Bagher Zarei | Machine Learning | Best Researcher Award

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Dr. Bagher Zarei | Machine Learning | Best Researcher Award

Dr at IAU, Iran

Dr. Bagher Zarei is an accomplished computer engineering expert and a faculty member at the Department of Computer Engineering, Shabestar Branch, Islamic Azad University in Iran. With a Ph.D. in Computer Engineering, Dr. Zarei’s research spans complex networks, social network analysis, evolutionary algorithms, and chaos theory. His scholarly work has contributed to significant advancements in fields such as learning automata and soft computing, with publications in renowned journals like Chaos and The Journal of Supercomputing. As a dedicated educator, he teaches courses in complex networks, AI, and data structures, actively mentoring future engineers and researchers.

Publication Profile

Scholar

Education 🎓

Ph.D. in Computer Engineering Institution: Islamic Azad University, Qazvin Branch (2014–2020) Supervisor: Dr. Mohammad Reza Meybodi Co-Supervisor: Dr. Behrouz Masoumi, Thesis: “Community Structure Detection in Complex Networks Using Evolutionary Algorithms and Learning Automata Based on Chaos Theory”. M.Sc. in Computer Engineering Institution: Islamic Azad University, Qazvin Branch (2004–2006) Supervisor: Dr. Mohammad Reza Meybodi Thesis: “Solving Complex Problems Using a Hybrid Approach (Genetic Algorithms + Learning Automata)”. B.Sc. in Computer Engineering Institution: Islamic Azad University, Shabestar Branch (2000–2004) Supervisor: Dr. Ali Farzan, Thesis: “Design, Analysis, and Implementation of a Central Laboratory System for Tabriz”

Experienceđź’Ľ

Dr. Zarei is a faculty member at Islamic Azad University, Shabestar Branch, where he has taught courses on complex networks, evolutionary algorithms, artificial intelligence, and algorithm design. His academic role also extends to the Tabriz Branch, where he educates students in programming, data structures, and systems simulation. With a decade of experience in teaching and research, Dr. Zarei has also co-authored several articles on complex network analysis, applying his expertise in courses and workshops that foster student engagement in advanced computing disciplines.

Awards and Honors 🏆

Dr. Zarei has been recognized for his research contributions to computer engineering, specifically in the areas of evolutionary algorithms and chaos theory. His collaborative work has led to multiple publications in high-impact journals. Notable acknowledgments of his contributions include awards for his groundbreaking studies in complex networks and soft computing. His scholarly pursuits have positioned him as a thought leader in the application of chaos theory in social network analysis, with his research frequently cited by peers globally.

Research Focus 🔬

Dr. Zarei’s research is concentrated on soft computing, complex networks, social network analysis, evolutionary algorithms, learning automata, and chaos theory. His work aims to solve intricate problems using hybrid methodologies, notably combining genetic algorithms with learning automata. Dr. Zarei’s recent projects explore the detection of community structures in networks, advancing the field by using chaos theory principles. His research provides innovative solutions to improve network analysis techniques, making strides in understanding patterns within social and computational networks.

Conclusion 🎓

Dr. Bagher Zarei’s expertise in computer engineering, particularly in the realms of soft computing, complex networks, and evolutionary algorithms, makes him a compelling candidate for the “Best Researcher Award.” His commitment to teaching and his innovative research contributions demonstrate his dedication to both academic and applied advancements in computer science. Continued emphasis on practical collaborations and international exposure would further strengthen his candidacy and broaden the influence of his work.

Publication Top Notes

  • Novel Cluster-Based Routing Protocol in Wireless Sensor Networks
    • Journal: International Journal of Computer Science Issues (IJCSI)
    • Date: 2010
    • Citations: 71

 

  • Detecting Community Structure in Complex Networks Using Genetic Algorithm Based on Object Migrating Automata
    • Journal: Computational Intelligence
    • Date: 2020
    • Citations: 20

 

  • A Hybrid Method for Solving Traveling Salesman Problem
    • Conference: 6th IEEE/ACIS International Conference on Computer and Information Science
    • Date: 2007
    • Citations: 17

 

  • Chaotic Memetic Algorithm and Its Application for Detecting Community Structure in Complex Networks
    • Journal: Chaos: An Interdisciplinary Journal of Nonlinear Science
    • Date: 2020
    • Citations: 12

 

  • A Source-Code Aware Method for Software Mutation Testing Using Artificial Bee Colony Algorithm
    • Journal: Journal of Electronic Testing
    • Date: 2022
    • Citations: 10

 

  • A Scalable Lookup Service for P2P File Sharing in MANET
    • Conference: International Conference on Wireless Communications
    • Date: 2007
    • Citations: 10

 

  • Improving Learning Ability of Learning Automata Using Chaos Theory
    • Journal: The Journal of Supercomputing
    • Date: 2021
    • Citations: 8

 

  • A New Evolutionary Model Based on Cellular Learning Automata and Chaos Theory
    • Journal: New Generation Computing
    • Date: 2022
    • Citations: 4

 

Souhail Dhouib | Artificial Intelligence | Best Researcher Award

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Dr. Ibrahim Ben Razek | Neurologie | Best Scholar Award

Dr of Université de Liège, Belgium

Ben Razek Ibrahim is a 4th-year medical resident in neurology with a robust educational background and diverse professional experience across Belgium and Switzerland. 🏥🧠 He holds a medical degree from Université de Liège and specialized qualifications in headaches and migraines from Universités de Paris et Montpellier, as well as advanced epilepsy courses. 📚 His dedication to neurology is reflected in his research and clinical practice, focusing on epilepsy and headache disorders. ✍️🔍 In addition to his clinical skills, Ben is known for his critical thinking, communication, empathy, attention to detail, and autonomy. 🌟💬❤️ His work on cravings for Swiss chocolate has been recognized in the Annals of Neurology. 🍫📜

Profile

Scopus

Education

  • Medical Degree: UniversitĂ© de Liège, Belgium (September 2014 — June 2020)
  • Degree in Headaches and Migraine: UniversitĂ©s de Paris et Montpellier (September 2022 — June 2023)
  • Advanced Courses in Epilepsy: Ligue francophone belge d’Ă©pileptologie (September 2021 — June 2023)

Experience

Ben Razek Ibrahim is a dedicated 4th-year medical resident specializing in neurology. His medical journey began at CHU de Liège, Belgium, where he gained extensive experience in general neurology under the guidance of Pr Maquet P. from October 2020 to September 2021. He then continued his residency at CHR Citadelle, Belgium, working in the general neurology unit and focusing on nerve and muscle diseases with Pr Maertens De Noordhout A. from October 2021 to September 2022. His journey took him to the Hôpitaux Universitaires de Genève, Switzerland, where he specialized in pre-surgical epilepsy under Pr Seeck M. and Pr Picard F. from October 2022 to September 2023. Currently, he is continuing his residency at CHU de Liège, Belgium.

Research Interests

Ben is passionate about neurology, with a particular focus on epilepsy, headaches, and migraines. His research interests have led to notable scientific contributions, including his publication on the newly developed craving for Swiss chocolate, accepted in the Annals of Neurology.

Awards

While specific awards are not mentioned, Ben’s published research in the Annals of Neurology is a significant achievement that reflects his contributions to the field of neurology. His work demonstrates his commitment to advancing knowledge in neurological disorders and his ability to conduct impactful research.

Publication Top Notes

  1. Research Focus: The publication explores an intriguing case of a newly developed craving for Swiss chocolate, contributing to the broader understanding of cravings and their neurological implications.
  2. Authors’ Contribution:
    • Ibrahim Ben Razek: Contributed as a lead author, showcasing his expertise in neurology and research.
    • Maria Isabel Vargas: Collaborated on the study, adding her knowledge and insights.
    • Daniel S. Schechter: Provided critical analysis and support in the research.
    • Margitta Seeck: Offered expertise and guidance, particularly in the context of epilepsy and neurological disorders.
  3. Institutional Context: Conducted at the University Hospital of Geneva and Faculty of Medicine, highlighting the high caliber of the research environment and the expertise of the contributing institutions.
  4. Significance: This publication adds valuable knowledge to the field of neurology, particularly in understanding the complexities of cravings and their potential neurological basis.
  5. Impact: Acceptance in a prestigious journal like Annals of Neurology underscores the quality and relevance of the research, potentially influencing future studies and clinical practices related to cravings and neurological conditions.