Daniel HISSEL awarded as « Fellow » of the IEEE society

Professor in Electrical Engineering at the University of Franche-Comté and researcher at FEMTO-ST, Daniel Hissel has been awarded as for his work on hydrogen systems.

Daniel Hissel was director of the CNRS FCLAB federation from 2012 to 2019, he is currently Vice President in charge of the socio-economic partnership and innovation at the University of Franche-Comté, head of the SHARPAC team (Hybrid Electric Systems, Electric Actuators, Fuel Cell Systems) at the FEMTO-ST institute, deputy director of the FRH2 hydrogen federation and co-founder of the H2SYS start-up. He was awarded the Blondel Medal in 2017, the CNRS Medal for Innovation in 2020 and "Fellow" of the Institute of Electrical & Electronics Engineers in 2022.

Daniel Hissel is one of the pioneers of the international research on the diagnosis and prognosis of hydrogen-energy systems both for embedded and stationary applications. For more than 20 years now, he has orchestrated the activities of many researchers in the team, particularly in the field of Artificial Intelligence (AI) for effective and non-invasive estimation of the state of health and control of systems integrating a fuel cell.

New platform to support the design and optimization of fuel cell hybride system and battery
Virtual FCS" is the first freely accessible online simulation platform to support fuel cell manufacturers and users.

Supported by a European funding, "Virtual FCS" has for French partner the University of Bourgogne-Franche-Comté through the FEMTO-ST institute and the FC-LAB
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ThermoBot : micro robots that walk on water
Imagine, a robot, the size of a fly, walking on the surface of the water and pursued by a laser beam. One could believe in a science fiction scenario...
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Recognizing liars from the sound of their voice ?
Scientists have prouved that the intensity, speed and pitch of the speaker's voice automatically influences our perception of the reliability and honesty of his or her speech. This work is published in the prestigious journal "Nature Communications"
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European project for the development of sustainable and high-performance bio-based composites
Led by FEMTO-ST and supported by the University of Franche-Comté, the « SSUCHY » R&D project which brings together 17 European partners is entering its final phase. The project is now quite advanced.
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Understanding the cytotoxicity of metallic nanoparticles
A recent study published in the journal "Chemical Science" and involving FEMTO-ST gives new insights into the understanding of the mechanisms of DNA alteration in cells by metallic nanoparticles.
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Artificial intelligence for next-generation ultrafast photonics
How can machine learning and associated methods improve the development of next-generation laser sources and revolutionize applications where ultrafast light plays a central role?
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Strong involvement of FEMTO-ST in the H2020 project "PhotonHub Europe"
The objective of this project is to help European SMEs to increase their competitiveness through photonics with a online guidance, which will offer the support of 54 leading competence centers in Europe, including FEMTO-ST, which is also the scientific coordinator at the national level.
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First demonstration of self-confined nonlinear waves in plasmonic structures
By providing the very first experimental evidence of the existence of this phenomenon, FEMTO-ST researchers and their partners hope to be able to generate this nonlinear effect using low intensity laser sources, in order to use it for nanophotonics applications.
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Mengjia Wang receives the « Chinese government award 2020 »
As a PhD student of the Optics Department of FEMTO-ST , Mengjia Wang has been recognized by the Chinese Government for his outstanding work in the field of nanophotonics and plasmonics.
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Laurent LARGER named Fellow 2021 of OSA
Full professor of Physics/Optics at the University of Franche-Comté and researcher at FEMTO-ST institute, Laurent Larger is rewarded for his pioneering work on nonlinear dynamics in optoelectronics and on the development of new architectures for photonic artificial intelligence.
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