Soodeh Hosseini | Machine Learning | Research Excellence Award

Prof. Dr. Soodeh Hosseini | Machine Learning | Research Excellence Award

Corresponding Author | Shahid Bahonar University of Kerman | Iran

Dr. Soodeh Hosseini is an Associate Professor of Computer Science at the Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, specializing in artificial intelligence, machine learning, cybersecurity, and complex networks. She holds a bachelor’s degree in Computer Science, a master’s degree in Computer Engineering with a specialization in software, and a doctorate in Computer Engineering with a focus on software engineering. Her professional experience encompasses extensive academic teaching, supervision of advanced research projects, leadership as head of academic and research units, and active involvement in technology growth centers and science parks, alongside advisory and executive roles in scholarly and innovation-driven initiatives. Her scholarly impact is evidenced by 1,426 citations, an h-index of 23, and an i10-index of 34.

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Featured Publications

A hybrid sine–cosine and golden ratio optimization algorithm for feature selection in intrusion detection systems
M. Maazalahi, S. Hosseini – International Journal of System Assurance Engineering and Management

Analytics and measuring the vulnerability of communities for complex network security
M. Jouyban, S. Hosseini – International Journal of Data Science and Analytics

An Improved Binary Slime Mold Algorithm for Intrusion Detection Systems
M. Khorashadizade, S. Hosseini, M. Jouyban – Concurrency and Computation: Practice and Experience

Rémi Cogranne | Signal & Image Processing | Research Excellence Award

Dr. Rémi Cogranne | Signal & Image Processing | Research Excellence Award

Troyes University of Technology | France

Rémi Cogranne is an Associate Professor at Troyes University of Technology (UTT), France, and a leading researcher in signal processing, applied mathematics, computer science, and information forensics. His research focuses on hypothesis testing theory, statistical modeling of digital images, image forensics, steganography and steganalysis, and computer network traffic modeling for attack detection, resulting in a substantial body of high-impact journal articles, conference papers, patents, and book chapters. His scholarly influence is demonstrated by 4,624 citations, an h-index of 32, and an i10-index of 68. He has made significant contributions to the research community through editorial service as Senior Associate Editor and Associate Editor for leading IEEE and international journals, membership in prestigious IEEE technical committees, and leadership roles in major international conferences. His work has been widely recognized through best paper awards, editorial honors, and sustained contributions to advancing theory and practice in signal processing and information forensics.

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Featured Publications

Content-adaptive steganography by minimizing statistical detectability
V. Sedighi, R. Cogranne, J. Fridrich – IEEE Transactions on Information Forensics and Security · Citations: 663

Selection-Channel-Aware Rich Model for Steganalysis of Digital Images
T. Denemark, V. Sedighi, V. Holub, R. Cogranne, J. Fridrich – IEEE WIFS · Citations: 469

Moving steganography and steganalysis from the laboratory into the real world
A. D. Ker et al., including R. Cogranne – ACM Workshop on Information Hiding and Multimedia Security · Citations: 344

Rich Model for Steganalysis of Color Images
M. Goljan, J. Fridrich, R. Cogranne – IEEE WIFS · Citations: 203

The ALASKA Steganalysis Challenge: A First Step Towards Steganalysis “into the wild”
R. Cogranne, É. Giboulot, P. Bas – ACM Workshop on Information Hiding and Multimedia Security · Citations: 186