Fatemeh Aghagoli | Insight Award | Best Researcher Award

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Dr. Fatemeh Aghagoli | Insight Award | Best Researcher Award

Ph.D student at Iran University of Science and Technology, Iran.

Fatemeh Aghagoli is an Iranian researcher and Ph.D. student at Iran University of Science and Technology, focusing on machine learning, image processing, artificial intelligence, cluster computing, and statistical modeling in medical science. She holds a master’s degree in Mathematical Statistics from the same university and a bachelor’s degree in Statistics from the University of Qom, Iran. Fatemeh is proficient in R, MATLAB, SPSS, Python, and Microsoft Office software. Her research includes projects on brain MRI segmentation, tumor detection in mammography images, and entropy-based methods in image segmentation. She is a member of the National Elite Foundation of Iran and has presented her work at international conferences.

Professional Profiles:

Education:

Fatemeh Aghagoli’s educational background includes a Ph.D. program at the Iran University of Science and Technology, where she is studying in the Faculty of Mathematics and Computer Science. She was accepted into the program without a test as a brilliant talent. Additionally, Fatemeh holds a master’s degree in Mathematical Statistics from Iran University of Science and Technology. Her academic journey began with a bachelor’s degree in Statistics from the University of Qom, Iran.

Research Experience:

Fatemeh Aghagoli is a dedicated researcher with a focus on machine learning, image processing, artificial intelligence, cluster computing, and statistical modeling in medical science. She is currently pursuing a Ph.D. at the Iran University of Science and Technology, Faculty of Mathematics and Computer Science, under the supervision of Professor Rahman Farnoosh. Her academic journey began with a bachelor’s degree in Statistics from the University of Qom, Iran, followed by a master’s degree in Mathematical Statistics from Iran University of Science and Technology. Fatemeh’s research has yielded significant contributions, including the development of improved mixtures of factor analyzers based on dynamic co-clustering for the segmentation of brain MRI images. This work was published in Neurocomputing in 2024. She has also devised a novel approach for automatic tumor detection and localization in mammography images using a mixture of factor analyzers based on co-clustering, which was published in Biomedical Signal Processing and Control in 2024. Furthermore, Fatemeh has presented her research on entropy-based nonparametric methods for mammography image segmentation and the use of the k-mean algorithm and mean entropy in MRI images for brain tumor lesion detection at conferences.

Research Interest:

Fatemeh Aghagoli’s research interests include machine learning, image processing, artificial intelligence, cluster computing, and statistical modeling in medical science. She is particularly interested in applying these techniques to improve the analysis and interpretation of medical imaging data, with a focus on areas such as brain MRI segmentation and tumor detection in mammography images. Her work aims to develop innovative solutions that can enhance the diagnosis and treatment of medical conditions.

Skills:

Fatemeh Aghagoli is proficient in a variety of software tools and programming languages, including R, MATLAB, SPSS, Python, and Microsoft Office. Her skills in these areas enable her to effectively analyze data, develop algorithms, and implement solutions in her research.

 

Toufik Mzili | Unlocked Award | Best Researcher Award

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Mr. Toufik Mzili | Unlocked Award | Best Researcher Award

Researcher at Meru University of Science and Technology, Kenya

Toufik Mzili is a researcher known for his work in optimization algorithms, particularly in solving complex problems like the traveling salesman problem. He has contributed significantly to the field through the development of novel algorithms such as the Discrete Rat Swarm Optimization (DRSO) algorithm. His research has been published in reputable journals and has garnered attention within the academic community, as evidenced by the number of citations his work has received. Mzili’s expertise lies in applying these optimization techniques to various real-world problems, demonstrating their effectiveness and potential impact in practical applications.

Professional Profiles:

Professional Experience:

Mr. Toufik MZILI is an Assistant Professor in Computer Science at the Faculty of Sciences, Chouaib Doukkali University, Morocco. With a background in software engineering, he has also served as the Software Engineer in chief and Coordination Manager at the General Secretariat of the Ministry of Health and Social Protection in Rabat from 2020 to 2023. Additionally, Mr. MZILI has worked as an IT Consultant at Kertys in Casablanca – Settat, Morocco, where he contributed to dematerializing and modernizing business process management, specializing in GED M-FILES design.

Research Experience:

Mr. Toufik MZILI serves as an Associate Editor for the Journal of Optimization and Artificial Intelligence. He provides assistance and support to several journals, including Decision Making Advances (DMA) Journal, Spectrum of Engineering and Management Sciences (SEMS) Journal, Journal of Soft Computing and Decision Analytics, Systemic Analytics Journal, Journal of Decision Analytics and Intelligent Computing (JDAIC), and Theoretical and Applied Computational Intelligence Journal. Additionally, Mr. MZILI acts as a reviewer and appraiser for prestigious journals such as the Journal of King Saud University – Computer and Information Sciences (Elsevier), Advanced Engineering Informatics (Elsevier), Results in Control and Optimization (Elsevier), Informatics in Medicine Unlocked (Elsevier), Decision Making: Applications in Management and Engineering, Operational Research in Engineering Sciences: Theory and Applications, IET Control Theory & Applications, PeerJ Computer Science, Journal of Physics Conference Series, and Optimization and Data Science in Industrial Engineering.

Skills:

Mr. Toufik MZILI is proficient in a variety of programming technologies, including Java, JEE, C++, PHP, XML, and CSS. He is experienced in using development frameworks such as Springs (MVC, Boot), JSF2, Laravel, VueJs, Livewire, and React. In terms of IDE, Mr. MZILI is skilled in Eclipse, Visual Studio, Telend ETL (BI), and SQL-Server. He also has expertise in working with databases like MySQL, Oracle, SQL Lite, Firebase, and SQL-Server. Additionally, Mr. MZILI is knowledgeable in analysis and design methods such as Merise and UML, and he has experience in mobile programming with React Native.

Publications:

  1. A novel discrete bat algorithm for solving the travelling salesman problem
    • Y Saji, ME Riffi
    • Neural Computing and Applications, 27, 1853-1866, 2016, 117 citations
  2. Cat swarm optimization for solving the open shop scheduling problem
    • A Bouzidi, ME Riffi, M Barkatou
    • Journal of Industrial Engineering International, 15 (2), 367-378, 2019, 38 citations
  3. Incorporating a modified uniform crossover and 2-exchange neighborhood mechanism in a discrete bat algorithm to solve the quadratic assignment problem
    • ME Riffi, Y Saji, M Barkatou
    • Egyptian Informatics Journal, 18 (3), 221-232, 2017, 36 citations
  4. Cat swarm optimization to solve job shop scheduling problem
    • A Bouzidi, ME Riffi
    • 2014 Third IEEE International Colloquium in Information Science and Technology, 35, 2014
  5. Discrete cat swarm optimization to resolve the traveling salesman problem
    • A Bouzidi, ME Riffi
    • International Journal, 3 (9), 33, 2013
  6. Discrete bat-inspired algorithm for travelling salesman problem
    • Y Saji, ME Riffi, B Ahiod
    • 2014 Second World Conference on Complex Systems (WCCS), 28-31, 2014
  7. ADAPTATION OF THE HARMONY SEARCH ALGORITHM TO SOLVE THE TRAVELLING SALESMAN PROBLEM
    • M Bouzidi, ME Riffi
    • Journal of Theoretical & Applied Information Technology, 62 (1), 30, 2014
  8. A novel discrete Rat swarm optimization (DRSO) algorithm for solving the traveling salesman problem
    • T Mzili, ME Riffi, I Mzili, G Dhiman
    • Decision making: applications in management and engineering, 5 (2), 287-299, 2022, 20 citations
  9. Discrete cuttlefish optimization algorithm to solve the travelling salesman problem
    • ME Riffi, M Bouzidi
    • 2015 Third World Conference on Complex Systems (WCCS), 1-6, 2015, 18 citations
  10. Discrete swallow swarm optimization algorithm for travelling salesman problem
    • S Bouzidi, ME Riffi
    • Proceedings of the 2017 International Conference on Smart Digital Systems, 17, 2017