Dr. Fang Li | Remote sensing | Best Researcher Award

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Dr. Fang Li | Remote sensing | Best Researcher Award

lecturer, Dalian Minzu University, China

Fang Li 🎓 is a dedicated lecturer at Dalian Minzu University, China, specializing in computer science and technology. She earned her Ph.D. in 2023 from Dalian Maritime University, focusing on signal and remote sensing image processing. With a strong passion for innovation and academic excellence, she has developed a reputation for her cutting-edge work in hyperspectral image processing, anomaly detection, and real-time target detection. As an active IEEE member, Fang Li contributes significantly to the global scientific community through her impactful research and publications in top-tier journals.

Publication Profile

ORCID

🎓Education Background

Fang Li received her Ph.D. in Computer Science and Technology in 2023 from Dalian Maritime University, China 🏫. Her academic foundation is rooted in advanced image processing and hyperspectral remote sensing technologies, setting the stage for her impressive research contributions.

💼Professional Experience

Currently serving as a lecturer at Dalian Minzu University 👩‍🏫, Fang Li has been actively engaged in teaching and research activities. Her experience spans several years of dedicated work in signal processing and remote sensing, with a strong emphasis on hyperspectral imaging applications. She also played a leading role in the Excellent Doctoral Dissertation Cultivation Program at her university, showcasing her leadership in mentoring and academic development.

🏅Awards and Honors

Fang Li has received institutional recognition for her academic excellence, including being a lead figure in the Excellent Doctoral Dissertation Cultivation Program 🏆 at Dalian Maritime University. While formal international awards are pending, her scholarly work in top IEEE journals reflects her growing global impact in the research field.

🔬Research Focus

Fang Li’s research focuses on signal and remote sensing image processing, particularly hyperspectral image analysis 🌌. Her interests include anomaly detection, target detection, band fusion, and real-time data processing. With over 15 journal publications and 6 patents under process, her work contributes significantly to the advancement of remote sensing and machine learning technologies.

🧩Conclusion

Fang Li exemplifies dedication, innovation, and scholarly excellence 📚. As a rising academic in hyperspectral remote sensing, she has consistently demonstrated the potential to lead and influence cutting-edge research. Her commitment to scientific development, paired with her IEEE membership and impactful publications, positions her as a deserving candidate for the Best Researcher Award.

📘Top Publications 

Abundance Estimation Based on Band Fusion and Prioritization Mechanism
Journal: IEEE Transactions on Geoscience and Remote Sensing (2022)
Cited by: 32 articles (as per Google Scholar)

Bi-Endmember Semi-NMF Based on Low-Rank and Sparse Matrix Decomposition
Journal: IEEE Transactions on Geoscience and Remote Sensing (2022)
Cited by: 27 articles

Progressive Band Subset Fusion for Hyperspectral Anomaly Detection
Journal: IEEE Transactions on Geoscience and Remote Sensing (2022)Cited by: 25 articles

Sequential Band Fusion for Hyperspectral Anomaly Detection
Journal: IEEE Transactions on Geoscience and Remote Sensing (2022)
Cited by: 44 articles

Sequential Band Fusion for Hyperspectral Target Detection
Journal: IEEE Transactions on Geoscience and Remote Sensing (2022)
Cited by: 36 articles

Assoc. Prof. Dr. Qiansheng Zhao | Geographical information | Excellence in Research Award

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Assoc. Prof. Dr. Qiansheng Zhao | Geographical information | Excellence in Research Award

Associate Professor, Wuhan University, China

Dr. Qiansheng Zhao is a dedicated Associate Professor at the School of Geodesy and Geomatics, Wuhan University . With a solid foundation in both Computer Science and Surveying Engineering, he has contributed significantly to the fields of Geographical Information Science and 3D GIS. Dr. Zhao has played a key role in advancing digital twin technologies, marine disaster scenario modeling, and intelligent geospatial systems. He brings international research exposure, having served as a visiting scholar at the University of Tennessee, Knoxville 🇺🇸, and continues to influence the field through innovative research, publications, and technological development.

Publication Profile

🎓 Education Background:

Dr. Zhao earned dual Bachelor’s degrees in Computer Science and Surveying Engineering from Wuhan University in 2004 🎓. He completed his Ph.D. at the same institution in 2009, specializing in geospatial technologies. His multidisciplinary academic background uniquely positions him at the intersection of geoinformatics, artificial intelligence, and spatial data processing.

💼 Professional Experience:

Since 2010, Dr. Zhao has served as an Associate Professor at Wuhan University, where he leads research in 3D GIS, GeoAI, and web-based spatial systems. He was a visiting scholar at the University of Tennessee, Knoxville during 2013–2014, enriching his global perspective and collaborative engagements. His work includes national-level projects supported by the Ministry of Science and Technology of China, as well as collaborations with the Marine Security Technical Committee of the China Society of Public Security Science and Technology 🌏.

🏆 Awards and Honors:

Dr. Zhao has made impactful contributions recognized through his involvement in national R&D programs and professional committees. While specific award titles are not mentioned, his leadership roles, successful project acquisition, and consistent research output highlight his excellence in both innovation and academic research 🏅. His authored book on marine disaster scenario deduction further emphasizes his applied expertise.

🔬 Research Focus:

Dr. Zhao focuses on 3D GIS, GeoAI, and digital twin technologies. His key contributions include developing systems for dynamic web-based management and visualization of large-scale 3D models, and creating collaborative geospatial platforms using Conflict-free Replicated Data Types (CRDTs) 🌐. His recent research involves smart highway digital twins and AI-driven marine security simulations, reflecting his commitment to solving real-world problems through cutting-edge geospatial science 🤖🌊.

🧩 Conclusion:

Dr. Qiansheng Zhao is a forward-thinking geospatial scientist whose work bridges advanced computing with practical applications in geographic information systems. With a strong academic foundation, international exposure, and a prolific publication record, he continues to contribute to the global advancement of GIS technologies, smart environments, and marine spatial intelligence. His work stands as a testament to innovation and excellence in geospatial research 🚀.

📚 Top Publications :

A cloud-based framework for collaborative 3D GIS using CRDTs. ISPRS Journal of Photogrammetry and Remote Sensing. 
Cited by: 58 articles

Semantic mapping integration for smart marine disaster management. Computers, Environment and Urban Systems. 
Cited by: 44 articles

Efficient web-based visualization of massive 3D city models using edge computing. Sensors. 
Cited by: 63 articles

Digital twin-driven real-time GIS for intelligent transportation systems. International Journal of Digital Earth. 
Cited by: 36 articles

Prof. Dr. Xinchao ZHAO | Swarm Intelligence | Best Researcher Award

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Prof. Dr. Xinchao ZHAO | Swarm Intelligence | Best Researcher Award

Vice Dean, Beijing University of Posts and Telecommunications, China

Prof. Xinchao Zhao is a distinguished academic and researcher in the fields of swarm intelligence, evolutionary algorithms, and optimization, currently serving as a Professor at the School of Science, Beijing University of Posts and Telecommunications (BUPT), China. With extensive teaching and research experience, he has made significant contributions to data-driven optimization, cloud scheduling, and machine learning. His prolific academic output and international collaborations have earned him recognition in the global scientific community. 📘🔬

Publication Profile

Scopus

🎓Education Background

While specific degree details are not listed, Prof. Zhao’s academic journey is rooted in his longstanding association with Beijing University of Posts and Telecommunications, progressing from lecturer to full professor. His multidisciplinary focus reflects a strong foundation in computer science, mathematics, and artificial intelligence. 🎓📚

💼Professional Experience

Prof. Zhao began his academic career in 2005 as a Lecturer at BUPT. He advanced to Associate Professor by 2009 and was promoted to full Professor in 2014. His international experience includes visiting professorships at the University of Birmingham and the University of Essex, UK, during 2013–2014. Since then, he has continued his professorial duties at BUPT, mentoring Ph.D. candidates and leading cutting-edge research. 🌍🏫

🏆Awards and Honors

While specific awards are not mentioned, Prof. Zhao has successfully secured and led numerous prestigious national and provincial projects, including several from the National Natural Science Foundation of China and the Beijing Natural Science Foundation. His research leadership and contributions to innovation in optimization algorithms underscore his recognition and reputation. 🏅💡

🔬Research Focus

Prof. Zhao’s research primarily centers around swarm intelligence, evolutionary computation, multi-objective optimization, and their applications in fields such as cloud computing, medical image analysis, and big data. He is particularly interested in data-driven optimization algorithms, fuzzy clustering, neural architecture search, and multi-modal objective problems. His interdisciplinary approach integrates theory and application to solve complex real-world problems. 🧠🧮

🔚Conclusion

Prof. Xinchao Zhao stands as a visionary scholar whose contributions continue to shape the evolution of computational optimization and artificial intelligence. His commitment to academic excellence and innovation reflects in his impactful research, prolific publications, and active mentorship. 🌟📈

📚Top Publications 

A Budget-Constrained Workflow Scheduling Approach With Priority Adjustment and Critical Task Optimizing in Clouds
IEEE Transactions on Automation Science and Engineering, 2025
Cited by: 17 articles
Focus: Cloud workflow scheduling under budget constraints with optimized task prioritization.

Fuzzy clustering-based large-scale multimodal multiobjective differential evolution algorithm
Swarm and Evolutionary Computation, 2025
Cited by: 11 articles
Focus: Combines fuzzy clustering and differential evolution to tackle complex multiobjective problems.

An enhanced tree-seed algorithm for global optimization and neural architecture search optimization in medical image segmentation
Biomedical Signal Processing and Control, 2025
Cited by: 8 articles
Focus: Tree-seed algorithm enhancement for image segmentation and neural architecture search.

A bidirectional workflow scheduling approach with feedback mechanism in clouds
Expert Systems with Applications, 2024
Cited by: 22 articles
Focus: Integrates feedback mechanism into cloud scheduling strategies.

Hybrid Response Dynamic Multi-objective Optimization Algorithm Based on Multi-Arm Bandit Model
Information Sciences, 2024
Cited by: 15 articles
Focus: Merges dynamic response strategies with the multi-arm bandit framework for MOO.

An enhanced Runge Kutta boosted machine learning framework for medical diagnosis
Computers in Biology and Medicine, 2023
Cited by: 34 articles
Focus: Advanced ML framework integrating Runge Kutta method for enhanced diagnostics.

A novel MOPSO-SODE algorithm for solving three-objective SR-ES-TR portfolio optimization problem
Expert Systems with Applications, 2023
Cited by: 19 articles

Dr. Fathima Nuzla Ismail | Atmospheric Modeling | Best Researcher Award

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Dr. Fathima Nuzla Ismail | Atmospheric Modeling | Best Researcher Award

Postdoctoral Associate, State University of New York, United States

Dr. Nuzla Ismail is a dynamic Postdoctoral Research Fellow specializing in bioinformatics and machine learning, with a PhD in Information Science. With over a decade of experience spanning academia and industry, she has played a transformative role in over 100 global projects. Her career is driven by a passion for turning complex data into actionable insights and pioneering predictive models for real-world impact. Recognized for her innovative contributions and leadership, Dr. Ismail actively explores advanced genetic analysis, disease prediction models, and the development of scalable data systems. 🌐🧬

Publication Profile

Google Scholar

🎓 Education Background:

Dr. Ismail earned her PhD in Information Science from the University of Otago, New Zealand in 2022. She holds a dual undergraduate background with a B.Sc. from the University of Sri Jayewardenepura and a BEng (Hons) in Software Engineering from Staffordshire University, UK (2015). Her academic journey reflects a unique blend of computing, bioinformatics, and data science education. 🎓📚

💼 Professional Experience:

Currently serving as a Postdoctoral Researcher at the State University of New York, Buffalo (2025–Present), Dr. Ismail applies her bioinformatics expertise to decode complex genetic networks. She has previously held roles at the University of Otago, including Postdoctoral Fellow and Research Assistant, contributing to pioneering work in genome graphs and structural variant detection. Her industry experience includes positions such as Architect/Data Scientist at Axiata Digital Labs and Consultant at Alex Solutions. She also held technical and academic roles, showcasing her versatile skills in IT deployment, robotics education, and business intelligence systems. 💻🧑‍🔬

🏅 Awards and Honors:

Dr. Ismail is a recipient of prestigious awards such as the University of Otago Doctoral Scholarship (2017), Google Grace Hopper Scholar (2016), and the Google Anita Borg Memorial Scholarship (2014). She has also represented globally at events like the ACM Tapia Celebration of Diversity, CERN’s Port Hackathon, and the NYUAD Hackathon for Social Good. Her recognition spans innovation, leadership, and diversity in STEM. 🏆🌍

🔎 Research Focus:

Her research is focused on computational biology, genome graph methodologies, and predictive analytics for wildfire modeling and disease risk estimation. She explores machine learning, structural variant detection, and genomic simulations for human and agricultural health. Her contributions extend to AI applications in climate science and bioinformatics workflow development. 🔬🔥🌱

🧭 Conclusion:

Dr. Nuzla Ismail is an interdisciplinary innovator whose work intersects data science, genetics, and AI. With a strong global presence and a robust publication portfolio, she continues to inspire progress in bioinformatics and data-driven decision-making. She is open to new collaborations, mentorship opportunities, and knowledge-sharing in her research domains. 🌟📈

📚 Top Publications 

Modelling Methane Emissions from Rice Paddies Using Machine Learning – 2024, IVCNZ 2024.
Cited by: 3 articles.

Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads – 2023, Frontiers in Genetics.
Cited by: 9 articles.

A Comparison of One-Class Versus Two-Class Machine Learning Models for Wildfire Prediction in California – 2023, Australasian Conference on Data Science and Machine Learning.
Cited by: 5 articles.

One-Class Classification-Based Machine Learning Model for Estimating Wildfire Risk – 2023, Procedia Computer Science.
Cited by: 6 articles.

An assessment of existing wildfire danger indices in comparison to one-class machine learning models – 2024, Natural Hazards.
Cited by: 4 articles.

Evaluating the boundaries of Big Data environments for Machine Learning – 2019, AI 2019: Australasian Joint Conference.
Cited by: 11 articles.

Dr. Aiai Wang | Machine Learning | Best Researcher Award

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Dr. Aiai Wang | Machine Learning | Best Researcher Award

Doctoral student, University of Science and Technology Beijing, China

Ai-Ai Wang is a passionate and dedicated young researcher born in March 1998 in Langfang, Hebei Province, China. A proud member of the Communist Party of China (CPC), she is currently based at the University of Science and Technology Beijing (USTB), where she serves as the Secretary of the 16th Party Branch, 4 Zhaizhai. With a solid academic foundation in mining and civil engineering, Ai-Ai has excelled in both academic and research spheres, contributing significantly to digital and intelligent mining technologies. Her work emphasizes physical dynamics in tailings sand cementation and filling, showing strong potential for innovation in sustainable mining practices.

Publication Profile

Scopus

🎓Education Background:

Ai-Ai Wang completed her Bachelor of Science in Mining Engineering from North China University of Science and Technology in 2021. She further pursued her Master’s degree in Civil Engineering at the University of Science and Technology Beijing (2021.09–2024.06), affiliated with the School of Civil and Resource Engineering.

🛠️Professional Experience:

Alongside her academic journey, Ai-Ai has undertaken significant responsibilities, currently serving as Secretary of the Party Branch at USTB. Her leadership extends beyond administration into collaborative research projects, software development, and patent contributions under renowned mentors such as Prof. Cao Shuai. She has played vital roles in developing intelligent systems for mining operations, reinforcing her multidisciplinary strengths.

🏅Awards and Honors:

Ai-Ai Wang has been recognized extensively for her academic and research excellence. Notable accolades include the “Top Ten Academic Stars” at USTB (2023), a National Scholarship for Master’s Degree Students (2022), the prestigious Taishan Iron and Steel Scholarship (2023), and multiple First-Class Academic Scholarships from USTB. She was twice named an Outstanding Three-Good Graduate Student and honored by her school as an outstanding individual. Moreover, she has received scientific awards such as the First Prize from the China Gold Association and the Second Prize from the China Nonferrous Metals Industry for her impactful contributions to green and safe mining.

🔬Research Focus:

Ai-Ai Wang’s research is rooted in advanced techniques of tailings sand cementation, intelligent filling systems, and digital mining. She explores the structural stability of backfills, application of nanomaterials, and CT-based 3D modeling of internal structures. Her work blends civil engineering, environmental safety, and digital innovation, aiming to enhance sustainability and efficiency in modern mining. She also contributes to cutting-edge software systems and patented technologies for mining design and operation support.

📝Conclusion:

Ai-Ai Wang stands out as a promising engineer and researcher whose academic achievements, professional dedication, and innovative research in intelligent mining set a high standard for future civil and mining engineers. Her trajectory reflects not just technical mastery but a deep commitment to sustainable and smart engineering solutions in the mining industry.

📚Top Publications with Details

Effect of height to diameter ratio on dynamic characteristics of cemented tailings backfills with fiber reinforcement through impact loading – Construction and Building Materials, 2022
Cited by: 26 articles
Influence of types and contents of nano cellulose materials as reinforcement on stability performance of cementitious tailings backfill – Construction and Building Materials, 2022
Cited by: 20 articles
Quantitative analysis of pore characteristics of nanocellulose reinforced cementitious tailings fills using 3D reconstruction of CT images – Journal of Materials Research and Technology, 2023
Cited by: 12 articles

 

MANIKANDAN S | Mathematics | Best Researcher Award

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MANIKANDAN S | Mathematics | Best Researcher Award

Research Scholar, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, India

Mr. Manikandan S is an aspiring academic and researcher in the field of applied mathematics, currently pursuing his Ph.D. in Fractional Mathematical Modelling at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai. With a passion for mathematical research and a keen interest in fractional calculus, he has made significant contributions to the mathematical modelling of real-world problems such as epidemic disease transmission. His expertise spans across various tools like MATLAB, SCILAB, R-Language, SPSS, and LaTeX, coupled with proficiency in programming languages like C and C++. He is a dedicated researcher recognized for his presentations at international conferences and has publications in high-impact Q1 journals indexed in Scopus and Web of Science.

Publication Profile

📘 Education Background

Mr. Manikandan completed his B.Sc. in Mathematics from Government Arts and Science College, Veppanthattai (Bharathidasan University) in 2018 with 58%, followed by an M.Sc. in Mathematics at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, graduating with a CGPA of 8.2 in 2022. He is presently pursuing his Ph.D. in Fractional Mathematical Modelling at the same institute since January 2023. His academic journey reflects his progressive dedication to research in applied mathematics and control theory.

💼 Professional Experience

While currently focused on doctoral research, Mr. Manikandan has actively engaged in professional development through numerous workshops, FDPs, and conference presentations. He has attended national and international-level events including FDPs on numerical techniques and Python for engineering applications, as well as workshops on research methodology and applied mathematical research hosted by prestigious institutions like VIT and SRM Institute of Science and Technology.

🏅 Awards and Honors

Mr. Manikandan is a Life Member of the International Association of Engineers (IAENG) and was honored with the Best Paper Presentation Award for his paper on Zika virus control using fractional-order models at the 7th International Conference on Mathematical Modelling, Applied Analysis, and Computation (ICMMAAC-24). His commitment to knowledge enhancement is evident from his completion of multiple international MOOCs from platforms like Coursera and CISCO in areas ranging from Python to Cybersecurity and Differential Equations.

🔬 Research Focus

His core research revolves around Differential Equations, Control Theory, and advanced topics like Fractal-Fractional Mathematical Modelling and Stochastic Analysis. He is especially focused on modeling infectious diseases using fractional differential systems like Atangana–Baleanu and Caputo–Fabrizio operators. His recent patent titled “A Statistical Method for Parkinson’s Disease Prognosis Using Clinical Data” also highlights his interdisciplinary innovation in mathematical applications for healthcare.

✅ Conclusion

Mr. Manikandan S is a motivated and evolving researcher whose work integrates deep mathematical theory with impactful real-world applications. With growing recognition in the academic community, a strong publication record, and an interdisciplinary approach, he continues to pave the way in the domain of fractional mathematical modelling and epidemiological research.

📚 Top Publications 

Fractal-fractional mathematical modeling of monkeypox disease and analysis of its Ulam–Hyers stability
Boundary Value Problems, 2025 (Q1, SCI – WoS – Scopus)
 Cited by: 3 articles

A Fractal-Fractional Mathematical Model for COVID-19 and Tuberculosis using Atangana–Baleanu Derivative
Mathematical and Computer Modelling of Dynamical Systems, 30(1), 2024 (Q1, SCI – WoS – Scopus)
Cited by: 6 articles

Mathematical Modelling of HIV/AIDS Treatment using Caputo–Fabrizio Fractional Differential Systems
Qualitative Theory of Dynamical Systems, 23(149), 2024 (Springer, Q1, SCI – WoS)
Cited by: 4 articles

Optimal Control Strategies for Dengue Fever Transmission Using Atangana-Baleanu Fractional Order Models
Indian Journal of Natural Sciences, 15(87), 2024 (WoS Indexed)
Cited by: 2 articles

Symmetry Analyses of Epidemiological Model for Monkeypox Virus with Atangana–Baleanu Fractional Derivative
Symmetry, 2023 (SCI Journal)
Cited by: 5 articles

Mr. Xingfu CAI | data mining | Best Researcher Award

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Mr. Xingfu CAI | data mining | Best Researcher Award

professor, xi’an institute and high-tech, China

Dr. Cai Xingfu is a dedicated Chinese nuclear science researcher actively contributing to advanced nuclear safety and radiation measurement technologies. With a profound commitment to applied physics and nuclear engineering, Dr. Cai has significantly impacted the development of neutron correlation-based nuclide identification and high-X environment radiation simulations. He plays key roles in national-level scientific research projects and is recognized for both his academic achievements and technological innovations in nuclear safety.

Publication Profile

Scopus

🎓 Education Background:

Dr. Cai Xingfu holds advanced degrees in nuclear science and engineering, underpinning his expertise in radiation measurement, nuclear safety, and tritium leakage studies. His academic training provided the foundation for developing multiple high-impact software systems and contributing to national defense-related research.

💼 Professional Experience:

Dr. Cai currently serves as a principal or co-investigator in several critical projects. These include his involvement in the National Natural Science Foundation of China (Project No. 12475307), where he contributes to intelligent nuclide identification using neutron angular correlation techniques (2025–2028). Additionally, he leads projects funded by the J Science and Technology Committee and Headquarters involving tritium measurement in high-radiation environments and X-emergency training technologies, respectively. His practical experience spans experimental, computational, and real-world nuclear safety systems.

🏆 Awards and Honors:

Dr. Cai was awarded the Second Prize in Natural Science by the Shaanxi Provincial Department of Education in 2022 for his contributions to α aerosol spectrum analysis in high-background environments. He also holds numerous software copyrights and a national patent, reflecting his contribution to radiation measurement and simulation software systems.

🔬 Research Focus:

His core research interests revolve around nuclear radiation field simulations, tritium behavior in storage and leak scenarios, emergency response optimization, and AI-aided nuclide identification. He specializes in the development of software for simulation and radiation detection in complex environments, significantly advancing radiation protection and safety technology.

🔚 Conclusion:

Driven by a mission to innovate in nuclear safety, Dr. Cai Xingfu continues to lead the field with state-of-the-art contributions in measurement technologies and software systems. His work not only improves scientific understanding but also enhances practical applications in nuclear facility safety and emergency preparedness.

📚 Top Publications:

Nuclear Radiation Digital Measurement Technology – Huo Yonggang, Xu Peng, Li Sufen, Cai Xingfu, National Defense Industry Press, 2021. (Academic Monograph)
Citation: Referenced widely in nuclear safety and detector calibration research (Cited by: 14+ articles)

Analysis on the influencing factors of radioactive tritium leakage and diffusion from an indoor high-pressure storage vessel – Li, Cai, Xiao, Huo, Xu, Li, Cao; Nuclear Science and Techniques, 2022, 33(12).
Author Note: Sole Corresponding Author
Cited by: 20+ articles

A modified A* algorithm for path planning in the radioactive environment of nuclear facilities – Zhang, Cai, Li et al.; Annals of Nuclear Energy, 2025, 214, 111233.
Author Note: Sole Corresponding Author
Cited by: Expected to impact autonomous robotics and nuclear AI (Early Access)

Nuclear safety characterisation of PBX explosives under low-velocity impact conditions – Guo, Cai, Huo, Wang; Annals of Nuclear Energy, 2025, 211.
Author Note: Sole Corresponding Author
Cited by: 12+ articles

Study on emergency ventilation optimization method for tritium leakage accident of high-pressure storage vessel – Cai Xingfu, Li, Huo, Xu, et al.; AIP Advances, 2022, 12(6): 65302.
Author Note: Sole First Author & Sole Corresponding Author
Cited by: 18+ articles

Ms. Darasimi Olorunlowu | Neuroscience | Best Researcher Award

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Ms. Darasimi Olorunlowu | Neuroscience | Best Researcher Award

Genomac Institute Inc. Nigeria

Darasimi Racheal Olorunlowu is a passionate and highly motivated graduate of Anatomy with a keen interest in Neuroscience, particularly neurodegeneration and brain health 🧠. With a solid academic background and growing research portfolio, she is committed to making impactful contributions to the scientific understanding of neurogenomics and neurodegenerative diseases. Her collaborative spirit, scientific curiosity, and strong analytical skills make her a standout emerging researcher in the Nigerian neuroscience community 🇳🇬.

Publication Profile

ORCID

🎓 Educational Background

Darasimi earned her Bachelor of Technology (B.Tech) in Anatomy from Ladoke Akintola University of Technology (LAUTECH), Nigeria, where she graduated with a commendable CGPA of 4.17/5.00 (3.63/4.00 iWES equivalent) 📚. Prior to this, she completed her secondary education at Royalpath College, Lagos, where she laid a strong foundation in biology, chemistry, and physics—subjects that would later shape her interest in brain research.

🧪 Professional Experience

She is currently a Research Intern at Genomac Institute Inc. (2025–present), where she analyzes large-scale genomic datasets and develops bioinformatics pipelines using tools like R, SPSS, and Geneious. She served as an Academic Tutor during her National Youth Service (2023–2024), supporting biology and neuroscience education at the secondary level. Her earlier role as a Research Assistant with the LAUTECH Neuroscience Group (2023–2024) involved histological analysis, literature reviews, data visualization, and manuscript preparation. Additionally, she completed internships in histopathology and conducted an undergraduate research project focused on drug-induced liver toxicity 🧫🔍.

🏆 Awards and Honors

Darasimi has been recognized by the LAUTECH Neuroscience Group and the International Brain Research Organization (IBRO) for her outstanding contributions to research, capacity building, and community development in neuroscience 🌍🏅. She has also obtained multiple certifications from institutions like the University of Michigan, HRH-CERID, and Gen’Omics Research Hub, which further solidify her training in neuroanatomy, genomics, and molecular diagnostics.

🧠 Research Focus

Her research focus centers around neurogenomics, neurodegenerative diseases, and molecular neuroscience 🧬. She has contributed to studies on Parkinson’s disease, mental stress pathways, and genetic markers associated with neurodegeneration. Her expertise in histology, molecular biology, and statistical data analysis underpins her multidisciplinary approach to understanding brain function and pathology. She is also actively engaged in bioinformatics-driven investigations and in silico modeling to identify hub genes and regulatory networks related to neurological disorders.

🔚 Conclusion

With an impressive early-career research track, multiple co-authored publications, and a strong commitment to advancing brain science, Darasimi Racheal Olorunlowu stands out as a promising neuroscience researcher. Her dedication to learning, collaborative leadership, and skillful scientific communication make her a valuable contributor to the global neuroscience community 🌐📖.

📚 Top Publications 

Neurogenomics Contributions to Neurodegenerative Disease
Adeleye, O. O., Olorunlowu, D. R., et al. (2024)
Nepal Journal of Neuroscience
DOI: 10.3126/njn.v21i1.58673
Cited by: 5 articles

Unraveling the Complex Tapestry of Mental Stress: A Multifaceted Exploration of Pathways, Consequences, and Remedies
Adeleye, O. O., Akindokun, S., Olorunlowu, D. R., et al. (2024)
European Journal of Neuroscience
DOI: 10.22541/au.172115134.42168367/v1
Cited by: 3 articles

Molecular, Genetic and Population Approaches of Brain Health: The African Perspective
Adeleye, O. O., Olorunlowu, D. R., et al. (2023)
Neuroscience Journal of Nigeria (Accepted)
Cited by: Upcoming publications

The Socioeconomic Impact of Lassa Fever in Nigeria
Akindokun, S.S., Adeleye, O.O. & Olorunlowu, D.R. (2024)
Discover Public Health, 21(133)
DOI: 10.1186/s12982-024-00265-z
Cited by: 4 articles

In Silico Analysis For Identification Of Hub Genes And Their Regulatory Network In Parkinson’s Disease Putamen
Akanbi, S. T., Yusuf, J. A., Olorunlowu, D.R., et al. (2025)
Egyptian Journal of Medical Human Genetics, 26(9)
DOI: 10.1186/s43042-025-00643-5
Cited by: 2 articles

Molecular Mechanism Underlying Stress Response And Adaptation
Yusuf, J. A., Akanbi, S. T., Olorunlowu, D. R., et al. (2025)
Progress in Brain Research, Elsevier
 DOI: 10.1016/bs.pbr.2025.01.005
Cited by: 6 articles

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

Posted on by Computer Scientists Awards

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)