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Wesley De Neve is an Associate Professor working at both the Internet Technology and Data Science Lab (IDLab) at Ghent University in Belgium and the Center for Biotech Data Science at the Ghent University Global Campus (GUGC) in Korea. His academic career spans computer science and biotech data science, with significant contributions to machine learning and multimedia analysis.
Dr. De Neve received his M.Sc. in Computer Science (2002) and Ph.D. in Computer Science Engineering (2007) from Ghent University, Belgium.
His research focuses on developing novel compression and machine learning approaches for analyzing multimedia content (text and video) and biotech data (omics data and medical images). His work bridges computer science with biological applications, particularly in genomic data analysis and medical imaging. He has made significant contributions to splice site prediction, translation initiation site prediction, and hashtag recommendation systems.
An analysis of his recent publications (2023-2025) shows a strong focus on applying deep learning to medical imaging and genomic data analysis. His work increasingly incorporates vision transformers, diffusion models, and multimodal approaches to solve problems in healthcare AI, particularly in surgical video analysis, cancer screening, and protein structure prediction. There's a clear trend toward developing more interpretable models for medical applications.
Dr. De Neve is actively involved with the Internet Technology and Data Science Lab (IDLab), where he leads research at the intersection of computer science and biotechnology. His team works on applying advanced machine learning techniques to solve real-world problems in healthcare and multimedia analysis.
