Publications by Demetri Psaltis

Solar Multimodal Transformer: Intraday Solar Irradiance Predictor Using Public Cameras and Time Series

Mario Paolone, Demetri Psaltis, Luisa Lambertini, Christophe Moser, Yanan Niu

Accurate intraday solar irradiance forecasting is crucial for optimizing dispatch planning and electricity trading. For this purpose, we introduce a novel and effective approach that includes three distinguishing components from the literature: 1) the unco ...

IEEE2025

Training hybrid neural networks with multimode optical nonlinearities using digital twins

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç

The ability to train ever-larger neural networks brings artificial intelligence to the forefront of scientific and technical discoveries. However, their exponentially increasing size creates a proportionally greater demand for energy and computational hard ...

Walter de Gruyter GmbH2025

Guided Nonlinear Optics for Information Processing

Demetri Psaltis

This special issue explores the dynamic and rapidly evolving field of optical computing, with a focus on guided nonlinear optics for information processing. Recent years have seen a resurgence of interest in this area [1], fuelled by groundbreaking experim ...

WALTER DE GRUYTER GMBH2025

Focusing Based on Singular Eigenstates in Non-Hermitian Systems

Demetri Psaltis

Wavefront shaping methods by spatial light modulators, have been an invaluable tool for a plethora of applications in photonics of complex media [1]. In fact in a series of ground-breaking experiments, reverse propagation by phase conjugation was used to c ...

IEEE2025

Resource-efficient photonic networks for next-generation AI computing

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç

Current trends in artificial intelligence toward larger models demand a rethinking of both hardware and algorithms. Photonics-based systems offer high-speed, energy-efficient computing units, provided algorithms are designed to exploit photonics' unique st ...

SPRINGERNATURE2025

Meteorological information prediction using images from webcams

Demetri Psaltis, Luisa Lambertini, Christophe Moser

One aspect of the present invention proposes a method of predicting meteorological information by using an artificial deep neural network. The present invention according to one example focuses on image processing, specifically on fusing a plurality of ima ...

2025

Power Control in Non-Hermitian Lattices Through Singular Value Decomposition

Demetri Psaltis

Periodic structures in optics, like gratings or photonic crystals have played a pivotal role in both basic and applied research applications over the decades [1]. As far as, integrated photonics is concerned, another highly relevant optical structure, that ...

IEEE2025

Ptychographic imaging with a fiber endoscope via wavelength scanning

Demetri Psaltis, Christophe Moser

Ptychography has become a popular computational imaging method for microscopy in recent years. In the present work we employ a wavelength scanning ptychography technique enhanced by neural networks for imaging with a fiber endoscope. Illumination of the ob ...

2024

Subwavelength imaging using a solid-immersion diffractive optical processor

Demetri Psaltis, Carlo Gigli, Niyazi Ulas Dinç

Phase imaging is widely used in biomedical imaging, sensing, and material characterization, among other fields. However, direct imaging of phase objects with subwavelength resolution remains a challenge. Here, we demonstrate subwavelength imaging of phase ...

Springernature2024

An actor-model framework for visual sensory encoding

Demetri Psaltis, Christophe Moser, Babak Rahmani, Diego Ghezzi

A fundamental challenge in neuroengineering is determining a proper artificial input to a sensory system that yields the desired perception. In neuroprosthetics, this process is known as artificial sensory encoding, and it holds a crucial role in prostheti ...

Nature Portfolio2024

Nonlinear processing with linear optics

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç

Deep neural networks have achieved remarkable breakthroughs by leveraging multiple layers of data processing to extract hidden representations, albeit at the cost of large electronic computing power. To enhance energy efficiency and speed, the optical impl ...

Nature Publishing Group2024

Volume holograms with linear diffraction efficiency relation by (3+1)D printing

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç

We demonstrate the fabrication of volume holograms using two-photon polymerization with dynamic control of light exposure. We refer to our method as (3 + 1)D printing. Volume holograms that are recorded by interfering reference and signal beams have a diff ...

Optica Publishing Group2024

Computational segmentation of nuclei and vacuoles based on statistical inference for tomographic phase microscopy in flow cytometry

Demetri Psaltis, Joowon Lim

Identifying intracellular organelles within the 3D label-free tomograms of cells’ refractive indexes recorded in flow cytometry is challenging. Here we present a method for the 3D statistical segmentation of nuclei and vacuoles in flowing cells. ...

Optical Society of America2024

On the implementation of nonlinearities in optical neural networks: opinion

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç

Optical neural networks are expected to be hybrid systems for the foreseeable future combining optics and electronics. The linear portion of the system, consisting of the weighted interconnections between the neurons, can be realized optically. The nonline ...

Optica Publishing Group2024

Optical data processing using structural non-linearity

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç

A device (1) and method for processing data comprises at least one input layer (2), at least one modulation layer (3), and at least one output layer (4). The input layer (2) is configured to receive at least one carrier signal (Sc). The modulation layer (3 ...

2024

Programming nonlinear propagation for efficient optical learning machines

Demetri Psaltis, Christophe Moser, Carlo Gigli, Niyazi Ulas Dinç, Ugur Tegin

The ever-increasing demand for training and inferring with larger machine-learning models requires more efficient hardware solutions due to limitations such as power dissipation and scalability. Optics is a promising contender for providing lower power com ...

Spie-Soc Photo-Optical Instrumentation Engineers2024

Programming the scalable optical learning operator with spatial-spectral optimization

Demetri Psaltis, Christophe Moser, Carlo Gigli, Niyazi Ulas Dinç, Yi Zhou Ju

Electronic computers have evolved drastically over the past years with an ever-growing demand for improved performance. However, the transfer of information from memory and high energy consumption have emerged as issues that require solutions. Optical tech ...

2024

Intraday solar irradiance forecasting using public cameras

Mario Paolone, Demetri Psaltis, Luisa Lambertini, Christophe Moser

With the significant increase in photovoltaic (PV) electricity generation, more attention has been given to PV power forecasting. Indeed, accurate forecasting allows power grid operators to better schedule and dispatch their assets, such as energy storage ...

Pergamon-Elsevier Science Ltd2024

High temperature electrolysis system and method

Demetri Psaltis, Steven Alexandre Schenk, Pooria Hadikhani

The present invention concerns an electrolysis system for high temperature electrolysis including a plurality of flow-based electrolysis units configured to receive an electrolyte solution and to perform electrolysis to provide a first output gas and a sec ...

2023

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