations: 2

  • Title: Optimized Explainable Tabular Transformer Model for Fault Localization in DC Microgrids
    Authors: A.H. Poursaeed, F. Namdari, P.A. Crossley
    Year: 2025
    Citations: 1

  • Title: Optimal Coordination of Directional Overcurrent Relays: A Fast and Precise Quadratically Constrained Quadratic Programming Solution Methodology
    Authors: A.H. Poursaeed, M. Doostizadeh, S. Hossein Beigi Fard, A.H. Baharvand, F. Namdari
    Year: 2024
    Citations: 1

Milind Cherukuri | Computer Science | Young Researcher Award

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Mr. Milind Cherukuri | Computer Science | Young Researcher Award

Salesforce Business Analyst & Administrator at University of North Texas, United States

Milind Cherukuri is a dynamic early-career researcher and technologist with a strong foundation in artificial intelligence, machine learning, and software engineering. With a Master’s in Computer Science from the University of North Texas, he has applied his expertise across leading organizations such as Caris Life Sciences, Amazon, and Infor. His research spans sentiment analysis, AI safety, LLM prompt engineering, and image segmentation, resulting in five peer-reviewed publications and presentations at major conferences like IEEE AI Summit and EEET 2024. Milind has a proven ability to translate research into real-world impact, particularly in healthcare, where he optimized clinical systems through AI-driven automation and data integration. Recognized as a Senior Member of IEEE in 2025, he actively contributes to the research community through peer review and technical leadership. His innovative mindset, technical depth, and cross-domain contributions position him as a strong candidate for the Young Researcher Award.

Professional Profile

Google Scholar

Education

Milind Cherukuri holds a Master’s degree in Computer Science from the University of North Texas, where he deepened his expertise in artificial intelligence, data science, and advanced software systems. Prior to that, he earned his Bachelor’s degree in Computer Science from SRM University, Chennai, India. His academic journey reflects a consistent focus on technical excellence, with coursework and projects covering machine learning, sentiment analysis, and cloud computing. During his graduate studies, Milind engaged in applied research initiatives and honed his skills in experimental design, statistical analysis, and academic writing. He leveraged these experiences to produce scholarly work and effectively bridge theory with practice. His education provided a strong foundation for multidisciplinary research, particularly in AI-driven applications across healthcare and enterprise environments. The blend of technical depth and research exposure during his formative academic years has directly influenced his ability to contribute meaningfully to both industrial innovation and scientific advancement.

Professional Experience

Milind Cherukuri’s professional journey spans prominent roles at Caris Life Sciences, Amazon, and Infor, reflecting a robust blend of research, software development, and systems integration experience. At Caris Life Sciences, he currently serves as a Salesforce Business Analyst and Administrator, where he leads automation, healthcare data integration, and clinical research optimizations. His work has directly impacted clinical decision-making by aligning technology with operational and regulatory needs. At Amazon, he developed scalable microservices, optimized APIs, and applied AI insights to enhance customer experience and personalization. Prior to that, at Infor in India, Milind supported legacy modernization and contributed to internal research on sentiment analysis and recommendation systems. Across these roles, he demonstrated an ability to innovate at scale while contributing to internal research pipelines and tool development. His hands-on experience across cloud platforms, AI tools, and enterprise software showcases a rare ability to move seamlessly between engineering execution and applied research.

Research Interest

Milind Cherukuri’s research interests lie at the intersection of artificial intelligence, machine learning, sentiment analysis, and safe AI deployment. He is passionate about building explainable, reliable, and application-driven AI systems that serve real-world domains such as healthcare, e-commerce, and cloud ecosystems. His work focuses on areas like multi-dimensional emotion representation, AI safety frameworks for large language models, and optimization techniques for prompt engineering. Milind is particularly interested in how AI can be made more context-aware, ethically responsible, and efficient when integrated into critical infrastructure. His research explores both the theoretical underpinnings of AI algorithms and their translation into user-centric applications. He uses tools such as TensorFlow, scikit-learn, Databricks, and Keras for prototyping and experimentation. Milind’s commitment to conducting reproducible and impactful research is evident through his multiple peer-reviewed publications and active participation in academic peer review and conference presentations.

Award and Honor

Milind Cherukuri has received several accolades that underscore his excellence in both research and professional performance. In 2025, he was elevated to the grade of Senior Member of IEEE, recognizing his significant contributions to engineering and AI research at a relatively early stage in his career. He has authored five peer-reviewed publications across reputable venues and conferences, including IEEE AI Summit and EEET 2024. His work has been cited in discussions on AI safety and ethics, especially regarding GPT-5 development strategies. Within industry roles, Milind earned recognition for developing fault-tolerant systems at Amazon and for improving automation workflows at Caris Life Sciences, boosting operational efficiency by over 30%. He has also contributed as a peer reviewer for research journals, enhancing his engagement with the broader scientific community. These honors reflect a balanced profile of innovation, leadership, and commitment to advancing technology responsibly and effectively.

Conclusion

Milind Cherukuri embodies the qualities of a forward-thinking, multidisciplinary researcher who bridges the worlds of academia and industry with exceptional skill. His educational foundation, professional achievements, and focused research trajectory demonstrate a rare combination of depth and adaptability. From developing scalable software at Amazon to integrating AI solutions in clinical workflows at Caris Life Sciences, he has consistently shown the ability to convert research insights into real-world impact. Milind’s publications, IEEE recognition, and conference engagements highlight his dedication to advancing AI in safe, ethical, and application-driven ways. His involvement in peer review and technical documentation further signals his readiness to contribute to and shape the global research landscape. With a passion for innovation, a track record of scholarly contributions, and strong industry credibility, Milind stands out as a compelling candidate for honors such as the Young Researcher Award, and is poised for continued impact in the field of computer science and artificial intelligence.

Publications Top Notes

  • Title: Comparing Image Segmentation Algorithms
    Author: M. Cherukuri
    Year: 2024
    Citations: 3

  • Title: Cost, Complexity, and Efficacy of Prompt Engineering Techniques for Large Language Models
    Author: M. Cherukuri
    Year: 2025
    Citations: 1

  • Title: WebChecker: A Versatile EVL Plugin for Validating HTML Pages with Bootstrap Frameworks
    Author: M. Cherukuri
    Year: 2025
    Citations: 1

  • Title: Advancing AI Safely: Frameworks and Strategies for the Development of GPT-5 and Beyond
    Author: M. Cherukuri
    Year: 2025
    Citations: 1

  • Title: Exploring Multi-Dimensional Sentiment Analysis: A Study on Emotion Representation Structures and Prediction Models
    Author: M. Cherukuri
    Year: 2024

Evelina Domashevskaya | Materials Science | Best Researcher Award

Published on by World Top Scientists

Prof. Dr. Evelina Domashevskaya | Materials Science | Best Researcher Award

Professor at Voronezh State University, Russia

Professor Evelina Pavlovna Domashevskaya is a distinguished scientist and academic at Voronezh State University, Russia, with a PhD in Physics earned at the age of 32. She has made significant contributions to science, evidenced by over 300 publications in national and international journals and presentations at more than 70 conferences. Recognized as an Academician of the Russian Academy of Natural Sciences and an Honored Scientist of the Russian Federation, she also serves as an expert in the Federal Register of Experts in the Scientific and Technical Sphere. Her accolades include winning the prestigious 2021 All-Russian Competition “Golden Names of Higher School.” Currently, she leads cutting-edge research on hybrid core-shell systems for targeted drug delivery, funded by the Russian Science Foundation (Grant No. 25-22-00292). Her work reflects a blend of academic excellence, national recognition, and impactful scientific inquiry, making her a prominent figure in the field of materials science and applied physics.

Professional Profile 

Scopus Profile
ORCID Profile

Education

Professor Evelina Pavlovna Domashevskaya completed her PhD in Physics from Voronezh State University, Russia, at the age of 32. Her academic training provided a strong foundation in materials science and solid-state physics. Through rigorous study and early research involvement, she developed expertise in experimental and theoretical approaches to advanced materials. Her educational background laid the groundwork for a lifelong commitment to scientific inquiry and innovation. As a graduate of one of Russia’s prominent universities, she benefited from exposure to high-caliber faculty and a robust research environment. Her academic development was also shaped by the changing landscape of science and technology in post-Soviet Russia, which demanded adaptability and deep technical knowledge. Over the years, her education has evolved through continuous learning and active participation in scientific communities, enabling her to stay at the forefront of research in physics, nanostructures, and materials applications for health and technology.

Professional Experience

Professor Domashevskaya has had a long and impactful professional career at Voronezh State University, where she currently holds a professorship. Over the years, she has served in various academic and research roles, playing a pivotal part in advancing the university’s scientific reputation. With experience in lecturing, mentoring graduate students, and leading research projects, she has significantly contributed to the university’s physics department. Her leadership extends beyond teaching, encompassing research management, grant coordination, and academic program development. She has presented her work at over 70 national and international conferences, facilitating scholarly exchange and collaboration. In addition to her institutional duties, she is also a registered expert in the Federal Register of Experts in the Scientific and Technical Sphere of the Ministry of Science and Higher Education of the Russian Federation. This role highlights her expertise and reliability in assessing and guiding scientific developments across Russia’s academic and technical sectors.

Research Interest

Professor Domashevskaya’s research centers on materials science, nanotechnology, and their applications in biomedical engineering. Her work explores the structure and properties of nanostructured and hybrid materials, with a particular focus on porous silicon and its potential for targeted drug delivery systems. She investigates the sorption and luminescent properties of core-shell hybrid systems, aiming to develop innovative materials for healthcare applications. Her interdisciplinary approach bridges physics, chemistry, and medicine, contributing to the development of functional materials with real-world utility. Her ongoing research, supported by the Russian Science Foundation through Grant No. 25-22-00292, reflects her commitment to solving complex scientific problems with societal relevance. By integrating experimental research with theoretical modeling, she aims to enhance the performance and specificity of drug delivery systems, opening new possibilities in diagnostics and therapy. Her interests also extend to spectroscopy, thin films, and interface physics, marking her as a versatile and forward-thinking researcher.

Award and Honor

Professor Evelina Domashevskaya has earned numerous accolades that highlight her excellence and impact in science and academia. She is an Academician of the Russian Academy of Natural Sciences, reflecting her status as a leading expert in her field. Her designation as an Honored Scientist of the Russian Federation underscores her contributions to national scientific advancement. In 2021, she was a recipient of the prestigious “Golden Names of Higher School” award, which recognizes outstanding educators and researchers across Russia. Additionally, she has been entrusted as an expert in the Federal Register of Experts in the Scientific and Technical Sphere, affirming her credibility in evaluating national research initiatives. Her most recent achievement includes securing the Russian Science Foundation Grant No. 25-22-00292 for her pioneering research on hybrid nanostructures for drug delivery (2025–2026). Collectively, these honors validate her scientific leadership, innovation, and dedication to advancing the frontiers of applied and theoretical physics.

Conclusion

Professor Evelina Pavlovna Domashevskaya stands as a highly accomplished scientist whose career blends academic rigor, research innovation, and national service. With a PhD from Voronezh State University and a professorship at the same institution, she has made sustained contributions to materials science and nanotechnology. Her over 300 publications and participation in 70+ scientific conferences reflect an active and influential research profile. Recognized as an Honored Scientist and Academician, she has also earned top honors such as the “Golden Names of Higher School” award and prestigious national research grants. Her work on hybrid nanostructures for targeted drug delivery represents a critical intersection of physics and medicine, offering high societal impact. Through her mentorship, publications, and service to the scientific community, Professor Domashevskaya has proven herself to be a leader in Russian and international research. She is an exemplary candidate for top research awards, with a career marked by innovation, dedication, and excellence.

Publications Top Notes

  • Title: Feature of Nonlinear Electromagnetic Properties and Local Atomic Structure of Metals in Two Systems of Nanocomposites Cox(MgF2)100−x and (CoFeZr)x(MgF2)100−x
    Authors: E.P. Domashevskaya, S.A. Ivkov, E.A. Gan’shina, V.G. Vlasenko, A.V. Sitnikov
    Year: 2025

  • Title: Microstructural and Hydrophilic Properties of Polylactide Polymer Samples with Various 3D Printing Patterns
    Authors: A.S. Lenshin, V.E. Frolova, S.V. Kannykin, E.P. Domashevskaya
    Year: 2024
    Citations: 1

  • Title: Microstructural and Hydrophilic Properties of Polyethylene Terephthalate Glycol Polymer Samples with Different 3D Printing Patterns
    Authors: A.S. Lenshin, V.E. Frolova, S.A. Ivkov, E.P. Domashevskaya
    Year: 2024
    Citations: 2

  • Title: Effect of Aluminum on the Structure and Electrical Properties of Amorphous Diamond-Like Silicon-Carbon Films
    Authors: A.I. Popov, A.D. Barinov, V.M. Yemets, M.Y. Presnyakov, M.A. Shapetina
    Year: 2023

  • Title: Nonlinear Electromagnetic Properties of Thinfilm Nanocomposites (CoFeZr)x(MgF2)100−x
    Authors: E.P. Domashevskaya, S.A. Ivkov, P.V. Seredin, A.V. Sitnikov, E.A. Gan’shina
    Year: 2023
    Citations: 1

  • Title: Thin-Film Oxide Materials for Ozone Detection in Thermal Modulation Mode
    Authors: S.V. Ryabtsev, N.Y. Obvintseva, D.A.A. Ghareeb, S.Y. Turishchev, E.P. Domashevskaya
    Year: 2023
    Citations: 1

  • Title: Formation of the Al3Si Metastable Phase in Al-Si Films Obtained by Ion-Beam Sputtering According to Experimental and Theoretical Data
    Authors: V.A. Terekhov, E.P. Domashevskaya, S.I. Kurganskiĩ, A.V. Sitnikov, B.L. Agapov
    Year: 2023
    Citations: 0

  • Title: Nonlinear Transport and Magnetic/Magneto-Optical Properties of Cox(MgF2)100-x Nanostructures
    Authors: S.A. Ivkov, K.A. Barkov, E.P. Domashevskaya, A.V. Sitnikov, P.V. Seredin
    Year: 2023
    Citations: 3

  • Title: Features of the Resistive Response to Ozone of Semiconductor PdO Sensors Operating in Thermomodulation Mode
    Authors: S.V. Ryabtsev, N.Y. Obvintseva, V.V. Chistyakov, S.Y. Turishchev, E.P. Domashevskaya
    Year: 2023
    Citations: 1