Month: November 2024

Education Background🎓

Dr. Hassan Mohamed Hassan holds a Ph.D. in Inorganic Chemistry from Suez Canal University, Ismailia, Egypt, which he completed in August 2008. He also earned an M.Sc. in Physical Chemistry from the same university in 1998, and a B.Sc. in Chemistry in 1987, where he graduated with distinction. His academic background is complemented by specialized training in method development and instrumental analysis, particularly in areas related to environmental chemistry, food, and pharmaceutical testing.

Professional Experience🌱

Dr. Hassan is currently a Laboratory Research Specialist at the College of Agriculture and Veterinary Medicine at UAE University (2012-present). He is responsible for performing advanced Analytical chemistry assays, developing new methodologies, and mentoring graduate students. His laboratory work primarily focuses on the analysis of food, animal feed, and environmental contaminants using a wide range of techniques, including UHPLC, GC-MS, FTIR, and NIR spectroscopy. He also plays a key role in hazardous testing and supports external clients with specialized research services.

Before his current position, Dr. Hassan served as a Laboratory Research Specialist in the Central Laboratories Unit at UAE University from 2002 to 2011. During this period, he contributed to the analysis of various organic components and pollutants in water, soil, and food samples, using HPLC, GC-MS/FID, and other chromatography-based techniques. Dr. Hassan’s experience extends to working in the pharmaceutical industry for Medical Union Pharmaceutical Company in Egypt, where he was involved in quality control, technology transfer, and method development from 1991 to 2002.

Research Interest🔬

Dr. Hassan’s research interests are primarily in the fields of biochemistry, analytical chemistry, and bioactive materials. He has a strong focus on separation and characterization of bioactive compounds from plant and animal sources, particularly from date palm leaves and camel milk. His research also explores innovative methods for the purification of biomolecules and the development of natural food colorants. Additionally, Dr. Hassan has worked extensively on the analysis of mycotoxins in food and animal feed, particularly aflatoxins and ergot alkaloids, and has contributed significantly to the development of environmental testing methods for water, soil, and sediment samples.

Author Metrics

US Patents: 2 patents granted for innovative methods in purification of lactoferrin and anthocyanin synthesis from date palm leaves.
Innovation Awards:
- 2021-2022 Chancellor’s Innovation Award for a novel UPLC technique for carbohydrate analysis.
- 2018-2019 Chancellor’s Innovation Award for a natural food colorant from date palm leaves.
- 2016-2017 Chancellor’s Innovation Award for an economic method of lactoferrin separation from camel milk.
Publications and Research: Active contributor to scientific literature in the fields of food chemistry, bioactive materials, and environmental analysis.
Research Collaborations: Co-investigator in projects such as Camel Gelatin as an alternative to pork gelatin and sausage production from camel meat.

Publications Top Notes 📄

Synergistic Combination of Natural Deep Eutectic Solvents and Green Extraction Techniques for the Valorization of Date Palm Leaves: Optimization of the Solvent-Biomass Interaction
- Published in: Microchemical Journal
- Year: 2023
- DOI: 10.1016/j.microc.2023.109503
- EID: 2-s2.0-85174737939
- ISSN: 0026-265X
- Abstract: The study explores the combination of natural deep eutectic solvents (NADES) and green extraction techniques to optimize the valorization of date palm leaves. The work investigates the interaction between the solvent and biomass to extract bioactive compounds efficiently, focusing on improving sustainability in agricultural waste management and bioresource utilization. The optimization process is designed to enhance extraction yields, offering a more eco-friendly alternative to conventional methods.
Use of 4-D Proteomics to Differentiate Between Bovine and Camel Lactoferrin
- Published in: Food Chemistry
- Year: 2023
- DOI: 10.1016/j.foodchem.2023.136682
- EID: 2-s2.0-85162972344
- ISSN: 0308-8146 | 1873-7072
- Abstract: This research utilizes 4-D proteomics to differentiate between bovine and camel lactoferrin. The study employs advanced proteomic techniques to examine the structural and functional differences in lactoferrin derived from two distinct mammalian sources. The findings provide valuable insights for food safety, nutraceutical applications, and the dairy industry, highlighting the potential for camel lactoferrin as a unique bioactive protein.
Exploring the Impact of Various Cooking Techniques on the Physicochemical and Quality Characteristics of Camel Meat Products
- Published in: Animal Bioscience
- Year: 2023 (November)
- DOI: 10.5713/ab.22.0238
- Abstract: This study examines how different cooking techniques influence the physicochemical properties and overall quality of camel meat products. By comparing various cooking methods, including grilling, boiling, and roasting, the research assesses changes in meat texture, nutritional content, and flavor. The findings contribute to improving camel meat processing techniques for enhanced quality in the food industry, especially in regions where camel meat is a staple.
Characterization, Bioactivities, and Rheological Properties of Exopolysaccharide Produced by Novel Probiotic Lactobacillus plantarum C70 Isolated from Camel Milk
- Published in: International Journal of Biological Macromolecules
- Year: 2020
- DOI: 10.1016/j.ijbiomac.2019.09.171
- EID: 2-s2.0-85075834341
- ISSN: 0141-8130 | 1879-0003
- Abstract: The study investigates the characterization, bioactivities, and rheological properties of an exopolysaccharide produced by the novel probiotic Lactobacillus plantarum C70, isolated from camel milk. This research highlights the potential of camel milk as a source of functional probiotics with health benefits, particularly in improving gut health. The study also examines the bioactivity and rheological properties of the exopolysaccharide, showing its potential in food and pharmaceutical applications.

Conclusion

Dr. Hassan Mohamed Hassan is a highly deserving candidate for the Best Researcher Award. His remarkable career, consisting of pioneering research in analytical chemistry, bioactive materials, and environmental analysis, is complemented by practical innovations and scientific patents. His research, particularly in the valorization of date palm leaves, camel milk, and food safety, stands as a testament to his dedication to improving agricultural and food industries sustainably.

Dr. Hassan’s innovative approach, long-standing research contributions, and ability to apply cutting-edge techniques in his work make him a leader in his field. While there are areas for improvement, especially in expanding interdisciplinary outreach and collaboration, his current research trajectory and recognition in both academia and industry place him in a strong position for the Best Researcher Award.

Haoran Yang | Graph Clustering | Outstanding Research Achievement Award

Published on 15/11/202415/11/2024 by Network Science

Dr. Haoran Yang | Graph Clustering | Outstanding Research Achievement Award

PhD , Tongji University, China📖

Haoran Yang is a PhD student in Computer Science at Tongji University, specializing in advanced graph neural networks and multimodal learning. His research since 2020 spans critical topics in artificial intelligence, including graph mining, few-shot learning, and self-supervised learning. His work explores innovative applications of AI in science (AI4Science) and complex graph analysis, advancing understanding and capabilities within these fields.

Profile

Education Background🎓

Haoran Yang is currently a PhD student in Computer Science at Tongji University, where he has been pursuing his research since 2020. His academic journey focuses on advanced topics in graph neural networks, few-shot learning, and multimodal learning, with a strong interest in AI applications for scientific research (AI4Science). Prior to his PhD studies, Haoran completed his undergraduate education in Computer Science, laying the foundation for his deep exploration of AI and machine learning techniques.

Professional Experience🌱

Haoran Yang has gained valuable professional experience as a reviewer for prominent academic journals and conferences, including IEEE Transactions on Knowledge and Data Engineering (TKDE) and the International Conference on Learning Representations (ICLR). His role as a peer reviewer allows him to contribute to the advancement of knowledge in the fields of graph neural networks, few-shot learning, and multimodal AI, ensuring high-quality research is disseminated within the academic community. Additionally, his research experience, focused on graph mining and AI applications in science (AI4Science), has further shaped his expertise in cutting-edge AI methodologies.

Research Interest🔬

Graph Neural Networks (GNNs): Focused on developing and optimizing GNN architectures, including deep clustering optimization and graph few-shot learning methods.
Multimodal Learning: Exploring AI4Science and the integration of multiple data sources for enhanced learning outcomes.
Graph Mining and Self-Supervised Learning: Aiming to refine the application of self-supervised techniques in graph learning to improve model adaptability and performance in varied data environments.

Author Metrics

As a rising researcher, Haoran Yang has contributed significantly to the field of graph neural networks and multimodal AI, with publications and reviews in prestigious venues. His work is gaining recognition, particularly for its innovative approaches to clustering and spectral GNN analysis.

Publications Top Notes 📄

DCOM-GNN: A Deep Clustering Optimization Method for Graph Neural Networks
- Authors: Haoran Yang, Jiao Wang, Rui Duan, Chao Yan
- Published in: Knowledge-Based Systems, Volume 279, Article 110961, 2023
- Abstract:
  This paper presents a novel method, DCOM-GNN, designed to optimize deep clustering in graph neural networks (GNNs). The approach targets improving the clustering performance in graph-based learning by incorporating a clustering loss into the GNN framework. The authors focus on enhancing the quality of learned representations while minimizing intra-cluster distances and maximizing inter-cluster distances, leading to more efficient and accurate graph clustering. The method demonstrates its effectiveness through various experimental results on benchmark datasets, showing improvements over existing clustering techniques in GNNs.
- Key Contributions:
  - Introduction of a deep clustering optimization method specifically for GNNs.
  - Formulation of a clustering loss that balances intra-cluster and inter-cluster distances.
  - Performance evaluation on multiple graph datasets showing the potential of DCOM-GNN in real-world applications.
Unifying Homophily and Heterophily for Spectral Graph Neural Networks via Triple Filter Ensembles
- Authors: Haoran Yang, et al.
- Conference: NeurIPS 2024 (Accepted)
- Abstract:
  This paper proposes a unified framework to address the challenge of integrating homophily (similarity between neighboring nodes) and heterophily (dissimilarity between neighboring nodes) in spectral graph neural networks (SGNNs). The authors introduce Triple Filter Ensembles, a novel technique that combines multiple filter types to account for both homophilic and heterophilic structures in a graph. The method allows SGNNs to adaptively learn from graphs with varying node relationships, improving model robustness and generalization across diverse graph datasets.
- Key Contributions:
  - The development of Triple Filter Ensembles to unify homophily and heterophily in SGNNs.
  - Enhanced model performance on graph datasets exhibiting mixed node relationships.
  - Novel insights into the challenges and solutions for spectral-based GNNs when applied to graphs with both similar and dissimilar neighboring nodes.

Conclusion

Haoran Yang’s research contributions to graph neural networks, particularly in deep clustering optimization and spectral GNNs, represent significant advancements in the field of AI. His innovative work has the potential to transform both theoretical and applied aspects of graph-based learning and multimodal AI. His future directions, focused on AI applications in science and the integration of self-supervised learning and few-shot learning into graph networks, promise to maintain his trajectory as a leading researcher. With continued academic success and the application of his work in real-world contexts, Haoran Yang is a deserving candidate for the Outstanding Research Achievement Award.

Masoumeh Jafari | Network Security | Best Researcher Award

Published on 15/11/202415/11/2024 by Network Science

Ms. Masoumeh Jafari | Network Security | Best Researcher Award

Visiting student, NUS University, Singapore📖

Masoumeh Jafari is a Ph.D. candidate in Software Engineering at Yazd University, currently advancing her research as a visiting scholar at the National University of Singapore. With a strong academic foundation and over a decade of experience, she has developed expertise in blockchain, cyber security, and artificial intelligence, focusing on practical applications for secure data exchange and decentralized systems. Masoumeh’s work includes contributions to peer-reviewed journals, conference presentations, and collaborations on cutting-edge projects in incident response and threat prevention. Recognized for her innovative approach and commitment to interdisciplinary research, she is both an accomplished academic and a dedicated educator in the fields of software engineering and information technology.

Profile

Education Background🎓

Masoumeh Jafari is a dedicated scholar currently pursuing her Ph.D. in Software Engineering at Yazd University, Iran, where she ranked 41st in the national entrance exam. Her research excellence has led her to a prestigious one-year visiting scholar position at the National University of Singapore (NUS), beginning in July 2024. She holds a Master’s degree in Software Engineering from Payame Noor University in Tehran, completed in 2014, and a Bachelor’s degree in Computer Science from Shahid Bahonar University of Kerman, where she graduated in the top 10% of her class. Her solid academic foundation in computer science and engineering has set the stage for her ongoing contributions to advanced research in blockchain, cybersecurity, and AI.

Professional Experience🌱

Masoumeh Jafari is an experienced researcher and lecturer in software engineering, actively involved in research and project development related to blockchain, cyber security, machine learning, and IoT. Since 2020, she has served as a research assistant to Dr. Adibnia at Yazd University and collaborated with the Academic and Policy Affairs (APA) Department at Yazd University on initiatives like incident response and threat prevention. Additionally, she has served as a reviewer for prestigious journals, including Information Fusion, Information Sciences, and Soft Computing. She has also judged conference submissions across diverse areas such as IoT, sustainable development, and computer science applications.

Masoumeh’s career spans over 14 years in academia and industry, including roles in game design, blockchain-based projects, and robotics education. Her technical skills encompass languages like Python, Solidity, and C++, with expertise in simulation tools (NS2, CloudSim), big data platforms (Hadoop, Spark), and blockchain environments (Ethereum, Remix).

Research Focus🔬

Masoumeh’s research interests lie in the fields of blockchain technology, cybersecurity, artificial intelligence (AI), and Internet of Things (IoT). She is particularly focused on the practical applications of blockchain in security, healthcare, and smart contracts, exploring new frameworks and solutions for secure, decentralized networks. Her recent projects include blockchain for secure data sharing in IoT systems and deep learning for data analytics.

Author Metrics

Masoumeh Jafari has published extensively, contributing papers in reputable journals such as IEEE and regularly participating as a peer reviewer for scientific publications. Her works cover a wide range of topics, from cybersecurity frameworks and blockchain advancements to machine learning applications in data mining. Her active engagement in interdisciplinary research has earned her recognition within the academic community, establishing her as a forward-thinking scholar and a contributor to software engineering and information systems.

Selected Certifications and Recognitions

Blockchain & Smart Contract Development – Academy of CoinIran
Malware Analysis – Maher Center, Iran Information Technology Organization
Machine Learning and Image Processing (Python) – Yazd University
Multiple Academic Awards (Top 3 rankings, Yazd University, 2021-2024)

Publications Top Notes 📄

Internet of Things in Eye Diseases: Introducing a New Smart Eyeglasses Designed for Probable Dangerous Pressure Changes in Human Eyes
Authors: G. Prouski, M. Jafari, H. Zarrabi
Conference: IEEE International Conference on Computer and Applications (ICCA)
Year: 2017
Pages: 364-368
Summary: This paper explores the development of innovative smart eyeglasses embedded with IoT sensors to monitor intraocular pressure, aiming to detect and alert users to potentially dangerous pressure fluctuations that could lead to eye diseases such as glaucoma. This solution provides a real-time monitoring system to support early intervention and reduce risks associated with eye pressure changes.
Citations: 13
Considerations to Spoken Language Recognition for Text-to-Speech Applications
Authors: M.S. Rafieee, S. Jafari, H.S. Ahmadi, M. Jafari
Conference: 2011 UKSim 13th International Conference on Computer Modelling and Simulation
Year: 2011
Summary: This paper discusses the challenges and considerations in spoken language recognition systems used in text-to-speech applications. It evaluates the factors influencing accuracy and proposes methodologies for improving the reliability of language recognition in automated systems.
Citations: 13
Internet of Things in Eye Diseases Using Smart Glasses
Author: M. Jafari
Journal: International Journal of Engineering Education (IJEE)
Year: 2017
Pages: 1034-1042
Summary: Building on IoT applications in healthcare, this paper presents the design and functionality of smart glasses aimed at diagnosing and managing eye diseases. The paper elaborates on sensor technology, data transmission, and potential benefits for patients with chronic eye conditions, contributing to personalized medical solutions and preventive care.
Citations: 2
A Novel Method for Extracting Blood Vessels in Digital Retinal Images
Author: M. Jafari
Journal: Soft Computing Journal
Volume: 10, Issue 1
Year: 2021
Pages: 110-121
Summary: This paper introduces a new algorithm for extracting blood vessels in retinal images, which is a crucial step for diagnosing various eye diseases. Utilizing soft computing techniques, the method enhances image segmentation and detection accuracy in digital retinal imaging, improving diagnosis and facilitating automated eye health monitoring.
Citations: 1 (recently cited)
Isolation of Vessels in Retinal Color Images
Author: M. Jafari
Journal: Soft Computing Journal
Year: 2022
Summary: This publication presents advanced techniques for isolating blood vessels in retinal color images, essential for retinal disease detection and analysis. The study leverages soft computing and image processing methods to improve the clarity and precision of vessel isolation in complex retinal imaging scenarios.

Conclusion

Masoumeh Jafari demonstrates an exceptional blend of technical expertise, interdisciplinary research acumen, and a commitment to impactful solutions in cybersecurity and IoT applications. Her research is highly innovative, grounded in solid technical skills, and driven by a commitment to advancing secure, decentralized systems and healthcare technology. Recognizing her achievements with the Research for Best Researcher Award would honor not only her scholarly contributions but also her vision for transformative technology in both digital and healthcare domains. Further development in cross-disciplinary applications and communication could enhance her impact, making her an even stronger candidate for future awards. Overall, her work aligns exceptionally well with the values of the Research for Best Researcher Award, marking her as a deserving candidate.

Surong Yan | Graph-based recommendation systems | Best Researcher Award

Published on 14/11/202414/11/2024 by Network Science

Ms. Surong Yan | Graph-based recommendation systems | Best Researcher Award

Professor, Zhejiang University of Finance and Economics, China📖

Dr. Surong Yan is a professor in the Department of Computer Science and Technology at Zhejiang University of Finance and Economics. With a research focus on data mining, knowledge discovery, artificial intelligence, and recommendation systems, her work explores innovative solutions for online activity recognition, human-computer interaction, and intelligent services. Dr. Yan has authored over 20 publications in leading journals such as IEEE TKDE and ACM TOIS, and has received multiple grants, including those from the National Science Foundation. She has also served as a reviewer for top journals and conferences in her field.

Profile

Education and Experience🎓

Dr. Surong Yan holds a Ph.D. in Computer Science and Technology from Zhejiang University, which she completed in 2014. Prior to this, she earned a Master of Arts in Computer Science and Technology as a visiting scholar at Zhejiang University in 2005. Dr. Yan also holds a Bachelor of Arts in Information Management and Information Systems from the Zhejiang University of Finance and Economics, where she graduated in 2002. Her academic journey has provided a solid foundation in computer science and technology, which she has built upon through her research and professional experience in the fields of data mining, artificial intelligence, and recommendation systems.

Professional Development🌱

Dr. Yan has been a dedicated member of the faculty at Zhejiang University of Finance and Economics since 2005, where she progressed from Lecturer to Associate Professor and ultimately to Professor. In addition to her teaching and research contributions, she spent a year as a visiting scholar at the University of California, Irvine, in 2015-2016, where she furthered her work in data mining and human activity recognition. Her contributions as an academic include serving as a reviewer for prestigious journals such as IEEE Transactions on Knowledge and Data Engineering (TKDE), Knowledge-Based Systems (KBS), Expert Systems with Applications (ESWA), and as a program committee (PC) member for international conferences.

Research Focus🔬

Dr. Surong Yan’s research focuses on data mining, knowledge discovery, artificial intelligence, and recommendation systems. Her work addresses real-world challenges in online activity recognition, human interaction, and recommendation systems in the context of IoT and social computing. Her innovative methodologies leverage edge computing, graph neural networks, and reinforcement learning to enhance intelligent services and human-computer interaction.

Author Metrics

Dr. Surong Yan has authored over 20 publications in prestigious journals and conferences, including IEEE Transactions on Knowledge and Data Engineering (TKDE), ACM Transactions on Information Systems (TOIS), Knowledge-Based Systems (KBS), and Expert Systems with Applications (ESWA). Her research has garnered significant attention, with multiple high-impact articles in the fields of data mining, artificial intelligence, and recommendation systems. Additionally, she has served as a reviewer for several leading journals and a program committee member for international conferences, further solidifying her influence in the academic community.

Grants & Awards

National Science Foundation (NSF) Grant, 2019: For “Research on adaptive recommendation and optimization of intelligent services based on edge computing and swarm intelligence sensing.”
National Science Foundation (NSF) Grant, 2015: For “Situation-aware personalized recommendation mechanism in a converged network environment.”
Natural Science Foundation of Zhejiang Province Grant, 2014: For “Personalized recommendation mechanism of multi-strategy integration in a social computing environment.”

Publications Top Notes 📄

Feature Interactive Graph Neural Network for KG-based Recommendation
- Authors: Yan, S., Li, C., Wang, H., Lin, B., Yuan, Y.
- Published in: Expert Systems with Applications
- Year: 2024
- Volume: 237
- Article ID: 121411
- Abstract: This study proposes a novel feature interactive graph neural network (GIN) model for knowledge graph (KG)-based recommendation systems. It explores feature interactions between different types of data (e.g., user, item, and context) in a knowledge graph to enhance recommendation accuracy. The model uses graph neural networks to process and learn from the structured knowledge embedded in the graph, which helps to improve the personalized recommendation systems.
- Citations: 3
Cross-view Temporal Graph Contrastive Learning for Session-based Recommendation
- Authors: Wang, H., Yan, S., Wu, C., Han, L., Zhou, L.
- Published in: Knowledge-Based Systems
- Year: 2023
- Volume: 264
- Article ID: 110304
- Abstract: This paper introduces a cross-view temporal graph contrastive learning method for session-based recommendation systems. The authors address the challenge of recommending items in a session-based environment, where the user preferences change over time. The proposed model utilizes temporal graph-based contrastive learning to capture these changes and enhance the accuracy of session-based recommendation engines.
- Citations: 10
LkeRec: Toward Lightweight End-To-End Joint Representation Learning for Building Accurate and Effective Recommendation
- Authors: Yan, S., Lin, K.-J., Zheng, X., Wang, H.
- Published in: ACM Transactions on Information Systems
- Year: 2022
- Volume: 40(3)
- Article ID: 54
- Abstract: LkeRec is an end-to-end lightweight joint representation learning approach aimed at improving the accuracy and efficiency of recommendation systems. It combines feature learning and recommendation generation into a single framework to simplify the process and reduce computation costs, while ensuring that the quality of recommendations remains high.
- Citations: 5
A Hybrid Model with Novel Feature Selection Method and Enhanced Voting Method for Credit Scoring
- Authors: Yao, J., Wang, Z., Wang, L., Jiang, H., Yan, S.
- Published in: Journal of Intelligent and Fuzzy Systems
- Year: 2022
- Volume: 42(3)
- Pages: 2565–2579
- Abstract: The paper presents a hybrid model for credit scoring, which integrates a novel feature selection method with an enhanced voting mechanism to improve prediction accuracy. The hybrid model combines different machine learning techniques to identify the most relevant features for credit scoring and make better predictions, particularly in the context of financial applications.
- Citations: 4
Attention-Aware Metapath-Based Network Embedding for HIN-Based Recommendation
- Authors: Yan, S., Wang, H., Li, Y., Zheng, Y., Han, L.
- Published in: Expert Systems with Applications
- Year: 2021
- Volume: 174
- Article ID: 114601
- Abstract: This paper proposes an attention-aware metapath-based network embedding method for heterogeneous information networks (HINs). The proposed method focuses on the importance of different metapaths and incorporates attention mechanisms to improve the recommendation quality in HIN-based environments. The approach is particularly useful for scenarios where the relationships between entities are complex and diverse.
- Citations: 30

Conclusion

Dr. Surong Yan is an exemplary candidate for the Best Researcher Award due to her significant contributions to the fields of data mining, knowledge discovery, and artificial intelligence. Her innovative methodologies, combined with her successful academic and research career, position her as a leader in her field. By expanding her research’s industrial and sectoral reach, Dr. Yan could amplify her already impressive impact. Her achievements, dedication, and promise for future advancements make her a deserving nominee for this prestigious recognition.

Abdulnaser Fakhrou | educational psychology applications | Excellence in Research

Published on 14/11/202414/11/2024 by Network Science

Assoc. Prof. Dr. Abdulnaser Fakhrou | Educational Psychology Applications | Excellence in Research

Abdulnaser Fakhrou, college of Education, Qatar University, Qatar📖

Dr. Abdulnaser Abdulraheem Fakhrou is an Associate Professor in the Department of Psychological Science at the College of Education, Qatar University. With a Ph.D. in Educational Psychology from the University of Birmingham, UK, Dr. Fakhrou has dedicated his career to advancing educational and psychological research, specializing in areas such as special education, educational psychology, and gifted education. His teaching and research work have spanned several institutions, including prior roles at Umm Al-Qura University in Saudi Arabia and the College of Basic Education in Kuwait. Dr. Fakhrou’s research interests include emotional intelligence, academic self-efficacy, and the psychological aspects of education technology. He has published widely in international journals, contributing to the fields of educational psychology and cyberpsychology, and actively engages in initiatives to support mental health and inclusive education practices. 🧬

Profile

Education and Experience🎓

Dr. Abdulnaser Abdulraheem Fakhrou has an extensive educational foundation in psychology and special education. He earned a Ph.D. in Educational Psychology from the University of Birmingham, UK, in 2005, where he also completed a Higher Diploma in Scientific Research in 2003. His specialization in gifted education was furthered with a diploma from the University of Connecticut, USA, in 2000. Additionally, he holds a Master’s in Special Education from the Arabian Gulf University, Bahrain (1998), and several higher diplomas in social sciences and special education, including a Bachelor of Arts from Kuwait University. This robust education underpins his expertise in educational psychology.

Professional Development🌱

Dr. Fakhrou is currently an Associate Professor in the Department of Psychological Science at Qatar University, a role he has held since 2021. Prior to this, he served as an Assistant Professor in special education at Umm Al-Qura University in Saudi Arabia and at Kuwait’s College of Basic Education. His career is marked by a focus on teaching and developing courses in educational psychology, special education, and inclusive practices. Dr. Fakhrou’s experience spans over two decades in academia, where he has contributed to curriculum development, student guidance, and the advancement of educational methods tailored to diverse learning needs.💼

Research Focus🔬

Dr. Fakhrou’s research interests are rooted in educational psychology and special education, with a particular focus on supporting gifted students and those with special needs. His work encompasses areas such as emotional intelligence, academic self-efficacy, and the impact of educational technology on learning. Recently, he has also explored cyberpsychology, studying the influence of social networking and cyber risks on university students. Dr. Fakhrou’s research aims to promote inclusive education and enhance learning outcomes through psychological insights, addressing both academic and emotional aspects to foster better academic achievement and personal development in diverse educational environments.🧪

Author Metrics

Dr. Fakhrou is a prolific researcher with multiple publications in reputable international journals. His work has been cited extensively, contributing significantly to fields such as educational psychology, special education, and cyberpsychology. Notable publications include studies on emotional intelligence, academic self-efficacy, and social media risks, reflecting his diverse research interests. His publications in journals like Multimedia Tools and Applications and the International Journal of Higher Education showcase his impact in education and psychology, with several articles accumulating high citation counts. Dr. Fakhrou’s research is accessible on platforms like ResearchGate, Scopus, and Google Scholar, reflecting his established academic presence.

Publications Top Notes 📄

Smartphone-based food recognition system using multiple deep CNN models 📅
- Authors: A. Fakhrou, J. Kunhoth, S. Al Maadeed
- Journal: Multimedia Tools and Applications
- Volume 80, Issue 21, Pages 33011-33032
- Citations: 50
- Year: 2021
The relationship between academic self-efficacy and academic achievement in students of the department of special education 📅
- Authors: A. Fakhrou, L. H. Habib
- Journal: International Journal of Higher Education
- Volume 11, Issue 2, Pages 1-12
- Citations: 21
- Year: 2022
The Effectiveness of a Proposed Program Titled (Creativity Lamp) in Raising the Primary School Students’ Academic Achievement and Promoting Creativity among Them in Kuwait 📅
- Authors: A. A. Fakhrou, S. A. Ghareeb
- Journal: Journal of Curriculum and Teaching
- Volume 9, Issue 3, Pages 20-32
- Citations: 9
- Year: 2020
Academic performance of engineering students: A predictive validity study of first-year GPA and final-year CGPA 📅
- Authors: A. H. Nurudeen, A. Fakhrou, N. Lawal, S. Ghareeb
- Journal: Engineering Reports
- Volume 6, Issue 5, Article e12766
- Citations: 7
- Year: 2024
Cybercrime Risk Fear Among University Students’ Social Networking Sites: Validity and Reliability 📅
- Authors: A. A. Fakhrou, T. R. Adawi, M. A. Moussa
- Journal: International Journal of Cyber Criminology
- Volume 16, Issue 1, Pages 40–53
- Citations: 5
- Year: 2022

Conclusion

Dr. Fakhrou’s contributions to educational psychology, especially his focus on special needs, emotional intelligence, and the psychological implications of technology, underscore his suitability for the Excellence in Research Award. His dedication to both academic rigor and practical applications reflects a career devoted to enhancing educational practices and supporting student development, making him a deserving candidate for this recognition.

Hebat-Allah S. Tohamy | Recycling and sustanability | Best Researcher Award

Published on 13/11/202413/11/2024 by Network Science

Dr. Hebat-Allah S. Tohamy | Recycling and sustanability | Best Researcher Award

Researcher, at National Research Centre, Egypt 📖

Dr. Hebat-Allah Tohamy is an accomplished organic chemist and researcher specializing in the development of sustainable, high-performance materials from agricultural waste. With over a decade of research experience at the National Research Center, she has spearheaded projects in water treatment, drug delivery, and environmental remediation. Dr. Tohamy has been recognized for her innovative M.Sc. thesis by the National Research Centre and has been featured on Egyptian television for her work in agricultural waste valorization. She actively shares her insights through conferences, webinars, and scientific collaborations worldwide, contributing to the advancement of sustainable technologies.

Profile

Education Background🎓

Dr. Hebat-Allah Tohamy holds a Ph.D. in Organic Chemistry from Helwan University (2020), where she focused on the Preparation, characterization, and applications of carbon allotropes derived from agricultural wastes. Her doctoral research underscores her commitment to sustainable chemistry, specifically in transforming agricultural residues into valuable carbon-based materials. Prior to her Ph.D., Dr. Tohamy earned her M.Sc. in Organic Chemistry from Helwan University in 2017, with a thesis centered on cellulose-based amphiphilic materials. This work laid the groundwork for her expertise in cellulose chemistry and nanomaterials. Dr. Tohamy completed her undergraduate studies at Helwan University, graduating in 2011 with a B.Sc. in Chemistry and Biochemistry, where she achieved top honors, ranking within the best ten students in her cohort. Additionally, she has expanded her expertise through scientific missions to Prague, Czech Republic, in 2019, 2022, and 2023, further enriching her knowledge in international research environments.

Professional Development🌱

Dr. Tohamy is a seasoned researcher at the National Research Center (NRC) in Cairo, where she has contributed significantly to the Cellulose and Paper Department since 2012. Her expertise spans cellulose chemistry, agricultural waste recycling, and nanotechnology, with a focus on developing sustainable materials for applications in water treatment, drug delivery, and environmental remediation. She has an extensive background in materials characterization, including techniques such as XRD, TEM, SEM, IR, TGA&DTA, DSC, Raman spectroscopy, UV, VSM, and fluorescence spectroscopy.

Her work emphasizes the transformation of agro-wastes into high-value materials like graphene oxide, carbon nanotubes, carbon quantum dots, and amphiphilic polymers. She is skilled in designing pH- and thermo-responsive hydrogels, adsorption materials, and sensors for waste contaminant detection. Dr. Tohamy has demonstrated her capabilities in scientific research, laboratory work, and project management on multiple national and international research collaborations.

Research Interests🔬

Dr. Tohamy’s research focuses on sustainable materials development through the recycling of agricultural wastes, particularly in synthesizing cellulose-based and carbon-based nanomaterials. Her work is centered around applications in water treatment, drug delivery, and environmental safety. Key areas of interest include:

Cellulose chemistry and hydrogels
Carbon-based materials like graphene oxide and carbon nanotubes
Kinetics and thermal analysis
Responsive polymers for medical and industrial applications
Material characterization and nanotechnology

Author Metrics

Dr. Hebat-Allah Tohamy is a recognized researcher with a solid impact in the field of organic chemistry and materials science, as reflected in her author metrics. She holds an h-index of 15, demonstrating her work’s high citation rate and influence in advancing sustainable material applications and waste valorization. Dr. Tohamy’s contributions to scientific literature are cataloged on platforms like Scopus and ORCID, where her publications in reputable journals are consistently cited by peers worldwide. Her research spans a range of innovative applications, from nanomaterials to environmental and pharmaceutical applications, underscoring her authority and continued engagement in impactful research.

Publications Top Notes📄

“Fullerenes and tree-shaped/fingerprinted carbon quantum dots for chromium adsorption via microwave-assisted synthesis”
- Journal: RSC Advances
- Publication Year: 2024
- DOI: 10.1039/D4RA04527K
- Contributors: Hebat-Allah S. Tohamy, Mohamed El-Sakhawy, Samir Kamel
- Summary: This study explores the synthesis of fullerenes and uniquely structured carbon quantum dots (tree-shaped and fingerprinted) using microwave-assisted techniques for the adsorption of chromium, a critical environmental contaminant.
“Application of electrospun N-doped carbon dots loaded cellulose acetate membranes as cationic dyes adsorbent”
- Journal: Journal of Environmental Management
- Publication Date: November 2024
- DOI: 10.1016/j.jenvman.2024.122714
- Contributors: Stefania Mottola, Gianluca Viscusi, Hebat-Allah S. Tohamy, Mohamed El-Sakhawy, Giuliana Gorrasi, Iolanda De Marco
- Summary: The article reports on the development of electrospun cellulose acetate membranes enhanced with nitrogen-doped carbon dots, designed for the adsorption of cationic dyes, showcasing potential for water purification applications.
“Development and characterization of fluorescent cellulose succinate hydrogels for efficient chromium adsorption”
- Journal: Journal of Polymer Research
- Publication Date: November 2024
- DOI: 10.1007/s10965-024-04164-4
- Contributors: Hebat-Allah S. Tohamy, Mohamed El-Sakhawy, Beata Strachota, Silvia Mares Barbosa, Adam Strachota, Samir Kamel
- Summary: This research focuses on creating fluorescent cellulose succinate hydrogels, demonstrating their efficacy for chromium ion adsorption, and highlighting their potential use in environmental cleanup.
“Antimicrobial Plectranthus amboinicus emulsions prepared with amphiphilic cellulose stearate”
- Journal: Euro-Mediterranean Journal for Environmental Integration
- Publication Date: November 5, 2024
- DOI: 10.1007/s41207-024-00675-0
- Contributors: Hebat-Allah S. Tohamy, Mohamed El-Sakhawy, Sally A. Abdel-Halim, Hossam M. El-Masry, Mona Mohamed AbdelMohsen
- Summary: The study investigates the preparation of antimicrobial emulsions using amphiphilic cellulose stearate and extracts from Plectranthus amboinicus, aiming to develop eco-friendly antimicrobial solutions.
“Novel, Speedy, and Eco-Friendly Carboxymethyl Cellulose-Nitrogen Doped Carbon Dots Biosensors with DFT Calculations, Molecular Docking, and Experimental Validation”
- Journal: Gels
- Publication Date: October 24, 2024
- DOI: 10.3390/gels10110686
- Contributors: Hebat-Allah S. Tohamy
- Summary: This publication introduces a fast, eco-friendly biosensor based on carboxymethyl cellulose and nitrogen-doped carbon dots. The study includes density functional theory (DFT) calculations, molecular docking, and experimental validation, providing insights into the sensor’s efficiency and accuracy.

Conclusion

Dr. Hebat-Allah S. Tohamy’s work aligns exceptionally well with the core goals of sustainability and environmental stewardship. Her contributions to developing eco-friendly materials from agricultural waste, as well as her significant publication record and respected standing in the field, present a compelling case for her as a deserving recipient of the Best Researcher Award. With further expansion of her research focus and international collaboration, Dr. Tohamy’s contributions are likely to continue growing in impact, making her a fitting and influential leader in her field.

Adla Padma | Blockchain | Best Researcher Award

Published on 11/11/202411/11/2024 by Network Science

Ms. Adla Padma | Blockchain | Best Researcher Award

Research Scholar at VIT Vellore, India 📝

Dr. Adla Padma is an Assistant Professor (On Contract) in the School of Computer Science Engineering and Information Systems (SCORE) at Vellore Institute of Technology (VIT), Vellore, Tamil Nadu. With over six years of teaching and research experience, Dr. Padma is deeply involved in cutting-edge research in blockchain technology, IoT, and privacy preservation frameworks. Her current research focuses on developing efficient blockchain-enabled privacy preservation systems for smart environments. She is passionate about leveraging her academic background and expertise to contribute to the advancement of emerging technologies in computer science.

Profile

Education 🎓

Dr. Adla Padma has a strong academic foundation in Computer Science Engineering, beginning with her Bachelor’s degree (B.Tech) from KBR Engineering College, Yadadri Bhuvanagiri, Telangana, where she graduated with a percentage of 79.94% in 2012. She then pursued her Master’s degree (M.Tech) in Computer Science Engineering at Sri Indu Institute of Engineering and Technology, Rangareddy, Telangana, completing it in 2016 with an impressive 82.75%. Currently, she is a Ph.D. candidate at Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, where she has submitted her thesis on an efficient blockchain-enabled privacy preservation framework for IoT smart environments. Throughout her academic journey, Dr. Padma has consistently demonstrated a commitment to excellence, both in her studies and in her ongoing research contributions to the field of computer science.

Professional Experience 💼

Dr. Padma’s academic career spans over six years, during which she has held positions as an Assistant Professor both at Sri Indu Institute of Engineering and Technology and VIT. Currently, as a faculty member at VIT, she is focusing on research in the fields of blockchain, IoT, and smart environments. She has guided students on various projects, including deep learning models for earthquake prediction and has presented talks on blockchain to B.Tech students. Prior to her position at VIT, she worked as an Assistant Professor in the Department of Computer Science & Engineering at Sri Indu Institute of Engineering and Technology from 2016 to 2020.

Research Interests 🔬

Dr. Adla Padma’s research interests lie at the intersection of cutting-edge technologies such as blockchain, the Internet of Things (IoT), and privacy preservation frameworks. She is particularly focused on developing efficient and scalable blockchain solutions for IoT smart environments, with an emphasis on ensuring privacy and security. Additionally, her work explores the design and analysis of algorithms, machine learning, and artificial intelligence techniques, aiming to address real-world challenges in data management and system optimization. Dr. Padma is also interested in web technologies, particularly in enhancing user experiences through novel image search models, and advancing the field of programming languages, with expertise in C, C++, Python, and Java. Her research aims to contribute to the evolution of smart systems and secure, decentralized environments in various technological domains.

Author Metrics 🏆

Publications:
Dr. Padma has made significant contributions to the academic community, particularly in the areas of blockchain technology, IoT, and privacy preservation. Notably, she has received the Raman Research Award for her publications in these fields, including titles such as “GLSBIoT: GWO-based enhancement for lightweight scalable blockchain for IoT with trust-based consensus” and “Blockchain Based Efficient and Secure Privacy Preserved Framework for Smart Cities.”
Reviewer & Conference Roles:
Dr. Padma serves as a technical reviewer for the American Journal of Information Science and Technology (2024-2027) and has also been a reviewer for the ic-ETITE’24 2nd IEEE International Conference conducted by VIT. She has taken an active role as Technical Panel Incharge and Organizing Committee Member for the same conference.
Awards:
She has been honored with the Raman Research Award for her impactful research contributions, underscoring the recognition of her work within the academic community.

Awards and Achievements 🏆

Raman Research Award for the publication titled “GLSBIoT: GWO-based enhancement for lightweight scalable blockchain for IoT with trust-based consensus,” VIT, Vellore.
Raman Research Award for the publication titled “Blockchain Based Efficient and Secure Privacy Preserved Framework for Smart Cities,” VIT, Vellore.
Technical Reviewer for the American Journal of Information Science and Technology (2024-2027).
Technical Reviewer for the ic-ETITE’24 2nd IEEE International Conference, VIT.
Technical Panel Incharge and Organizing Committee Member for ic-ETITE’24 2nd IEEE International Conference, VIT

Publications Top Notes 📚

Blockchain based an efficient and secure privacy-preserved framework for smart cities
- Authors: A Padma, M Ramaiah
- Journal: IEEE Access
- Publication Year: 2024
- Volume: 19
A review of security vulnerabilities in industry 4.0 applications and the possible solutions using blockchain
- Authors: M Ramaiah, V Chithanuru, A Padma, V Ravi
- Book: Cyber Security Applications for Industry 4.0
- Pages: 63-95
- Publication Year: 2022
- Publisher: Springer
Detecting security breaches on smart contracts through techniques and tools: A brief review – Applications and challenges
- Authors: A Padma, R Mangayarkarasi
- Conference: International Conference on Information and Management Engineering
- Pages: 361-369
- Publication Year: 2022
GLSBIoT: GWO-based enhancement for lightweight scalable blockchain for IoT with trust-based consensus
- Authors: A Padma, M Ramaiah
- Journal: Future Generation Computer Systems
- Volume: 159
- Pages: 64-76
- Publication Year: 2024
A Technologies Study on Trending for IoT Use Cases Aspires to Build Sustainable Smart Cities
- Authors: M Ramaiah, RM Yousuf, R Vishnukumar, A Padma
- Book: Intelligent Systems and Sustainable Computational Models: Concepts
- Publication Year: 2024

Conclusion

Dr. Adla Padma is a highly qualified candidate for the Best Researcher Award. Her expertise in blockchain, IoT, and privacy preservation is well-aligned with current global technological challenges, particularly in the development of smart cities. Her impressive academic background, impactful publications, and significant contributions to research make her a standout figure in her field.

Shurun Wang | Brain function connectivity analysis | Best Researcher Award

Published on 11/11/202411/11/2024 by Network Science

Dr. Shurun Wang | Brain function connectivity analysis | Best Researcher Award

Postdoctoral researcher at University of Science and Technology, China📝

Dr. Shurun Wang is a postdoctoral researcher at the School of Information Science and Technology, University of Science and Technology of China (USTC), specializing in biomedical signal analysis and brain function connectivity analysis. He holds a Ph.D. from the School of Electrical Engineering and Automation, Hefei University of Technology, where he also earned his MSc and BSc degrees. Dr. Wang has actively contributed to academic research and is passionate about advancing understanding in brain connectivity and biomedical systems through his work. He has received several prestigious awards, including the National Scholarship for Doctoral Students and the Outstanding Doctoral Dissertation Award from the Anhui Province Robotics Society.

Profile

Education 🎓

Dr. Shurun Wang has a robust academic background in Electrical Engineering and Automation. He completed his Ph.D. at the School of Electrical Engineering and Automation, Hefei University of Technology, in Hefei, China, from 2019 to 2024, where he specialized in biomedical signal analysis and brain function connectivity. During his doctoral studies, he also had the opportunity to enhance his research through a one-year visiting student program at the Graduate School of Medicine, Juntendo University, Tokyo, Japan, from April 2023 to April 2024. Prior to his Ph.D., Dr. Wang earned both his M.Sc. (2016–2019) and B.Sc. (2012–2016) degrees in Electrical Engineering and Automation, also from Hefei University of Technology, where he gained a strong foundation in electrical systems and automation technologies.

Professional Experience 💼

Dr. Shurun Wang is currently a Postdoctoral Researcher at the School of Information Science and Technology, University of Science and Technology of China (USTC), where he conducts cutting-edge research in biomedical signal analysis and brain function connectivity analysis. Prior to his postdoctoral role, he completed his Ph.D. at the School of Electrical Engineering and Automation, Hefei University of Technology. During his doctoral studies, Dr. Wang also undertook a one-year research stint as a visiting student at the Graduate School of Medicine, Juntendo University, Tokyo, Japan.

Research Interests 🔬

Dr. Wang’s primary research interests lie in biomedical signal analysis, particularly focusing on brain function connectivity. His work aims to develop advanced computational techniques to enhance the understanding of neural systems and brain activity patterns. This research is vital for applications in medical diagnostics, neuroengineering, and cognitive neuroscience, with potential contributions to improving treatments for neurological disorders and enhancing brain-machine interfaces.

Author Metrics 🏆

Dr. Wang has published extensively in top-tier journals and conferences, contributing to the fields of biomedical signal processing and neural networks. His work has gained recognition for its innovation and impact on both theoretical advancements and practical applications.

Awards and Recognition 🏆

National Scholarship for Doctoral Students
Outstanding Doctoral Dissertation Award from Anhui Province Robotics Society
Xplore New Automation Award 2018 of PHOENIX CONTACT

Academic Service

Dr. Wang has contributed significantly to the academic community by reviewing for over 10 reputable journals, including:

IEEE Transactions on Instrumentation and Measurement
IEEE Transactions on Neural Networks and Learning Systems
Scientific Reports
Applied Artificial Intelligence

Publications Top Notes 📚

Title: A novel approach to detecting muscle fatigue based on sEMG by using neural architecture search framework
Authors: S Wang, H Tang, B Wang, J Mo
Journal: IEEE Transactions on Neural Networks and Learning Systems
Volume: 34, Issue: 8, Pages: 4932-4943
Year: 2021
Citations: 28
Summary: This paper proposes a novel method for detecting muscle fatigue from surface electromyographic (sEMG) signals by employing a neural architecture search (NAS) framework. The study demonstrates that using NAS can efficiently identify optimal deep learning architectures for accurate and real-time fatigue detection, making it a significant contribution to health monitoring technologies.
Title: Analysis of fatigue in the biceps brachii by using rapid refined composite multiscale sample entropy
Authors: S Wang, H Tang, B Wang, J Mo
Journal: Biomedical Signal Processing and Control
Volume: 67, Article Number: 102510
Year: 2021
Citations: 24
Summary: This study focuses on the analysis of muscle fatigue in the biceps brachii using rapid refined composite multiscale sample entropy (rRCMSE), a novel method to quantify the complexity of sEMG signals during fatigue. The research provides a reliable approach for muscle fatigue assessment in clinical and rehabilitation settings.
Title: A double threshold adaptive method for robust detection of muscle activation intervals from surface electromyographic signals
Authors: H Tang, S Wang, Q Tan, B Wang
Journal: IEEE Transactions on Instrumentation and Measurement
Volume: 71, Article Number: 1-12
Year: 2022
Citations: 5
Summary: This paper introduces a double-threshold adaptive method to improve the robustness of detecting muscle activation intervals from sEMG signals. The method enhances the reliability and accuracy of muscle activation detection, which is crucial for fatigue monitoring and rehabilitation applications.
Title: Continuous estimation of human joint angles from sEMG using a multi-feature temporal convolutional attention-based network
Authors: S Wang, H Tang, L Gao, Q Tan
Journal: IEEE Journal of Biomedical and Health Informatics
Volume: 26, Issue: 11, Pages: 5461-5472
Year: 2022
Citations: 4
Summary: This paper proposes a deep learning-based model that estimates human joint angles continuously from sEMG signals. The model uses a temporal convolutional attention mechanism to process multiple features, enabling precise real-time joint angle estimation for applications in rehabilitation and prosthetics.
Title: Optimizing graph neural network architectures for schizophrenia spectrum disorder prediction using evolutionary algorithms
Authors: S Wang, H Tang, R Himeno, J Solé-Casals, CF Caiafa, S Han, S Aoki, …
Journal: Computer Methods and Programs in Biomedicine
Volume: 257, Article Number: 108419
Year: 2022
Citations: Not specified
Summary: This paper focuses on optimizing graph neural network (GNN) architectures for predicting schizophrenia spectrum disorder. By using evolutionary algorithms, the study improves model accuracy, highlighting the potential of AI in mental health diagnosis and prognosis.

Conclusion

Dr. Shurun Wang is an outstanding candidate for the Best Researcher Award, owing to his remarkable contributions to biomedical signal analysis, brain function connectivity, and innovative health technologies. His research in detecting muscle fatigue, improving neurodiagnostic systems, and exploring neural systems for mental health prediction has the potential to revolutionize the field. With his continued dedication to advancing computational techniques in health sciences, Dr. Wang is poised to make even greater strides in improving medical diagnostics, neuroengineering, and treatment methodologies for neurological disorders.

Seyyed Amirreza Abdollahi | Gas Turbines | Best Researcher Award

Published on 11/11/202411/11/2024 by Network Science

Mr. Seyyed Amirreza Abdollahi | Gas Turbines | Best Researcher Award

Researcher at University of Tabriz, Iran📝

Seyyed Amirreza Abdollahi is a mechanical engineer with a focus on renewable energy technologies and energy system optimization. With extensive experience in research, teaching, and development, Abdollahi has a proven track record in the design and analysis of sustainable energy solutions. He combines academic knowledge with practical insights, contributing to advancements in renewable energy research and promoting sustainable practices within the engineering community.

Profile

Education 🎓

Seyyed Amirreza Abdollahi graduated with a Bachelor of Science in Mechanical Engineering from the University of Tabriz (2018-2022), achieving an impressive GPA of 17.90 out of 20. He ranked in the top 1.5% of candidates in both his undergraduate and M.Sc. university entrance exams, highlighting his academic excellence and dedication to mechanical engineering studies.

Professional Experience 💼

Abdollahi has accumulated hands-on experience across various roles within the field of mechanical engineering, particularly in renewable energy and thermal power systems. He currently holds a position in Research and Development (R&D) at Foolad Gharb, a subsidiary of Safa Holding, where he contributes to innovative mechanical engineering projects. Previously, he served as a project advisor for Sabir International Co. and worked as a teacher assistant in several technical courses, including Heat Exchanger, Advanced Engineering Mathematics, Heat Transfer, and Power Plants, all within the University of Tabriz. He completed an internship at the Tabriz Thermal Power Plant, where he gained practical insights into thermodynamic systems.

Research Interests 🔬

Abdollahi’s research interests are primarily in renewable energy systems, including wind and solar power generation, and energy efficiency. He is particularly focused on advanced topics such as exergy analysis, piezoelectric micropumps, photovoltaics, nanofluids, fuel cell technologies, and HVAC systems. His work aims to improve the efficiency and sustainability of energy systems, aligning with global priorities in clean energy and sustainability.

Author Metrics 🏆

Abdollahi has authored and contributed to multiple articles and presentations within the field of mechanical engineering. His work emphasizes innovative solutions in renewable energy, evidenced by his active participation in international conferences and publication contributions, especially around the design and optimization of energy systems.

Publications Top Notes 📚

Title: Computer simulation of Cu: AlOOH/water in a microchannel heat sink using a porous media technique and solved by numerical analysis AGM and FEM
Authors: SA Abdollahi, P Jalili, B Jalili, H Nourozpour, Y Safari, P Pasha, DD Ganji
Journal: Theoretical and Applied Mechanics Letters
Volume: 13, Issue 3, Article 100432
Year: 2023
Citations: 55
Summary: This study focuses on the computer simulation of a Cu: AlOOH/water nanofluid in a microchannel heat sink. Utilizing a porous media technique, the research applies both the Adomian Decomposition Method (ADM) and Finite Element Method (FEM) to investigate heat transfer enhancement in the heat sink, providing insights for applications in advanced cooling systems.
Title: Investigating heat transfer and fluid flow betwixt parallel surfaces under the influence of hybrid nanofluid suction and injection with numerical analytical technique
Authors: SA Abdollahi, A Alizadeh, M Zarinfar, P Pasha
Journal: Alexandria Engineering Journal
Volume: 70, Pages 423-439
Year: 2023
Citations: 43
Summary: This article examines the heat transfer and fluid flow characteristics between parallel surfaces using a hybrid nanofluid. A unique approach involving nanofluid suction and injection is analyzed, providing critical insights into fluid mechanics and thermal properties for applications such as cooling systems and industrial fluid handling.
Title: Computational study of blood hemodynamic in ICA aneurysm with coiling embolism
Authors: M Mirzaei Poueinak, SA Abdollahi, A Alizadeh, MA Youshanlui, H Zekri
Journal: International Journal of Modern Physics C
Volume: 34, Issue 10, Article 2350138
Year: 2023
Citations: 23
Summary: This computational study investigates the hemodynamics of blood flow in an internal carotid artery (ICA) aneurysm treated with coiling embolism. Using fluid dynamics models, the paper provides insight into blood flow patterns, pressure distribution, and aneurysm stability, which is critical for advancements in medical treatment and patient outcomes.
Title: Influence of extruded injector nozzle on fuel mixing and mass diffusion of multi-fuel jets in the supersonic cross flow: computational study
Authors: SA Abdollahi, G Rajabikhorasani, A Alizadeh
Journal: Scientific Reports
Volume: 13, Issue 1, Article 12095
Year: 2023
Citations: 19
Summary: This computational analysis investigates the effects of extruded injector nozzles on fuel mixing and mass diffusion in a supersonic cross flow, providing valuable insights for improving fuel injection efficiency in high-speed propulsion systems, with applications in aerospace and automotive industries.
Title: Removal of ciprofloxacin and cephalexin antibiotics in water environment by magnetic graphene oxide nanocomposites; optimization using response surface methodology
Authors: M Alishiri, SA Abdollahi, AN Neysari, SF Ranjbar, N Abdoli
Journal: Results in Engineering
Volume: 20, Article 101507
Year: 2023
Citations: Not specified
Summary: This study explores the removal of pharmaceutical contaminants, specifically ciprofloxacin and cephalexin, from water using magnetic graphene oxide nanocomposites. By optimizing parameters through response surface methodology, this research presents an effective method for water purification, addressing environmental pollution concerns.

Conclusion

Seyyed Amirreza Abdollahi’s academic achievements, diverse research contributions, and practical engineering experience make him a strong candidate for the Best Researcher Award. His ability to merge theory with practical applications, particularly in renewable energy and thermal management, speaks to his potential to drive significant advancements in sustainable energy solutions. With continued focus on sustainability metrics and expanded international collaborations, Abdollahi could further solidify his impact as a leading researcher in mechanical and energy engineering.

Zahra Barati | epidemiology | Best Researcher Award

Published on 11/11/202411/11/2024 by Network Science

Ms. Zahra Barati | epidemiology | Best Researcher Award

Zahra Barati at Isfahan University of Medical Sciences, Isfahan, Iran📝

Zahra Barati is a skilled epidemiologist with a strong foundation in public health research and statistical analysis. She has demonstrated excellence in academic achievements, teaching, and leadership within her field. As a distinguished student and a dedicated researcher, Zahra has contributed to significant research in infectious disease epidemiology, including a recent thesis on bovine brucellosis, and has received multiple recognitions for her academic and professional contributions.

Profile