Plenary Event
Hot Topics I
13 April 2026 • 08:45 - 11:00 CEST | Auditorium Erasme (Niveau/Level 0)
8:45 – 8:50 hrs
Welcome Address
8:50 – 8:55 hrs
Univ. of Strasbourg Welcome
8:55 – 9:05 hrs
Extra/Ordinary Light: Invitation to Art Exhibition
Paul Montgomery
Univ. of Strasbourg (France)
2026 Symposium Chair
9:05 - 9:10 hrs
City of Strasbourg Welcome
9:10 - 9:15 hrs
Presentation of the 2025 SPIE María J. Yzuel Educator Award
to
for a lifelong dedication to teaching optics and photonics with infectious passion, and a lifelong dedication to the SPIE community
SPIE New Fellows Announcement
9:15 - 9:20 hrs
Introduction to Hot Topics
Paul Montgomery
Univ. of Strasbourg (France)
2026 Symposium Chair
9:20 - 10:05 hrs CEST
Photonics and A(G)I innovations will enable industry 5.0 & 6.0 in the agrifood sector
Climate change is one of the greatest and most urgent challenges of our time. If we want to keep the planet livable, greenhouse gas emissions must be net zero by 2050. Food production is responsible for up to a staggering 34% of greenhouse gas emissions. At the same time, our food production is highly sensitive to climate change and this is already having a major impact on the food system, such as crop failures due to extreme weather conditions. As a result, food security and food sustainability are top of mind. Technology can and will make the difference. The unprecedented convergence of AI, gene editing, DNA synthesis and biotechnology will revolutionize global industry, particularly in the agrifood domain.
This presentation will show how optical sensing in general and photonic integrated circuits in particular are unique and indispensable technologies that provide solutions for farmers, food processing industry and consumers, and will help guide the transition of our food ecosystem to a more secure and sustainable industry. New tools in barns, in greenhouses, in orchards, in protein bioreactors and the accompanying digital twin AI technology will be shown.
Chris van Hoof is Vice President R&D at imec, general manager of the One Planet Research Center, and professor at KULeuven. After his PhD in Electrical Engineering from the University of Leuven in 1992, and throughout his career at imec since 1987, Chris created innovations at technology, system, and application level, ranging from deployment in space to implantable or ingestible medical devices and sensors used in the barn and the orchard. His work led to 5 startups, 4 in the healthcare domain. The solutions that are being created at OnePlanet rely on imec chip and digital technology innovations and on domain know-how from Wageningen University and Research, and Radboud University and Radboud Medical Center. The interdisciplinary OnePlanet Research Center currently has approximately 100 researchers with a mission to create a society where everyone can live healthy lives and have access to sustainable food.
10:10 - 10:55 hrs CEST
Failing forward in deep spectral imaging
Spectral imaging has long promised to uncover physiological and molecular information invisible to the human eye. Yet, despite decades of innovation, its translation into clinical routine has been slow. Beyond regulatory hurdles, challenges such as ill-posed inverse problems, data scarcity, and the demand for real-time analysis have repeatedly stalled progress.
In this keynote, I will present recent breakthroughs at the intersection of computational biophotonics and machine learning that are reshaping the field. I will discuss how we combine spectral imaging with deep learning to achieve real-time tissue characterization in surgery and intensive care. Case studies will illustrate how spectral imaging can enable context-sensitive, clinically actionable support during interventions, transforming invisible spectral signatures into robust biomarkers.
I will highlight not only our successes but also the failures that have shaped them. From spectral unmixing approaches that collapsed under distribution shifts to algorithms that failed spectacularly in the operating room, I will show how negative results became the foundation for new strategies. By dissecting what went wrong, we discovered how to adapt models across species and sensors, quantify uncertainty in predictions, and build validation frameworks that hold up under clinical reality.
By putting the spotlight on failure—and how it fuels methodological innovation—I will argue that embracing negative results is the key to moving spectral imaging, powered by AI, from promise to practice. The future of the field may not depend on avoiding failure, but on failing better.
Lena Maier-Hein is a full professor at Heidelberg University (Germany) and division head at the German Cancer Research Center (DKFZ). She is managing director of the National Center for Tumor Diseases (NCT) Heidelberg and of the DKFZ Data Science and Digital Oncology cross-topic program. Her research concentrates on machine learning-based biomedical image analysis with a specific focus on surgical data science, computational biophotonics and validation of machine learning algorithms.
Welcome Address
 |
Paul Montgomery
Univ. of Strasbourg (France) 2026 Symposium Chair |
8:50 – 8:55 hrs
Univ. of Strasbourg Welcome
 |
Michel de Mathelin
Univ. of Strasbourg (France) Vice President for Strategy and Innovation |
8:55 – 9:05 hrs
Extra/Ordinary Light: Invitation to Art Exhibition
Paul Montgomery
Univ. of Strasbourg (France)
2026 Symposium Chair
9:05 - 9:10 hrs
City of Strasbourg Welcome
9:10 - 9:15 hrs
Presentation of the 2025 SPIE María J. Yzuel Educator Award
to
 |
Dan Curticapean
Offenburg Univ. (Germany) |
for a lifelong dedication to teaching optics and photonics with infectious passion, and a lifelong dedication to the SPIE community
SPIE New Fellows Announcement
9:15 - 9:20 hrs
Introduction to Hot Topics
Paul Montgomery
Univ. of Strasbourg (France)
2026 Symposium Chair
9:20 - 10:05 hrs CEST
Photonics and A(G)I innovations will enable industry 5.0 & 6.0 in the agrifood sector
 |
Chris van Hoof
Imec (Belgium) OnePlanet Research Ctr. (Belgium) |
Climate change is one of the greatest and most urgent challenges of our time. If we want to keep the planet livable, greenhouse gas emissions must be net zero by 2050. Food production is responsible for up to a staggering 34% of greenhouse gas emissions. At the same time, our food production is highly sensitive to climate change and this is already having a major impact on the food system, such as crop failures due to extreme weather conditions. As a result, food security and food sustainability are top of mind. Technology can and will make the difference. The unprecedented convergence of AI, gene editing, DNA synthesis and biotechnology will revolutionize global industry, particularly in the agrifood domain.
This presentation will show how optical sensing in general and photonic integrated circuits in particular are unique and indispensable technologies that provide solutions for farmers, food processing industry and consumers, and will help guide the transition of our food ecosystem to a more secure and sustainable industry. New tools in barns, in greenhouses, in orchards, in protein bioreactors and the accompanying digital twin AI technology will be shown.
Chris van Hoof is Vice President R&D at imec, general manager of the One Planet Research Center, and professor at KULeuven. After his PhD in Electrical Engineering from the University of Leuven in 1992, and throughout his career at imec since 1987, Chris created innovations at technology, system, and application level, ranging from deployment in space to implantable or ingestible medical devices and sensors used in the barn and the orchard. His work led to 5 startups, 4 in the healthcare domain. The solutions that are being created at OnePlanet rely on imec chip and digital technology innovations and on domain know-how from Wageningen University and Research, and Radboud University and Radboud Medical Center. The interdisciplinary OnePlanet Research Center currently has approximately 100 researchers with a mission to create a society where everyone can live healthy lives and have access to sustainable food.
10:10 - 10:55 hrs CEST
Failing forward in deep spectral imaging
 |
Lena Maier-Hein
German Cancer Research Ctr. (DKFZ) (Germany) Heidelberg Univ. (Germany) |
Spectral imaging has long promised to uncover physiological and molecular information invisible to the human eye. Yet, despite decades of innovation, its translation into clinical routine has been slow. Beyond regulatory hurdles, challenges such as ill-posed inverse problems, data scarcity, and the demand for real-time analysis have repeatedly stalled progress.
In this keynote, I will present recent breakthroughs at the intersection of computational biophotonics and machine learning that are reshaping the field. I will discuss how we combine spectral imaging with deep learning to achieve real-time tissue characterization in surgery and intensive care. Case studies will illustrate how spectral imaging can enable context-sensitive, clinically actionable support during interventions, transforming invisible spectral signatures into robust biomarkers.
I will highlight not only our successes but also the failures that have shaped them. From spectral unmixing approaches that collapsed under distribution shifts to algorithms that failed spectacularly in the operating room, I will show how negative results became the foundation for new strategies. By dissecting what went wrong, we discovered how to adapt models across species and sensors, quantify uncertainty in predictions, and build validation frameworks that hold up under clinical reality.
By putting the spotlight on failure—and how it fuels methodological innovation—I will argue that embracing negative results is the key to moving spectral imaging, powered by AI, from promise to practice. The future of the field may not depend on avoiding failure, but on failing better.
Lena Maier-Hein is a full professor at Heidelberg University (Germany) and division head at the German Cancer Research Center (DKFZ). She is managing director of the National Center for Tumor Diseases (NCT) Heidelberg and of the DKFZ Data Science and Digital Oncology cross-topic program. Her research concentrates on machine learning-based biomedical image analysis with a specific focus on surgical data science, computational biophotonics and validation of machine learning algorithms.