Publications by Eirini Kakkava

Improved two-photon polymerization through an optical fiber using coherent beam shaping

Demetri Psaltis, Christophe Moser, Eirini Kakkava, Georgia Konstantinou, Antoine Vincent Boniface

The state of the art for high resolution three-dimensional light-based additive manufacturing mainly relies on two-photon polymerization. It consists of focusing and scanning a femtosecond laser beam on a photosensitive resin to initiate crosslinking and f ...

ELSEVIER SCI LTD2023

Multicore fiber endoscope for phase imaging based on intensity recording using deep neural networks

Demetri Psaltis, Christophe Moser, Navid Borhani, Eirini Kakkava

The present invention is related to an endoscopic system for phase imaging, comprising a multicore waveguide (080), an optical system comprising at least one first light source (002), for illuminating the sample to be examined, a first camera (010) that is ...

2022

Spatial self-beam cleaning in spatiotemporally mode-locked fiber lasers

Demetri Psaltis, Christophe Moser, Eirini Kakkava, Babak Rahmani, Ugur Tegin

IEEE2021

Full characterization of partially measured systems with neural networks

Demetri Psaltis, Christophe Moser, Navid Borhani, Damien Claude-Marie Loterie, Eirini Kakkava, Babak Rahmani, Ugur Tegin

IEEE2021

Learning to See and Compute through Multimode Fibers

Demetri Psaltis, Christophe Moser, Navid Borhani, Damien Claude-Marie Loterie, Eirini Kakkava, Babak Rahmani, Ugur Tegin

We propose a computational method for controlling the output of a multimode fiber using machine learning. Arbitrary images can be projected with amplitude-only calibration (no phase measurement) and fidelities on par with conventional full-measurement meth ...

IEEE2021

High-resolution microfabrication through a graded-index multimode optical fiber

Demetri Psaltis, Christophe Moser, Damien Claude-Marie Loterie, Eirini Kakkava, Georgia Konstantinou

IEEE2021

Predicting optical transmission through complex scattering media from reflection patterns with deep neural networks

Demetri Psaltis, Eirini Kakkava

Deep neural networks (DNNs) are used to reconstruct transmission speckle intensity patterns from the respective reflection speckle intensity patterns generated by illuminated parafilm layers. The dependence of the reconstruction accuracy on the thickness o ...

2021

Deep Learning-Based Image Classification through a Multimode Fiber in the Presence of Wavelength Drift

Demetri Psaltis, Christophe Moser, Navid Borhani, Eirini Kakkava, Babak Rahmani, Ugur Tegin

Deep neural networks (DNNs) are employed to recover information after its propagation through a multimode fiber (MMF) in the presence of wavelength drift. The intensity distribution of the speckle patterns generated at the output of an MMF when an input wa ...

2020

Computer generated optical volume elements by additive manufacturing

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç, Eirini Kakkava, Joowon Lim

Computer generated optical volume elements have been investigated for information storage, spectral filtering, and imaging applications. Advancements in additive manufacturing (3D printing) allow the fabrication of multilayered diffractive volume elements ...

2020

Controlling spatiotemporal nonlinearities in multimode fibers with deep neural networks

Demetri Psaltis, Christophe Moser, Navid Borhani, Eirini Kakkava, Babak Rahmani, Ugur Tegin

Spatiotemporal nonlinear interactions in multimode fibers are of interest for beam shaping and frequency conversion by exploiting the nonlinear interaction of different pump modes from quasi-continuous wave to ultrashort pulses centered around visible to i ...

2020