@@ -10,7 +10,7 @@ last_name: Maroun
 superuser: false
 
 # Role/position
-role: PhD Student
+role: Former PhD Student
 
 # Organizations/Affiliations
 organizations:
@@ -63,12 +63,12 @@ highlight_name: true
 
 # Organizational groups that you belong to (for People widget)
 user_groups:
-  - PhD Students
+  - Alumni
 ---
 
-**Gaby Maroun** is a PhD student at the University of the Basque Country, affiliated with the Computer Vision and Pattern Discovery (CVPD) research group. He is currently pursuing a PhD under the supervision of [Dr. Fadi Dornaika](https://cvpd.github.io/author/fadi-dornaika/) and [Dr. Salah El Dine Bekhouche](https://cvpd.github.io/author/salah-el-dine-bekhouche/), with a focus on generalizable deep learning methods, particularly hybrid architectures combining ConvNeXt and Transformers. He is expected to defend his thesis by the end of 2026. Gaby earned an MSc in Big Data (2021) from the University of Pau and the Adour Region (UPPA), France, and a BSc in Computer Science (2018) from the Lebanese University – Faculty of Sciences in Tripoli, Lebanon.
+**Gaby Maroun** was a PhD student at the University of the Basque Country, affiliated with the Computer Vision and Pattern Discovery (CVPD) research group. He pursued his PhD under the supervision of [Dr. Fadi Dornaika](https://cvpd.github.io/author/fadi-dornaika/) and [Dr. Salah El Dine Bekhouche](https://cvpd.github.io/author/salah-el-dine-bekhouche/), with a focus on generalizable deep learning methods, particularly hybrid architectures combining ConvNeXt and Transformers. Gaby earned an MSc in Big Data (2021) from the University of Pau and the Adour Region (UPPA), France, and a BSc in Computer Science (2018) from the Lebanese University – Faculty of Sciences in Tripoli, Lebanon.
 
-During his PhD, Gaby’s research has focused on building annotation-efficient, generalizable models for tasks such as **medical image segmentation** and **face age estimation**. His work emphasizes hybrid deep learning architectures, leveraging the strengths of convolutional and transformer-based models to improve performance in low-data regimes. He is a co-author of *SegDT: A Diffusion Transformer-Based Segmentation Model for Medical Imaging*, accepted for presentation at MICCAI 2025, which introduces a novel framework combining diffusion models with transformers for enhanced segmentation accuracy on complex medical datasets.
+During his PhD, Gaby’s research focused on building annotation-efficient, generalizable models for tasks such as **medical image segmentation** and **face age estimation**. His work emphasizes hybrid deep learning architectures, leveraging the strengths of convolutional and transformer-based models to improve performance in low-data regimes. He is a co-author of *SegDT: A Diffusion Transformer-Based Segmentation Model for Medical Imaging*, accepted for presentation at MICCAI 2025, which introduces a novel framework combining diffusion models with transformers for enhanced segmentation accuracy on complex medical datasets.
 
 In addition to his academic work, Gaby has led technical and analytical projects in the aerospace industry, managing cross-functional data initiatives and developing robust data pipelines and tools. His professional experience complements his research by grounding theoretical models in real-world systems and large-scale deployments.