About
Back to topI am a third-year PhD candidate in the Machine Learning & Perception Group at Friedrich-Alexander-Universität Erlangen-Nürnberg, jointly supervised by Prof. Vasileios Belagiannis, Prof. Gustavo Carneiro, and Prof. Nassir Navab. Before starting the PhD, I completed both the B.Sc. and M.Sc. in Medical Engineering at FAU, where my thesis work was conducted in collaboration with Dalia Rodríguez and Prof. Andreas Maier.
My research interests focus on applied computer vision, particularly in areas such as Monocular Depth Estimation, Domain Adaptation, and Uncertainty Estimation, leveraging generative techniques.
News
Back to top| Mar 2026🏅 | Our VISAPP paper was selected as a Best Paper Award Candidate. |
| Feb 2026🎉 | One CVPR (Findings) paper on prompt-guided image editing with VAR models accepted for publication. |
| Nov 2025🎉 | VISAPP paper on depth estimation with VAR models accepted for publication. |
| Feb 2025🎉 | TPAMI paper on gradient-based uncertainty for monocular depth estimation accepted for publication. |
| Jun 2024🎉 | CoLLAs paper on consistency regularisation for unsupervised domain adaptation in monocular depth estimation accepted for publication. |
Selected Publications
Back to topWork on uncertainty estimation, domain adaptation, depth estimation and medical imaging.
Teaching
Back to topCurrent
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MLISP: Machine Learning in Signal Processing
Exercises in fundamentals of machine learning with programming assignments in Python.
Past
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ATDL: Advanced Topics in Deep Learning
Foundational overview of advanced AI concepts and applications with weekly programming assignments in Python.
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SemML: Seminar on Selected Topics in Machine Learning
Students present scientific publications from the literature on machine learning and deep learning.
Contact
Back to topFor general inquiries, please use the contact details below.
- amir.el-ghoussani@fau.de
- Office
- Room 06.036, Cauerstr. 7, FAU Erlangen-Nürnberg
Collaborations
I welcome industry and academic partners interested in applied generative computer vision (such as diffusion models or visual autoregressive models), Monoculardepth estimation, and uncertainty modeling. Drop me a mail here
Prospective Students
For theses or research projects with our group, please prepare the following materials:
- Most recent academic transcript (unofficial copies are fine for the initial review).
- If your program is outside the Department of EEI, include an official confirmation from your program advisors that our group may supervise your thesis or project.
Due to the high volume of applications, we may be unable to respond to every inquiry individually, but we appreciate your interest.
Send your materials here and indicate whether you want to apply for a thesis or a research project in the subject.