Assistant Professor at University of Science and Culture, Iran📖

Dr. Alireza Rezvanian is an accomplished academic and researcher, serving as an Assistant Professor at the University of Science and Culture (USC) in Tehran, Iran. He holds multiple editorial positions, including Associate Editor for journals such as CAAI Transactions on Intelligence Technology, Human-Centric Computing and Information Sciences, The Journal of Engineering, and Data in Brief. Dr. Rezvanian is actively involved in various professional and scientific activities, including serving as the Director of Information and Scientific Resources at USC and contributing to the IEEE Computer Society Iran Chapter.

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Scopus Profile

Orcid Profile

Google Scholar Profile

Education Background🎓

Dr. Rezvanian completed his Ph.D. in Computer Engineering from Amirkabir University of Technology (Tehran Polytechnic) in 2016, under the guidance of Dr. Mohammad Reza Meybodi. His doctoral thesis focused on “Stochastic Graphs for Social Network Analysis.” He holds a Master’s degree in Computer Engineering from Islamic Azad University of Qazvin (2010), where he specialized in improving Artificial Immune System algorithms using Learning Automata for dynamic environments. He also earned a Bachelor’s degree in Computer Engineering from Bu-Ali Sina University of Hamedan (2007).

Professional Experience🌱

Dr. Rezvanian has extensive teaching and research experience across multiple prestigious institutions. Currently, he is an Assistant Professor at the University of Science and Culture, Tehran. He is also an Adjunct Professor at Amirkabir University of Technology, the University of Tehran, and Tarbiat Modares University. His leadership roles include serving as the Head of the Computer Engineering Department at USC (2021-2023) and as the Director of Information and Scientific Resources at USC since 2023. He has previously held research positions at the Institute for Research in Fundamental Sciences (IPM) and the Niroo Research Institute (NRI).

Research Interests🔬

Dr. Rezvanian’s research interests lie in the areas of complex networks, social network analysis, machine learning, learning automata, data mining, and soft computing. His work focuses on the application of evolutionary algorithms, image processing, and stochastic graphs for modeling social networks. His research aims to provide insights into real-world applications through innovative techniques in network analysis and machine learning.

Author Metrics

Dr. Rezvanian has a strong academic presence, with an H-index of 26 on Google Scholar (2024), 23 on Scopus, and 18 on Web of Science. He has authored and co-authored numerous research articles in renowned journals and conferences, contributing significantly to the fields of computer science, machine learning, and network analysis. His work has earned him recognition and a substantial citation count, further solidifying his impact in academia.

Publications Top Notes 📄

1. Robust Fall Detection Using Human Shape and Multi-Class Support Vector Machine

Authors: H. Foroughi, A. Rezvanian, A. Paziraee
Conference: Sixth Indian Conference on Computer Vision, Graphics & Image Processing (ICVGIP 2008)
Year: 2008
Summary: This paper focuses on a robust fall detection system utilizing human shape and a multi-class support vector machine (SVM) for classifying human body shapes and movements. The system aims to effectively detect falls, which is crucial in healthcare applications like elderly care.

2. Sampling from Complex Networks Using Distributed Learning Automata

Authors: A. Rezvanian, M. Rahmati, M.R. Meybodi
Journal: Physica A: Statistical Mechanics and its Applications
Volume: 396
Pages: 224–234
Year: 2014
Summary: This paper introduces a method for sampling complex networks using distributed learning automata (LA), a technique inspired by machine learning algorithms. The approach aims to enhance network analysis by efficiently exploring and sampling complex graph structures.

3. Minimum Positive Influence Dominating Set and Its Application in Influence Maximization: A Learning Automata Approach

Authors: M.M.D. Khomami, A. Rezvanian, N. Bagherpour, M.R. Meybodi
Journal: Applied Intelligence
Volume: 48 (3)
Pages: 570–593
Year: 2018
Summary: This paper presents a novel approach for solving the Minimum Positive Influence Dominating Set (MPIDS) problem, using learning automata for influence maximization in social networks. The proposed method addresses the optimization challenges in selecting influential nodes for spreading information effectively in network-based applications.

4. CDEPSO: A Bi-population Hybrid Approach for Dynamic Optimization Problems

Authors: J.K. Kordestani, A. Rezvanian, M.R. Meybodi
Journal: Applied Intelligence
Volume: 40 (4)
Pages: 682–694
Year: 2014
Summary: The paper introduces CDEPSO (Cognitive Dynamic Evolutionary Particle Swarm Optimization), a hybrid approach that integrates bi-population evolutionary algorithms to address dynamic optimization problems. The method aims to improve the solution quality and efficiency in environments where the optimization landscape changes over time.

5. Cellular Edge Detection: Combining Cellular Automata and Cellular Learning Automata

Authors: M. Hasanzadeh Mofrad, S. Sadeghi, A. Rezvanian, M.R. Meybodi
Journal: AEU-International Journal of Electronics and Communications
Volume: 69 (9)
Pages: 1282–1290
Year: 2015
Summary: This paper explores the combination of cellular automata (CA) and cellular learning automata (CLA) for edge detection in image processing. The approach leverages the computational power of CA and CLA to enhance the edge detection process in digital images, contributing to improvements in image recognition and processing tasks.

Conclusion

Dr. Alireza Rezvanian is highly deserving of the Network Science Excellence Award due to his pioneering contributions to the field of complex networks and social network analysis. His research not only provides innovative methods for understanding and optimizing networks but also demonstrates a strong academic leadership role in advancing network science. With his continued focus on interdisciplinary research and industry collaboration, Dr. Rezvanian is poised to make even greater contributions to the field of network science, making him a worthy recipient of this prestigious award.

Jose Mendes | Network Theory | Network Science Visionary Award

Published on 07/12/202407/12/2024 by Network Science

Prof. Jose Mendes | Network Theory | Network Science Visionary Award

Professor,at univ aveiro, Portugal📖

José Fernando Mendes is a Full Professor at the Department of Physics, University of Aveiro, Portugal, and a globally recognized expert in statistical physics and complex systems. His pioneering research on ‘small-world’ and ‘scale-free’ networks has significantly influenced multiple domains, including neuroscience, ecology, and epidemiology. A Fellow of the American Physical Society (APS) and the Academia Europaea, he has published over 160 peer-reviewed articles, authored three books with Oxford and Cambridge University Press, and presented groundbreaking analytical solutions to major network models. His contributions have earned him numerous accolades, including the Senior Prize of the Complex Systems Society (2020) and honorary fellowships.

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Google Scholar Profile

Education Background🎓

José Fernando Mendes holds a Habilitation in Physics from the University of Porto, Portugal (2002), a Ph.D. in Physics from the same institution (1995), and a Master’s in Physics from the University of Porto (1990). His extensive academic background has equipped him with the expertise needed to become a leading figure in his field, particularly in theoretical physics and complex systems.

Professional Experience🌱

José Fernando Mendes has an illustrious career in academia, holding the position of Full Professor at the Department of Physics, University of Aveiro, Portugal, since 2005. Before this, he served as Associate Professor at the same department (2002-2005) and Assistant Professor at the University of Porto, Portugal (1995-2002). Mendes has also held prestigious roles as a visiting researcher and invited professor at various renowned institutions worldwide, including École Polytechnique Fédérale de Lausanne (EPFL), Nanyang Technical University (NTU), and ETH Zurich, among others. Additionally, he has contributed significantly to university administration, having served as Vice-Rector for Research at the University of Aveiro (2010-2018) and Director of the Associated Laboratory I3N from 2009 to 2010, with renewed leadership in 2023.

Research Interests🔬

Prof. Mendes’ research spans statistical physics, complex systems, granular media, soft condensed matter, complex networks, and computational physics. He is especially known for:

Analytical solutions of small-world and scale-free network models.
Statistical mechanics approaches for random graphs.
Applications in neuroscience, epidemics modeling, and ecology.
Hybrid phase transitions and explosive percolation.

Author Metrics

José Fernando Mendes has made a substantial impact in his field, with over 160 papers published in peer-reviewed journals, including high-impact journals such as Reviews of Modern Physics, Nature Physics, and Physical Review Letters. His scholarly work has earned him over 21,000 citations, an h-index of 49, and an average of 70 citations per paper. Notably, his two books published by Oxford University Press have received over 3,400 citations. His work on complex networks and statistical physics has significantly influenced various scientific disciplines, cementing his position as a leading figure in his area of expertise.

Major Breakthroughs

Exact analytical solutions for small-world phenomena and the Albert-Barabási model.
Generalized scaling for non-equilibrium systems.
Data-driven models for COVID-19 and other epidemics.
Introduced metrics for ranking scientists and analyzing mobility program disparities.

Publications Top Notes 📄

1. Evolution of Networks: From Biological Nets to the Internet and WWW

Authors: S.N. Dorogovtsev, J.F.F. Mendes
Publisher: Oxford University Press, 2003
Year: 2003
Content Summary: This book explores the principles and mechanisms of network evolution across biological, technological, and social systems, focusing on the Internet and the World Wide Web.
Citations: 4185

2. Evolution of Networks

Authors: S.N. Dorogovtsev, J.F.F. Mendes
Journal: Advances in Physics, 51(4), pp. 1079–1187
Year: 2002
DOI: 10.1080/00018730110112519
Content Summary: This comprehensive review covers network evolution mechanisms, small-world and scale-free networks, and their clustering properties, with applications in diverse real-world systems.
Citations: 4140

3. Critical Phenomena in Complex Networks

Authors: S.N. Dorogovtsev, A.V. Goltsev, J.F.F. Mendes
Journal: Reviews of Modern Physics, 80(4), pp. 1275–1335
Year: 2008
DOI: 10.1103/RevModPhys.80.1275
Content Summary: This paper investigates critical phenomena in complex networks, focusing on phase transitions, percolation, and synchronization in fields ranging from physics to biology.
Citations: 2520

4. Sync and Swarm: Solvable Model of Nonidentical Swarmalators

Authors: S. Yoon, K.P. O’Keeffe, J.F.F. Mendes, A.V. Goltsev
Journal: Physical Review Letters, 129(20), Article 208002
Year: 2022
DOI: 10.1103/PhysRevLett.129.208002
Content Summary: This paper introduces a solvable model of swarmalators, entities combining synchronization and swarming, with applications in fields such as biology and robotics.
Citations: 22

5. Weak Percolation on Multiplex Networks with Overlapping Edges

Authors: G.J. Baxter, R.A. da Costa, S.N. Dorogovtsev, J.F.F. Mendes
Journal: Chaos, Solitons and Fractals, 164, Article 112619
Year: 2022
DOI: 10.1016/j.chaos.2022.112619
Content Summary: This study explores weak percolation in multiplex networks with overlapping edges, providing insights into their structural robustness and critical behavior.
Citations: 5

Conclusion

Prof. José Fernando Mendes is an outstanding candidate for the Network Science Visionary Award due to his pioneering contributions to network theory, his interdisciplinary influence, and his sustained academic excellence. His ability to provide analytical solutions to complex problems has profoundly impacted network science. To further amplify his impact, expanding collaborations with other research sectors and embracing emerging technologies would be beneficial. Overall, his legacy in network science is already firmly established, and his continued work promises to shape the field for many years to come.

Network Science Visionary Award

Published on 17/11/202323/11/2023 by Network Science

Introduction of Network Science Visionary Award

Welcome to the Network Science Visionary Award, a prestigious recognition celebrating those who exemplify groundbreaking contributions and extraordinary vision in the field of network science. This award aims to honor individuals whose innovative thinking and transformative efforts have significantly advanced our understanding of networks.

Eligibility:

Open to professionals, researchers, and innovators of all ages, the Network Science Visionary Award is accessible to anyone who has made noteworthy contributions to the field of network science. There are no age limits, and candidates may come from diverse educational backgrounds.

Qualifications:

Candidates must possess a strong foundation in network science, demonstrated through outstanding academic achievements, research publications, and a history of impactful contributions to the field.

Evaluation Criteria:

The award committee will assess candidates based on the depth and breadth of their contributions to network science, the significance of their research, and the transformative impact of their work on the field.

Submission Guidelines:

Submit a comprehensive biography, an abstract outlining your key contributions, and supporting files that showcase the impact of your work. Ensure that your submission clearly demonstrates your visionary approach to network science.

Recognition:

The Network Science Visionary Award brings unparalleled recognition and prestige to the recipient. Awardees will be featured in prominent industry publications, invited to speak at leading conferences, and connected with a network of fellow visionaries.

Community Impact:

Beyond individual recognition, this award acknowledges the broader impact of visionary contributions on the community. Awardees are celebrated for their role in advancing the collective understanding of network science.

Innovation Excellence Award in Network Science and Graph Analytics

Introduction of Innovation Excellence Award in Network Science and Graph Analytics Welcome to the forefront of recognition in the realm of Network Science and Graph Analytics! The Innovation Excellence Award

Outstanding Research Achievement Award in Network Science and Graph Analytics

Introduction of Outstanding Research Achievement Award in Network Science and Graph Analytics Welcome to the pinnacle of excellence in the realm of Network Science and Graph Analytics! The "Outstanding Research

Academic Excellence Award in Network Science and Graph Analytics

Introduction of Academic Excellence Award in Network Science and Graph Analytics Welcome to the Academic Excellence Award in Network Science and Graph Analytics, recognizing outstanding achievements and contributions in the

Industry Impact Award in Network Science and Graph Analytics

Introduction of Industry Impact Award in Network Science and Graph Analytics Welcome to the Industry Impact Award in Network Science and Graph Analytics—an accolade honoring pioneers shaping the future of

Leadership in Business Applications Award in Network Science and Graph Analytics

Introduction of Leadership in Business Applications Award in Network Science and Graph Analytics Welcome to the forefront of innovation! The Leadership in Business Applications Award in Network Science and Graph

Collaborative Achievement Award in Network Science and Graph Analytics

Introduction of Collaborative Achievement Award in Network Science and Graph Analytics Welcome to the Collaborative Achievement Award in Network Science and Graph Analytics—a prestigious recognition celebrating innovation and collaboration in

Emerging Talent Award in Network Science and Graph Analytics

Introduction of Emerging Talent Award in Network Science and Graph Analytics Welcome to the future of Network Science and Graph Analytics! The Emerging Talent Award celebrates individuals who showcase exceptional

Strategic Implementation Award in Network Science and Graph Analytics

Introduction of Strategic Implementation Award in Network Science and Graph Analytics Welcome to the Strategic Implementation Award in Network Science and Graph Analytics—an accolade designed to recognize and honor outstanding

Pioneering Contribution Award in Network Science and Graph Analytics

Introduction of Pioneering Contribution Award in Network Science and Graph Analytics Welcome to the Pioneering Contribution Award in Network Science and Graph Analytics, celebrating the trailblazers shaping the future of

Outstanding Contribution to Graph Analytics in Business Award

Introduction of Outstanding Contribution to Graph Analytics in Business Award Welcome to the pinnacle of recognition for leaders shaping the future of Graph Analytics in the business realm. The Outstanding

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Research Advancement Award in Network Science and Graph Analytics

Published on 17/11/202323/11/2023 by Network Science

Introduction of Research Advancement Award in Network Science and Graph Analytics

Welcome to the forefront of innovation and excellence in the realm of Network Science and Graph Analytics! The Research Advancement Award is a beacon of recognition, celebrating those who push the boundaries of knowledge and foster progress in this dynamic field.

Award Eligibility:

Open to researchers, academics, and industry professionals, the Research Advancement Award seeks to honor individuals who have made significant contributions to the advancement of knowledge in Network Science and Graph Analytics.

Age Limits:

No age restrictions; innovation knows no boundaries.

Qualification:

Individuals with a background in Network Science and Graph Analytics, showcasing a profound understanding of the subject matter.

Publications Requirements:

Candidates should demonstrate a substantial record of high-impact publications, showcasing their commitment to disseminating valuable insights within the community.

Requirements and Evaluation Criteria:

Proven impact on the field through publications, projects, or innovations.
Demonstrated leadership and influence in the Network Science and Graph Analytics community.
Sustained commitment to research and advancement.
Contribution to collaborative efforts, fostering knowledge exchange.

Submission Guidelines:

Detailed guidelines regarding submission formats, deadlines, and document specifications can be found on our official website.

Recognition:

Recipients of the Research Advancement Award will be acknowledged at a prestigious ceremony, gaining visibility within the global Network Science and Graph Analytics community.

Community Impact:

By recognizing and celebrating outstanding contributions, this award aims to inspire and uplift the entire Network Science and Graph Analytics community.

Biography:

Applicants are required to submit a concise biography highlighting their journey, achievements, and vision for the future of Network Science and Graph Analytics.

Abstract and Supporting Files:

In addition to the biography, applicants should submit a comprehensive abstract outlining their noteworthy contributions. Supporting files such as publications, project documentation, or other relevant materials are encouraged.

Innovation Excellence Award in Network Science and Graph Analytics

Outstanding Research Achievement Award in Network Science and Graph Analytics

Academic Excellence Award in Network Science and Graph Analytics

Industry Impact Award in Network Science and Graph Analytics

Leadership in Business Applications Award in Network Science and Graph Analytics

Collaborative Achievement Award in Network Science and Graph Analytics

Emerging Talent Award in Network Science and Graph Analytics

Strategic Implementation Award in Network Science and Graph Analytics

Pioneering Contribution Award in Network Science and Graph Analytics

Outstanding Contribution to Graph Analytics in Business Award

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Academic Excellence Award in Network Science and Graph Analytics

Published on 16/11/202323/11/2023 by Network Science

Introduction of Academic Excellence Award in Network Science and Graph Analytics

Welcome to the Academic Excellence Award in Network Science and Graph Analytics, recognizing outstanding achievements and contributions in the dynamic fields of network science and graph analytics. This prestigious award celebrates individuals who have demonstrated unparalleled academic prowess, pushing the boundaries of knowledge and innovation in these interconnected domains.

Eligibility:

Open to researchers, scholars, and academics globally.
No age limits apply.
Qualifications: Minimum of a Master's degree in a relevant field.
Publications: Demonstrated scholarly contributions in peer-reviewed journals or conference proceedings.

Requirements:

Original research work in the field of Network Science or Graph Analytics.
Submission of a detailed biography and abstract of the work.
Supporting files containing relevant data, methodologies, and findings.

Evaluation Criteria:

Submissions will be evaluated based on:

Academic rigor and originality of the research.
Significance and impact on the field.
Methodological soundness.
Contribution to the advancement of Network Science and Graph Analytics.

Submission Guidelines:

Submissions must be in English.
Include a comprehensive biography.
Submit an abstract and supporting files in PDF format.

Recognition:

The awardee will receive:

A certificate of Academic Excellence.
Recognition at an international conference.
Opportunities for collaboration and networking.

Community Impact:

The recipient's work should demonstrate a positive influence on the academic community, fostering collaboration and knowledge dissemination.

Biography:

Provide a brief biography highlighting academic achievements, relevant experience, and contributions to Network Science and Graph Analytics.

Abstract and Supporting Files:

The abstract should succinctly summarize the research, while supporting files should contain detailed methodologies, data, and findings.

Innovation Excellence Award in Network Science and Graph Analytics

Outstanding Research Achievement Award in Network Science and Graph Analytics

Academic Excellence Award in Network Science and Graph Analytics

Industry Impact Award in Network Science and Graph Analytics

Leadership in Business Applications Award in Network Science and Graph Analytics

Collaborative Achievement Award in Network Science and Graph Analytics

Emerging Talent Award in Network Science and Graph Analytics

Strategic Implementation Award in Network Science and Graph Analytics

Pioneering Contribution Award in Network Science and Graph Analytics

Outstanding Contribution to Graph Analytics in Business Award

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Assist. Prof. Dr. Alireza Rezvanian | Complex Social Networks | Network Science Excellence Award

Profile

Education Background🎓

Author Metrics

Prof. Jose Mendes | Network Theory | Network Science Visionary Award

Profile

Education Background🎓

Research Interests🔬

Author Metrics

Major Breakthroughs

Publications Top Notes 📄

Introduction of Network Science Visionary Award

Eligibility:

Qualifications:

Evaluation Criteria:

Submission Guidelines:

Recognition:

Community Impact:

Introduction of Research Advancement Award in Network Science and Graph Analytics

Award Eligibility:

Age Limits:

Qualification:

Publications Requirements:

Requirements and Evaluation Criteria:

Submission Guidelines:

Recognition:

Community Impact:

Biography:

Abstract and Supporting Files:

Introduction of Academic Excellence Award in Network Science and Graph Analytics

Eligibility:

Requirements:

Evaluation Criteria:

Submission Guidelines:

Recognition:

Community Impact:

Biography:

Abstract and Supporting Files: