![](https://www.epfl.ch/labs/lo/wp-content/uploads/2023/06/IMG_9184.jpeg) | “Deep Learning for Imaging course winners for best project performance” Sven Becker, Ekrem Yüksel, Enes Demirtas, Ilker Oguz, Demetri Psaltis |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2023/01/Unknown-2.jpeg) | Physics-informed neural networks for diffraction tomography
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2022/12/4916235724571913286_121.jpg) | Photo with Professor Tegin and his wife in Boston! |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2022/09/image4.jpeg) | Ahmed becomes Dr. Ahmed ! |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2022/02/Ahmed.jpeg) | Congratulations to Ahmed who passed his private defense. |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2022/01/Scheme.png)
| MaxwellNet: Physics-driven deep neural network training based on Maxwell’s equations
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2021/09/job.png) | New job oportunity : Open Positions |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2021/09/Image_09.2021.png) | “High-speed, complex wavefront shaping using the digital micro-mirror device” |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2021/09/IMG_7102-1.jpeg) | Giulia becomes Dr. Panusa! |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2021/08/LRW3_v2.jpg) | “Optical computing article published in Nature Computational Science” |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2021/08/IMG_20210817_161958-1.jpeg) | Ugur becomes Dr. Tegin! |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2021/07/Ugur.jpg)
| Congratulations to Ugur who passed his private defense. |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2021/07/Giulia.jpeg)
| Congratulations to Giulia who passed her private defense. |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2021/05/RNN-Fig2.png)
| LO researchers demonstrated a recurrent neural network can learn complex spatiotemporal nonlinear propagation and can replace time-consuming, heavy simulations” |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2021/07/Electrolyte.jpg)
| “The porous wall electrolyzer utilizes two porous walls between nucleation sites that improves product separation” |
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![](https://www.epfl.ch/labs/lo/wp-content/uploads/2021/05/Kyriakos.png)
| “Learning to predict optical transmission from reflected light in single and multiple scattering regimes by using neural networks” |