I am a senior data scientist at Swiss Data Science Center (SDSC) hub at Paul Scherrer Institute (PSI). My research focuses on machine learning for scientific discovery and healthcare, with particular emphasis on deep learning for computational imaging and inverse problems, generative AI, and foundation models for science and medicine.
Biography
Amir received his PhD in Computer Science from the University of Basel in 2024. During his doctoral studies, he was awarded a prestigious grant to spend nine months as a visiting researcher at University College London (UCL), where he focused on cosmological imaging problems.
Selected publications
A full list of publications can be found in Amir's google scholar.
[1] AmirEhsan Khorashadizadeh, Tobias Liaudat, Tianlin Liu, Jason McEwen and Ivan Dokmanić.
‘LoFi: Neural Local Fields for Scalable Image Reconstruction.’ IEEE Transactions on Computational
Imaging 2025.
[2] AmirEhsan Khorashadizadeh, Valentin Debarnot, Tianlin Liu and Ivan Dokmanić. ‘GLIMPSE:
Generalized Local Imaging with MLPs.’ IEEE Transactions on Medical Imaging 2025.
[3] AmirEhsan Khorashadizadeh, Anadi Chaman, Valentin Debarnot and Ivan Dokmanić.
'FunkNN: Neural Interpolation for Functional Generation.' International Conference on Learning Representations (ICLR 2023).
[4] AmirEhsan Khorashadizadeh, Vahid Khorashadizadeh, Sepehr Eskandari , Guy A. E. Vandenbosch and Ivan Dokmanić.
'Deep Injective Prior for Inverse Scattering.' IEEE Transactions on Antennas and Propagation 2023.
[5] AmirEhsan Khorashadizadeh, Konik Kothari, Leonardo Salsi, Ali Aghababaeiharandi, Maarten V. de Hoop and Ivan Dokmanić. 'Conditional Injective Flows for Bayesian Imaging.' IEEE Transactions on Computational Imaging 2023.
[6] Kothari, Konik, AmirEhsan Khorashadizadeh, Maarten de Hoop, and Ivan Dokmanić. 'Trumpets: Injective flows for inference and inverse problems.' Uncertainty in Artificial Intelligence (UAI 2021).