Prof. Dr. Chenyu Wu | Energy Technologies | Best Researcher Award

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Prof. Dr. Chenyu Wu | Energy Technologies | Best Researcher Award

Hohai University, China

Prof. Dr. Chenyu Wu is a distinguished academic and researcher currently serving as a Professor in Jiangsu Province at the College of Energy and Electrical Engineering, Hohai University 🇨🇳. With deep expertise in power systems and electricity markets, he has authored over 20 high-impact SCI (Q1) papers and contributed to two team standards. Prof. Wu has led numerous key national and industrial projects, including those funded by the National Natural Science Foundation and the State Grid Corporation of China. His groundbreaking research has been implemented across various regions, including Jilin, Yunnan, and Myanmar. Recognized for both academic and applied excellence, he has received top-tier honors such as the First Prize of Jiangsu Province Science and Technology Award and the National Innovation and Entrepreneurship Outstanding Postdoctoral Fellow title 🏆.

Publication Profile

🎓Education Background:

Prof. Wu earned his Ph.D. in Electrical Engineering from Southeast University (2015–2019) 🎓, following a B.S. in Electrical Engineering from Hohai University (2011–2015) 📘. His academic training laid the foundation for his advanced contributions to smart grids and integrated energy systems.

💼Professional Experience:

Prof. Wu’s professional journey includes serving as a Senior Engineer at the State Grid (Suzhou) Urban Energy Research Institute (2019–2020) 🏙️. He then transitioned to academia, where he held roles as Associate Professor at Southeast University (2020–2025) and later as a Professor at Hohai University from March 2025 onward. His experience bridges industrial engineering practice and cutting-edge academic research.

🏅Awards and Honors:

Prof. Wu’s excellence has been widely recognized. Notable accolades include the First Prize in Science and Technology of Jiangsu Province (2022) 🥇, the Bronze Award in the China Postdoctoral Innovation and Entrepreneurship Competition (2022) 🥉, and the Outstanding Doctoral Dissertation Award by the China Simulation Society (2020) 📜. He is also among the elite few chosen (<1%) for the Jiangsu “333” talent project and the National Excellent Postdoctoral Fellow title 🌟.

🔬Research Focus:

His core research areas include the optimal operation of integrated energy systems, virtual power plants, active distribution networks, and electricity market bidding strategies ⚡. He integrates concepts from distributed optimization, differential game theory, and reverse engineering to advance clean, efficient energy systems aligned with smart grid development and market transformation.

✅Conclusion:

Prof. Dr. Chenyu Wu stands as a thought leader in the evolving fields of power system optimization and energy economics. His impactful publications, prestigious awards, and active academic involvement testify to his dedication to sustainable energy innovation and system-wide transformation 🌍📈.

📚Top Publications:

A Two-Stage Game Model for Combined Heat and Power Trading Market – IEEE Transactions on Power Systems, 2019 | Cited by: 240+

Energy Trading and Generalized Nash Equilibrium in Combined Heat and Power Market – IEEE Transactions on Power Systems, 2020 | Cited by: 200+

Coordinated Optimal Power Flow for Integrated Active Distribution Network and Virtual Power Plants Using Decentralized Algorithm – IEEE Transactions on Power Systems, 2021 | Cited by: 180+

Competitive Equilibrium Analysis for Renewables Integration in Dynamic Combined Heat and Power Trading Market – IEEE Transactions on Power Systems, 2023 | Cited by: 30+

Model-Free Economic Dispatch for Virtual Power Plants: An Adversarial Safe Reinforcement Learning Approach – IEEE Transactions on Power Systems, 2023 | Cited by: 25+

Combined Economic Dispatch Considering the Time-Delay of District Heating Network – IEEE Transactions on Sustainable Energy, 2018 | Cited by: 150+

Bi-level Optimization Model for Integrated Energy System Considering the Thermal Comfort of Heat Customers – Applied Energy, 2018 | Cited by: 180+

Mr. Mihai Ciobotea | Analysis | Innovative Research Award

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Mr. Mihai Ciobotea | Analysis | Innovative Research Award

Senior Engineer & Associated Teacher, SN Nuclearelectrica SA / ASE Bucharest, Romania

Mihai Ciobotea is a seasoned Management Professional from Bucharest, Romania, with deep expertise in finance, risk management, and change leadership. With an impressive career spanning over two decades, Mihai has held prominent positions in leading organizations like S.N. Nuclearelectrica S.A., OMV Petrom, and Hewlett-Packard. His unique blend of technical and managerial proficiency, supported by an MBA in Finance and ongoing doctoral research, has positioned him as a thought leader in Enterprise Risk Management and business process optimization. Passionate about business excellence, Mihai thrives on strategic planning and fostering strong professional relationships.

Publication Profile

ORCID

🎓 Education Background

Mihai holds a Bachelor’s Degree in Engineering from Universitatea Politehnica, Bucharest (1991–1997) and earned an MBA in Finance from the Romanian-Canadian MBA Program (2007–2009). He is currently a PhD candidate in Statistics & Cybernetics at Academia de Studii Economice, Bucharest (2020–present). He also pursued doctoral studies at Universitatea Politehnica (1999–2007). Additionally, Mihai has enriched his expertise through international certifications, including Six Sigma Green Belt, R & Python courses from HarvardX, and data science training from MITx and IDBx.

💼 Professional Experience

Mihai currently serves as a Specialist Engineer at S.N. Nuclearelectrica S.A., where he leads initiatives on business continuity, emergency flow integration, and BPMN modeling. Previously, as a Risk Analyst at the same organization, he developed a comprehensive Enterprise Risk Management (ERM) framework and a unique risk database. His journey also includes vital roles such as Business Intelligence Analyst at Pathwwway and Performance Manager at OMV Petrom, where he led strategic projects including field redevelopment and budgeting. His early experience includes impactful contributions as Change Manager and Quality Manager at HP, establishing performance and continuity frameworks, and pioneering risk-focused technology implementation across hundreds of sites.

🏅 Awards and Honors

While specific formal awards are not listed, Mihai’s leadership in high-value projects such as a €1 billion polymer injection field redevelopment, successful ERP integration post-M&A, and the implementation of Six Sigma frameworks at HP, are testaments to his professional recognition. His role as an Associated Teacher at Academia de Studii Economice further reflects his academic contribution and peer acknowledgment.

🔬 Research Focus

Mihai’s research interests lie at the intersection of digital transformation, enterprise risk, and financial innovation. He has authored several impactful journal articles on topics such as employment trends in digital economies, ethical auditing practices, datafication, data visualization in finance, and Romania’s renewable energy investments. His scholarly work uses statistical and probabilistic modeling, driven by a strong commitment to data integrity and evidence-based strategy development.

🔚 Conclusion

Mihai Ciobotea stands out as a dynamic professional bridging the gap between business strategy and technical acumen. With a strong academic foundation, leadership in critical industrial projects, and an expanding publication portfolio, he continues to shape the future of risk and innovation management across Europe and beyond.

📝 Publication Top Notes

The Interactions Between Digitalization, Innovation and Employment in European Companies: Insights from a Latent Class Analysis
Published: 2025 – Journal: Economies
Cited by: Pending as it’s newly published

Ethical Conduct and Independence in Audit and Control of Public Institutions in Romania: A Case Study
Published: 2024 – Journal: Oblik i finansi
Cited by: 1 article (Crossref)

European Perspectives on Datafication
Published: 2024 – Journal: Ovidius University Annals. Economic Sciences Series
Cited by: Pending

The Role of Data Visualization in the Finance – The Case of Publicly Listed EdTech Companies
Published: 2024 – Journal: Ovidius University Annals. Economic Sciences Series
Cited by: Pending

Data–Driven Analysis of Romania’s Renewable Energy Landscape and Investment Uncertainties
Published: 2024 – Journal: Heliyon
Cited by: 3 articles (Scopus)

An Analysis of Network Effects and the Financial Performance of Online Learning Platforms
Published: 2023 – Journal: Ovidius University Annals. Economic Sciences Series
Cited by: 2 articles (Crossref)

Dr. Saikat Gochhait | Artificial Intelligence | Best Researcher Award

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Dr. Saikat Gochhait | Artificial Intelligence | Best Researcher Award

Assistant Professor, Symbiosis International (Deemed to be University), India

Dr. Saikat Gochhait is an accomplished Indian academic, researcher, and innovator, currently serving as an Assistant Professor at Symbiosis International Deemed University, Pune. With a strong background in management, information technology, and behavioral sciences, he also contributes as a Research Team Member at the Symbiosis Centre for Behavioral Sciences and Adjunct Faculty at the Neuroscience Research Institute, Samara State Medical University, Russia. He is a prolific inventor with several published patents and has been recognized for his contributions to interdisciplinary research in artificial intelligence, neuroscience, and optimization algorithms.

Publication Profile

🎓 Education Background

Dr. Gochhait earned his Doctor of Philosophy (Ph.D.) in Management from Sambalpur University in 2014 🧠, a Master’s in Business Management from the same university in 2009 📊, and a Master’s in Information Technology from Sikkim Manipal University in 2017 💻. His diverse academic training has laid a multidisciplinary foundation that supports his cross-functional research across business, IT, and neuroscience domains.

💼 Professional Experience

With over two decades of experience spanning academia and industry, Dr. Gochhait has held key roles such as Assistant Professor at ASBM University, Khalikote University, and HOD at Sambhram Institute of Technology. His industry experience includes strategic roles at IFGL Refractories Ltd. and Tata Krosaki Refractories Ltd. Currently, at Symbiosis International University, he mentors postgraduate and doctoral students, manages AI-centric research projects, and continues collaborative ventures with prestigious institutions including IIT Roorkee and international universities 🌏.

🏆 Awards and Honors

Dr. Gochhait has been honored as a Senior Member of IEEE in 2019 and recognized by the Alpha Network of the Federation of European Neuroscience Societies in 2024 🌟. His academic excellence has earned him international research fellowships from leading institutions, including the Natural Sciences and Engineering Research Council of Canada, Samara State Medical University (Russia), National Dong Hwa University (Taiwan), and the University of Deusto (Spain), with total grants exceeding USD 20,000 💰.

🔬 Research Focus

Dr. Gochhait’s research is rooted in artificial intelligence, behavioral science, energy prediction, bio-inspired optimization algorithms, and neuroscience-enhanced technology applications 🧬. He is a principal investigator of high-impact government-funded projects such as AI-based load forecasting for dispatch centers and BCI-integrated neurofeedback games. His innovations also extend to smart agriculture and transport systems, reflecting his dedication to societal improvement through technology 🤖🌱.

✅ Conclusion

Blending visionary academic pursuit with innovative problem-solving, Dr. Saikat Gochhait continues to drive global research collaborations, mentor emerging scholars, and contribute meaningful technological solutions to real-world challenges 📚🌍. His evolving body of work bridges disciplines, industries, and nations, making him a respected figure in AI, management, and neuroscience research.

📚 Top Publications

Pufferfish Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems
Biomimetics, 2024 – Indexed in Scopus/WoS
Cited by: 12 articles

Dollmaker Optimization Algorithm: A Novel Human-Inspired Optimizer for Solving Optimization Problems
International Journal of Intelligent Engineering and Systems, 2024 – Indexed in Scopus
Cited by: 9 articles

Addax Optimization Algorithm: A Novel Nature-Inspired Optimizer for Solving Engineering Applications
International Journal of Intelligent Engineering and Systems, 2024 – Indexed in Scopus
Cited by: 7 articles

Enhancing Household Energy Consumption Predictions Through Explainable AI Frameworks
IEEE Access, 2024 – Indexed in Scopus/WoS
Cited by: 15 articles

URL Shortener for Web Consumption: An Extensive and Impressive Security Algorithm
 Indonesian Journal of Electrical Engineering and Computer Science, 2024 – Indexed in Scopus
 Cited by: 6 articles

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.

Dr. Maria Antonietta Grignano | ATP engineering | Best Researcher Award

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Dr. Maria Antonietta Grignano | ATP engineering | Best Researcher Award

Unit of Nephrology, Dialysis and Transplantation, IRCCS Foundation Policlinico San Matteo of Pavia, Italy

Maria Antonietta Grignano is a dedicated biologist and clinical researcher at the Unit of Nephrology, Dialysis, and Transplantation at Fondazione IRCCS Policlinico San Matteo di Pavia, Italy. With specialization in clinical pathology and clinical biochemistry, she has significantly contributed to translational nephrology research, focusing on extracellular vesicles, ischemic damage, and innovative drug delivery strategies. Her work bridges molecular biology and clinical application, aiming to improve outcomes in kidney transplantation and chronic kidney disease.

Publication Profile

🎓 Education Background:

Maria holds a Bachelor’s Degree in Biological Sciences from the University of Palermo (2006–2010), followed by a Master’s Degree in Experimental and Applied Biology from the University of Pavia (2010–2012). She further specialized in Clinical Biochemistry and Clinical Pathology at the University of Pavia from 2017 to 2021, gaining advanced expertise in clinical and diagnostic research.

💼 Professional Experience:

Since 2014, Maria has been an integral part of the Fondazione IRCCS Policlinico San Matteo, contributing first as a research fellow, then under various research contracts, and eventually as the head of the Research Laboratory within the Nephrology Unit. Between 2018 and 2019, she researched virus-specific antibody responses in transplant patients, and earlier, she also worked in pediatric hematology oncology. Her current role since December 2019 as a lead researcher reflects her long-term dedication to advancing nephrology through laboratory-based innovation.

🏆 Awards and Honors:

While specific awards and honors are not listed publicly, Maria’s continuous appointments at one of Italy’s top clinical research institutes, her leadership of multiple innovative projects, and her extensive publication record in high-impact journals underscore her recognition and credibility in the nephrology research community.

🔬 Research Focus:

Maria’s research revolves around the therapeutic potential of extracellular vesicles derived from mesenchymal stem cells, particularly in reducing ischemia-reperfusion injury during kidney transplantation. She is also exploring the modulation of immune responses in chronic kidney disease, including the effect of PCSK9 inhibitors, and has participated in projects correlating transcriptional profiles with response to extracorporeal photo-apheresis. Her projects integrate advanced bioengineering, clinical immunology, and proteomics.

🧾 Conclusion:

Maria Antonietta Grignano exemplifies scientific commitment and clinical relevance through her research in nephrology and transplantation. Her work in cellular therapies and biomarker discovery not only advances the field but also holds promise for patient-specific interventions and improved transplant outcomes.

📚 Top Publications :

Engineered ATP-Loaded Extracellular Vesicles Derived from Mesenchymal Stromal Cells: A Novel Strategy to Counteract Cell ATP Depletion in an In Vitro Model
International Journal of Molecular Sciences, 2025
Cited by: Ongoing

Atypical Hemolytic Uremic Syndrome Associated with BNT162b2 mRNA COVID-19 Vaccine in a Kidney Transplant Recipient: A Case Report and Literature Review
Infectious Disease Reports, 2025
Cited by: Ongoing

The Impact of Serum/Plasma Proteomics on SARS-CoV-2 Diagnosis and Prognosis
International Journal of Molecular Sciences, 2024
Cited by: Ongoing

Characterization of Mesenchymal Stromal Cells after Serum Starvation for Extracellular Vesicle Production
Applied Sciences, 2024
Cited by: Ongoing

Uremic plasma proteins accumulate in peripheral blood mononuclear leukocytes inducing apoptosis: insights in the immuno-proteostasis response of chronic kidney disease
ResearchSquare, 2023
Cited by: Ongoing

Dr. Anis Fradi | Statistics | Best Researcher Award

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Dr. Anis Fradi | Statistics | Best Researcher Award

Assistant professor, Lumière University Lyon 2, Claude Bernard University Lyon 1, ERIC, France

Dr. Anis Fradi is a dedicated academic and researcher in the fields of computer science and applied mathematics, currently serving as an Associate Professor at Université Lumière Lyon 2, France. With a strong interdisciplinary background and a passion for machine learning, optimization, and Bayesian inference, he brings a wealth of experience in developing efficient, interpretable models for high-dimensional and structured data. His work bridges theoretical foundations and practical applications, especially in areas like image classification, regression models, and manifold-valued data analysis. 🇫🇷💻📊

Publication Profile

🎓 Education Background

Dr. Fradi earned a dual PhD in Computer Science from Université Clermont Auvergne, France, and Applied Mathematics from the University of Monastir, Tunisia (2017–2021). His thesis focused on Bayesian Inference in 2D and 3D Shape Analysis. He also holds a Research Master’s Degree in Mathematics and Applications (2013–2015, University of Sousse) with honors and a Bachelor’s Degree in Mathematics and Applications (2010–2012) from the same university. His academic journey reflects a solid foundation in mathematical modeling and algorithmic development. 📘📐👨‍🎓

💼 Professional Experience

Dr. Fradi began his career as a lecturer in Tunisia before transitioning to multiple academic roles in France. He has served as a Postdoctoral Researcher at CNRS-LIMOS and Inria Bordeaux – Sud-Ouest, focusing on learning on manifolds and probabilistic representations. Between 2023 and 2024, he was a Temporary Lecturer and Research Assistant at Université Clermont Auvergne. Since September 2024, he has held a permanent Associate Professorship at Université Lumière Lyon 2, contributing to both teaching and research in computer science and data mining. 🏫📈🧠

🏅 Awards and Honors

Dr. Fradi has been recognized for his impactful contributions to AI and data science. He received the Best Paper Award at PRICAI 2023 in Jakarta and the prestigious CNRS 80|Prime Award, a competitive French national research incentive. These accolades highlight his innovative work in robust AI models and inference techniques. 🏆🎖️📚

🔍 Research Focus

His research revolves around Bayesian learning, manifold-valued data, Gaussian processes, optimization, and interpretable AI. He aims to reduce computational complexity while maintaining model accuracy and robustness. His work is especially prominent in image classification, regression models with low complexity, and analysis on non-Euclidean spaces such as Riemannian manifolds. 🧮🤖🌐

🔚 Conclusion

Dr. Anis Fradi stands out as a thought leader blending advanced mathematical concepts with modern AI to solve complex real-world problems. His career is marked by interdisciplinary excellence, international collaborations, and a commitment to both innovation and education in data science and machine learning. 🚀📚🌍

📚 Top Publications 

ConvKAN: Towards Robust, High-Performance and Interpretable Image Classification – 2025, Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Cited by: Early impact; award-nominated contribution in interpretable AI and convolutional kernel adaptive networks.

Decomposed Gaussian Processes for Efficient Regression Models with Low Complexity – 2025, Entropy (MDPI)
Cited by: Researchers in scalable Bayesian models and metamodeling; rapidly gaining attention.

A New Bayesian Approach to Global Optimization on Parametrized Surfaces in R3\mathbb{R}^3 – 2024, Journal of Optimization Theory and Applications
Cited by: Mathematicians and data scientists working on optimization and 3D surface modeling.

A New Framework for Evaluating the Validity and the Performance of Binary Decisions on Manifold-Valued Data – 2024, Book Chapter
Cited by: Scholars focusing on non-Euclidean data analysis and manifold learning.

Reduced Run-Time and Memory Complexity Regression with a Gaussian Process Prior – 2024, Conference Paper (HAL)
Cited by: Applications in real-time systems and efficient predictive modeling.

Dr. Fei Long | Power Systems | Most Cited Article Award

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Dr. Fei Long | Power Systems | Most Cited Article Award

Lecturer, China Three Gorges University, China

Dr. Fei Long is a dedicated Lecturer and Postdoctoral Researcher at the School of Electrical Engineering and New Energy, China Three Gorges University 🇨🇳. With a deep-rooted passion for systems control and stability, he has significantly contributed to the advancement of control theory, especially in time-delay and power systems. Known for his academic rigor and innovation, Dr. Long is actively engaged in top-tier research that addresses critical challenges in modern power systems. 📊🔋

Publication profile

Scopus

🎓 Education Background

Dr. Long earned his Ph.D. in Control Science and Engineering from China University of Geosciences (Wuhan) 🎓 between September 2016 and June 2022. Prior to this, he completed his undergraduate studies in Electrical Engineering and Automation at Hubei University of Technology from 2011 to 2015 ⚡📚.

💼 Professional Experience

Since June 2022, Dr. Fei Long has been serving as a Lecturer and Postdoctoral Researcher at China Three Gorges University. His role involves both teaching and conducting cutting-edge research in the field of electrical engineering and control systems. 🏫🔍

🏆 Awards and Honors

Dr. Long is the Principal Investigator of a National Natural Science Foundation of China (Youth Science Fund Project) 🧪. Notably, two of his research papers have been recognized as ESI Highly Cited Papers, placing them in the top 1% of citations worldwide 🌍📈—a testament to the global impact of his research.

🔬 Research Focus

Dr. Long’s primary research interests lie in the stability and robust control of time-delay systems and power systems ⏳⚙️. His work emphasizes innovative mathematical modeling and control strategies to enhance system resilience and performance, particularly in neural networks and energy systems integration.

✅ Conclusion

With a robust academic background, impactful research contributions, and a strong focus on systems stability, Dr. Fei Long stands out as a prominent young researcher in the field of electrical and control engineering. His commitment to excellence and scholarly achievement continues to inspire and shape the future of sustainable energy systems. 🚀📘

📚 Top Publication Notes

IEEE Transactions on Cybernetics (2022) Highly cited paper, recognized for its innovation in delay systems control (Cited by 100+ articles).

IEEE Transactions on Neural Networks and Learning Systems (2023) – Advanced delay-product-type functionals (Cited by 80+ articles).

Automatica (2020) – A key contribution to relaxed matrix inequalities (Cited by 120+ articles).

IEEE Transactions on Systems, Man, and Cybernetics: Systems (2021) – Used in applied power systems and neural networks (Cited by 90+ articles).

Applied Mathematics and Computation (2019) –  Mathematical advancements in delay control theory (Cited by 85+ articles).

IEEE Transactions on Cybernetics (2024) –  Recent breakthrough in delayed neural networks stability.

Mr. Huifa Jiang | Numerical Solutions | Best Researcher Award

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Mr. Huifa Jiang | Numerical Solutions | Best Researcher Award

Lecturer, Hunan University of Technology, China

Huifa Jiang is a dedicated academic currently serving as a Lecturer at Hunan University of Technology, China. With a passion for applied mathematics, particularly in solving complex partial and fractional differential equations, she has contributed significantly to the field through innovative numerical methods. Her research is deeply rooted in precision, efficiency, and scientific rigor, and she has already authored multiple papers in SCI-indexed journals. Despite being at an early stage in her career, Huifa’s work demonstrates a mature understanding of computational mathematics and its applications.

Publication Profile

🎓 Education Background

Huifa Jiang earned both her Master’s (2019) and Ph.D. (2022) degrees from Hunan Normal University, specializing in numerical methods for partial differential equations (PDEs). During her graduate studies, she honed her expertise in fractional differential equations and computational techniques, which laid the groundwork for her subsequent research contributions.

👩‍💼 Professional Experience

Currently a Lecturer at Hunan University of Technology, Huifa Jiang is involved in teaching and research in applied mathematics. Her professional journey is marked by a focused academic trajectory, with a special emphasis on numerical solutions and mathematical modeling, particularly in time-fractional equations. She is actively contributing to advancing computational solutions in her area of specialization.

🏆 Awards and Honors

While Huifa Jiang has not listed any formal awards yet, her academic credentials are noteworthy. She has published 3 SCI-indexed journal articles, achieving a Google Scholar citation count of 27, with an H-index of 2 and an i10-index of 1 — promising metrics reflecting her emerging influence in the research community.

🔬 Research Focus

Huifa’s research primarily revolves around the numerical solutions of partial differential equations and fractional differential equations. A highlight of her work includes the development of a compact Alikhanov scheme to solve the time-fractional Kuramoto–Sivashinsky equation, significantly improving computational efficiency and accuracy. Her focus is on devising stable, convergent, and computationally economical methods, with practical implications in engineering and physics-related simulations.

📚 Top Publications

A compact difference scheme for the time-fractional Kuramoto–Sivashinsky equation – Applied Mathematics and Computation, 2022
🔗 Link to article – Cited by 9 articles

Compact finite difference schemes for the numerical solution of time-fractional PDEs – Computers & Mathematics with Applications, 2021
🔗 Link to article – Cited by 12 articles

Stability and convergence analysis for time-fractional diffusion equations using Alikhanov’s method – Mathematics, 2021
🔗 Link to article – Cited by 6 articles

🔚 Conclusion

Huifa Jiang is an emerging researcher whose work in numerical solutions for fractional differential equations is gaining scholarly recognition 📈. Through her analytical rigor, she has developed efficient computational schemes that address key mathematical challenges. As a young academic, her contributions are not only technically sound but also impactful in advancing computational methods in applied sciences. She holds great promise as a future leader in mathematical modeling and numerical analysis 🌟.

Prof. Dr. Otilia Manta | Artificial Intelligence | Innovative Research Award

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Prof. Dr. Otilia Manta | Artificial Intelligence | Innovative Research Award

Professor PhD, Romanian Academy, Romania

Prof. Dr. habil. Elena Otilia Manta  is a renowned economist, academic, and scientific researcher, currently serving as a Professor at the Romanian-American University and a Scientific Researcher at the Romanian Academy. With over two decades of experience in economic sciences, she is widely respected for her expertise in finance, FinTech, AI integration, and sustainable development. She also holds various leadership roles in international organizations, including Vice President of EUExperts in Brussels, reflecting her strong influence in policy and academic circles globally. 🌍💼

Publication Profile

🎓 Education Background

Prof. Manta holds a Ph.D. in Economics and the academic title of “habilitation,” enabling her to supervise doctoral research. Her education has been complemented by continuous development in areas like finance, international economic relations, and technological integration, laying a solid academic foundation for her contributions in both national and international academic communities. 🎓📖

💼 Professional Experience

Since 2014, Prof. Manta has been a Scientific Researcher at the Romanian Academy and since 2019, a full Professor at the Romanian-American University in Bucharest. She also serves as Vice President of the European Union Experts (EUExperts) and the International Research Institute for Economics and Management (IRIEM), among others. As founder and CEO of The Romanian Group for Investments and Consultancy (RGIC), she combines academic depth with real-world financial leadership. She has also served as an EU Expert and Rapporteur with the European Commission. 🌐🏛️📊

🏆 Awards and Honors

Prof. Manta has received numerous honors, including the “2006 Woman of the Year Commemorative Medal” by the American Biographical Institute. She is a respected honorary member of the Romanian-Italian Chamber of Commerce and holds various affiliations with prestigious academic, financial, and developmental organizations such as the UN HLPF Mechanism and the Financial Stability Oversight Council (NY). 🥇🎖️🌟

🔬 Research Focus

Her research focuses on FinTech, artificial intelligence integration in banking, sustainable economic development, academic transparency, and financial innovation. As an active participant in multidisciplinary fields, Prof. Manta is a frequent contributor to leading journals and conferences, continuously shaping discussions on the future of finance and digital transformation. 💡📈🤖

🔗 Publications – Top Notes

Banking Transformation Through FinTech and the Integration of Artificial Intelligence in Payments – FinTech, 2025 | DOI: 10.3390/fintech4020013 – A highly impactful paper exploring AI’s role in revolutionizing payment systems.

FinTech and AI as Opportunities for a Sustainable Economy – FinTech, 2025 | DOI: 10.3390/fintech4020010 – Widely cited for linking technology to green and inclusive finance.

The Transfer of Managerial Expertise in Romanian Companies through the Application of the DEMATEL Method – Journal for Future Society and Education, 2025 – Emphasizes decision science in corporate governance.

Ensuring Academic Integrity: Tools and Mechanisms for a Transparent Educational Environment – Preprints, 2025 – Focuses on digital tools fostering academic ethics.

🔚 Conclusion

Prof. Dr. habil. Otilia Manta is a distinguished leader, bridging the worlds of academia, finance, and international consultancy. Her career reflects a strong commitment to innovation, transparency, and global collaboration in economics. Through her scholarly research, institutional leadership, and consultancy, she continues to inspire future generations in both Romania and abroad. 🌟📘🌍

Dr. Gracia Samuel | Telecommunications | Best Researcher Award

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Dr. Gracia Samuel | Telecommunications | Best Researcher Award

Former Research Scholar, Christ University, India

Dr. Gracia Samuel is an accomplished Computer Science Researcher with over 11 years of extensive experience spanning academia, industry, and doctoral research. 📊 With a strong foundation in data analytics, she specializes in optimizing QoS (Quality of Service) and QoE (Quality of Experience) metrics in telecom networks. 📡 Her unique blend of skills in DEA (Data Envelopment Analysis), predictive modeling, and network performance benchmarking makes her a valuable asset in the field of network optimization and planning. Currently residing in Chennai, India, she is passionate about driving impactful research that contributes to smarter, more connected societies. 🌐

Publication Profile

Google Scholar

🎓 Educational Background

Dr. Gracia Samuel holds a Ph.D. in Computer Science from Christ University, Bangalore (2020–2024), where her thesis focused on benchmarking QoS and QoE metrics using DEA. 📘 She earned her M.S. in Telecommunication Networks from the prestigious Polytechnic University, now NYU Tandon School of Engineering, USA (2006–2008). 🎓 Her undergraduate journey began with a B.E. in Electronics and Communication Engineering from Karunya Institute of Technology, Coimbatore (2002–2006). 🧑‍💻 Her educational path has been firmly rooted in communication networks and data science.

💼 Professional Experience

Dr. Gracia brings rich industry and academic experience to the table. She started her career as a Programmer Analyst Trainee at Peri Software Solutions, New Jersey 🇺🇸 (2008), gaining hands-on expertise in Perl, HTML, and SQL. Later, as an Assistant Professor at VIT University (2009–2010), she led several courses and student research projects in computer networks using OPNET. 📘 Her industry roles include Senior Analyst at Ocwen Financial Solutions (2015–2017), where she conducted predictive modeling and market risk analysis using SAS and SQL, and Analyst at GE Capital (2011–2014), focusing on customer analytics and economic research. 📈

🏆 Awards and Honors

Gracia Samuel has received several accolades throughout her career 🌟. She was appreciated by the CRO and Board of Directors at GE Capital for her insights into auto lending risks. She earned multiple Gold Awards for her contributions to e-commerce and mobile analytics and for her economic data validations. 🥇 She also received a Bronze Award for efficiency and an Achievement Award for optimizing e-commerce dashboard processes. Notably, her conference paper was awarded Best Paper at the 2022 International Conference on Intelligent Computing and Technology. 🏅

🔬 Research Focus

Dr. Gracia’s research interests lie at the intersection of Data Analytics, Telecommunications, and Network Optimization. 📡 Her Ph.D. work focuses on using Slack-Based Measures in DEA to benchmark and enhance QoS/QoE in telecom services, providing actionable strategies for network planning and service improvement. She also explores predictive analytics, VANET security, 5G benchmarking, and smart network societies. Her work contributes to designing resilient, scalable, and customer-centric telecom infrastructures. 📶

📚 Top Publications 

Towards a Smarter Connected Society By Enhancing Internet Service Providers’ QoS Metrics Using Data Envelopment Analysis – ECS Transactions, 2022 – Cited by 10 articles.

An Optimal Benchmarking Technique to Improve Quality of Experience in 4G Indian Public Telecom Sector for Better Network Penetration and Fair Service Pricing – Telematique, 2023 – Cited by 7 articles.

A Case Study of Security in VANETs – International Journal of Advanced Research in Computer Science, 2011 – Cited by 5 articles.

5G Planning and QoE Management Using Mathematical Benchmarking Techniques for Europe and Middle Eastern Countries – IEEE CONECCT, 2022 – Cited by 4 articles.

5G Telecom Toolkit – Patent Office Journal, Nov 2023.

🧾 Conclusion

With a strong foundation in both theory and practice, Dr. Gracia Samuel exemplifies the convergence of academic rigor and industry relevance. 💡 Her contributions to telecom benchmarking, data analytics, and network optimization have added value to both scholarly research and operational excellence. Driven by curiosity and a commitment to technological advancement, she continues to push boundaries in creating efficient, fair, and innovative communication networks. 🌍