Editor in Chief
Professor Jean-Christophe Olivo-Marin: Institut Pasteur, France
Jean-Christophe Olivo-Marin is the Head of the BioImage Analysis Unit at Institut Pasteur and the Director of the Institut Carnot Pasteur Microbes et Santé. He received the Ph.D. and H.D.R. degrees in optics and signal processing from Institut d’Optique Théorique et Appliquée, University of Paris-Orsay, France. He chaired the Cell Biology and Infection Department (2010-2014) and was CTO and Director of the Centre for Innovation and Technological Research (2015-2018) at Institut Pasteur, and the founder CTO of Institut Pasteur Korea (2004-2005). He was at the European Molecular Biology Laboratory, Heidelberg, from 1990 to 1998. He is a Fellow of IEEE, SPIE and Optica, and an IEEE Signal Processing Society and IEEE Engineering in Medicine and Biology Society Distinguished Lecturer. His research interests are in bioimage informatics, ML and mathematical approaches of biological imaging, with application topics in mechanobiology of cellular dynamics and computational pathology. He is the founding Editor-in-Chief of the journal Biological Imaging published by Cambridge University Press.
Executive Editors
Professor Elsa Angelini: Telecom Paris, France & Imperial College London, UK
Elsa D. Angelini is a Professor in Biomedical Image Computing & Machine Learning at Telecom Paris, engineering school part of the Institut Polytechnique de Paris and the Institut Mines Telecom, in France. She holds joint affiliations with Columbia University (USA) and Imperial College London (UK). She is a senior member of IEEE. She has co-authored over 140 publications in the field of bio and medical image analysis. She was the general chair of the IEEE ISBI'15 conference, and co-chair (2016-19) of the SPIE Medical-Imaging sub-Conference on Image Processing. Her research interests focus on image computing for biomedical modalities, focusing on smart encoding of image information and machine-learning on images, electronic health records, and omics data for patient stratification, prognosis, disease scoring and subtyping.
Professor Jong Chul Ye: KAIST, South Korea
Jong Chul Ye is a Professor of the Kim Jaechul Graduate School of Artificial Intelligence (AI) of Korea Advanced Institute of Science and Technology (KAIST), Korea. He received the B.Sc. and M.Sc. degrees from Seoul National University, Korea, and the Ph.D. from Purdue University, West Lafayette. Before joining KAIST, he worked at Philips Research and GE Global Research in New York. He has served as an associate editor of IEEE Trans. on Image Processing, and an editorial board member for Magnetic Resonance in Medicine. He is currently an associate editor for IEEE Trans. on Medical Imaging, and a Senior Editor of IEEE Signal Processing Magazine. He is an IEEE Fellow, was the Chair of IEEE SPS Computational Imaging TC, and IEEE EMBS Distinguished Lecturer. He was a General Cochair (with Mathews Jacob) for IEEE Symp. On Biomedical Imaging (ISBI) 2020. His research interest is in machine learning for biomedical imaging and computer vision.
Professor Arrate Muñoz Barrutia: Universidad Carlos III, Spain
Professor Chrysanthe Preza: University of Memphis, USA
Chrysanthe Preza is the Kanuri Professor and Chair in the Department of Electrical and Computer Engineering at the University of Memphis, where she joined 2006. She received her D.Sc. degree in Electrical Engineering from Washington University in St. Louis in 1998. She leads the research in the Computational Imaging Research Laboratory at the University of Memphis. Her research interests are imaging science, estimation theory, computational imaging enabled by deep learning, and computational optical sensing and imaging applied to multidimensional multimodal light microscopy and hyperspectral imaging. She received a CAREER award by the National Science Foundation in 2009, the Herff Outstanding Faculty Research Award in 2010 and 2015, and she was the recipient of the Ralph Faudree Professorship at the University of Memphis 2015-2018. She was named Fellow of the SPIE in 2019 and Fellow of Optica (OSA) in 2020. She serves as Associate Editor for IEEE Transactions on Computational Imaging and as Executive Editor for Biological Imaging, Cambridge University Press.
Professor Ge Yang: Chinese Academy of Sciences, China
Professor Ge Yang is a professor of computational biology at the Institute of Automation of the Chinese Academy of Sciences and the School of Artificial Intelligence of the University of Chinese Academy of Sciences. He received his Ph.D. degree in mechanical engineering (robotics) from the University of Minnesota Twin Cities in Minneapolis-Saint Paul, Minnesota, USA, in 2004. From 2004 to 2008, he completed his postdoctoral training in computational cell biology at the Scripps Research Institute in La Jolla, California, USA. From 2009 to 2018 he was an assistant professor then an associate professor of computational biology and biomedical engineering at Carnegie Mellon University in Pittsburgh, Pennsylvania, USA. Since 2019 he has been a full professor at the State Key Laboratory for Multimodal Artificial Intelligence Systems and the National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences and the School of Artificial Intelligence, the University of Chinese Academy of Sciences. His main research interests are in computational biology and artificial intelligence. His research mainly focuses on developing deep learning-based computational methods for analyzing biological microscopy images and on using these methods for understanding the molecular and systems mechanisms of basic cellular processes, especially dynamic organization of intracellular organelle networks, and for AI-based drug discovery. He is the recipient of several honors and awards, including a US National Science Foundation Faculty Early Career Award in 2012 and an Outstanding Teacher Award from the University of Chinese Academy of Sciences in 2020.
Associate Editors
Dr Ed Cohen: Imperial College London, UK
Professor Marc Thilo Figge: Leibniz-HKI, Germany
Professor Marc Thilo Figge is a professor of Applied Systems Biology at the Friedrich Schiller University in Jena, Germany, and is running his research group at the Leibniz Institute for Natural Product Research and Infection Biology. The main focus of his research is on all aspects of image-based systems biology, including (i) the development of the visual programming language JIPipe for the quantitative analysis of bioimage data and (ii) the automated processing of microscopic images and spectroscopy data being accompanied by mathematical modeling and spatiotemporal computer simulations. He is a board member and coordinator of “Bioimage Informatics” in the DFG-funded national research data management initiative “NFDI4Bioimage”; furthermore, he is a board member and principal investigator in the DFG-Research Training School RTG 2723 – “Materials-Microbes-Microenvironments” as well as a coordinator in the BMBF-funded “Leibniz Center for Photonics in Infection Research” and in the DFG-funded Excellence Cluster “Balance of the Microverse” that are both located in Jena.
Dr Auguste Genovesio: ENS Paris, France
Dr Estibaliz Gómez de Mariscal: Instituto Gulbenkian de Ciência, Portugal
Estibaliz Gómez de Mariscal completed her PhD in Mathematical Engineering in 2021 at Universidad Carlos III de Madrid in Spain, where she developed advanced methods for the characterization of cancer cell migration and statistical testing modelling in the context of big data. Currently, she is an EMBO postdoctoral researcher at Instituto Gulbenkian de Ciência in Portugal. Her research focuses on contributing to biological discoveries by exploiting image processing techniques and facing the challenges in the intersection between Artificial Intelligence and live-cell microscopy imaging. She has also contributed actively to the bioimage analysis community within the deepImageJ, ZeroCostDL4Mic, DeepBacs, the Cell Tracking Challenge and the BioImage Model Zoo projects.
Dr Charles Kervrann: Inria Rennes, France
Charles Kervrann, Inria Senior Researcher since 2010, is heading the SAIRPICO Team jointly located in Rennes and Paris since 2023. From 2018-2023, he was head of the SERPICO Team. He received his MSc, PhD and HdR in Signal Processing and Telecommunications from the University of Rennes in 1992, 1995 and 2010, respectively. Prior to his current position, Dr. Kervrann was appointed INRA junior researcher in the Applied Mathematics and Informatics department in 1997. His research interests are in the field of image processing and analysis, machine learning, and inverse problems in cell imaging and light and electron microscopy. Dr. Kervrann has supervised 18 PhD students and 7 postdocs. He is currently Associate Editor of IEEE Transactions of Image Processing and Biological Imaging journals. Previously, he was Associate Editor of IEEE Signal Processing Letters (2015-2019) and member of the IEEE BISP Biomedical Image and Signal Processing committee (2010-2018). He served as Guest editor for one special issue for the IEEE Journal of Selected Topics in Signal Processing in 2016 and for one special issue on Biophotonics for the IEEE Journal of Selected Topics in Quantum Electronics in 2023. He was Co-General Chair and Organizer of the Quantitative BioImaging (QBI’2019) conference in 2019 (Rennes, France).
Professor Michal Kozubek: Masaryk University, Czech Republic
Michal Kozubek is a professor of computer science at the Faculty of Informatics, Masaryk University. He is a head of the Centre for Biomedical Image Analysis (CBIA), and former Dean (2011‑2015). His research focuses on image analysis, especially as applied in biomedicine. Recently he has mainly attended to the benchmarking in biomedical image analysis in general and joined MICCAI Group on Challenges that attends to the quality control of competitions (so-called challenges) in the field. Currently, he mostly attends to the applications of deep learning in biomedical image analysis and has become the director of the Centre for Artificial Intelligence in Oncology. He is a member of Czechoslovak and European Microscopy Societies, IEEE Signal Processing Society and Medical Image Computing and Computer-Assisted Intervention Society.
Dr Thibault Lagache: Institut Pasteur, France
Professor Matthew D. Lew: Washington University Saint-Louis, USA
Professor Matthew D. Lew and his lab build advanced imaging systems to study biological and chemical systems at the nanoscale. Their technology leverages innovations in applied optics, signal and image processing, design optimization, and physical chemistry. Super-resolution is a key feature of many of their imaging systems–the ability to overcome the resolution limit of wave physics, called the diffraction limit, in order to visualize the nanoscale world. Single-molecule imaging is also a central theme–enabling their technology to see individual molecules as they drive biological and chemical dynamics at the nanoscale. Their research spans three areas: 1) Sensing nanoscale environments using single fluorescent molecules; 2) Designing microscopes for optimal multidimensional nanoscale imaging; and 3) Building multidimensional image analysis algorithms that are robust against bias and noise.
Meng Lu: University of Cambridge, UK
Meng Lu is a Senior Research Associate at the Laser Analytics Group and Molecular Neuroscience Group at the University of Cambridge. After earning his PhD in Biotechnology from Cambridge in 2015, he has been focusing on integrating super-resolution imaging, deep learning, and molecular biology to explore the intricacies of intracellular organelles, with a particular emphasis on cell models of neurodegenerative diseases. Dr Lu’s research has led to the creation of cell models that generate protein aggregates, providing critical tools for studying disorders such as Alzheimer's and Huntington's diseases. In addition, Dr Lu has developed computational methods to analyse the structure of organelles in super-resolution microscopy images, allowing for a more precise understanding of cellular mechanisms. One of his contributions is the identification of the lysosome as a driving force behind the structure and distribution of the endoplasmic reticulum, a discovery made possible by a deep-learning tool known as ERnet. Actively promoting the integration of deep learning in bioimaging, Dr Lu continues to develop new avenues for understanding and potentially treating neurodegenerative diseases.
Professor Erik Meijering: University of New South Wales, Australia
Professor Erik Meijering leads the Computer Vision Group in the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney, Australia. He has over 20 years of experience in developing advanced computational methods and tools for efficient and reliable quantitative analysis of biomedical imaging data. These methods are increasingly based on artificial intelligence approaches involving machine and deep learning. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) for his contributions to biological image analysis. Before moving to UNSW, he worked in various engineering institutes and university medical centers across Europe, including Delft University of Technology (as an MSc student) and Utrecht University (as a PhD student) in the Netherlands, the Swiss Federal Institute of Technology in Lausanne (as a Postdoc), and Erasmus University Medical Center in the Netherlands (as an Assistant Professor and later Associate Professor). He is a multidisciplinary scientist-engineer with a passion to translate computer science theories and mathematical concepts into powerful algorithms for the advancement of medicine and biology. Over the years his group has developed innovative solutions for image restoration, super-resolution, registration, object detection, segmentation, quantification, classification, and tracking, and has produced various image analysis software tools used by thousands worldwide. In addition to his academic work, he was/is active internationally as a member of the IEEE Signal Processing Society Technical Committee on Bio Imaging and Signal Processing (BISP, 2005-2010, 2016-2020, Chair 2018-2019), the IEEE Engineering in Medicine and Biology Society Technical Committee on Biomedical Imaging and Image Processing (BIIP, since 2007), and the cross-Society IEEE Life Sciences Technical Community (LSTC, 2018-2020). He was/is an Associate Editor for the IEEE Transactions on Medical Imaging (since 2004), the International Journal on Biomedical Imaging (2006-2009), the IEEE Transactions on Image Processing (2008-2011), and Biological Imaging (since 2020), has co-edited various journal special issues, including for the IEEE Transactions on Image Processing (2005) and the IEEE Signal Processing Magazine (2015, 2022), has co-organized three international benchmarking competitions (Particle Tracking Challenge 2012, Cell Tracking Challenge since 2013, BigNeuron Project since 2015), as well as various conferences in the field, most notably the IEEE International Symposium on Biomedical Imaging (ISBI, especially 2006, 2010, 2018 as Technical Program Chair) and the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2020 as Workshops Chair), and served/serves on a great variety of other conference, advisory, and review boards.
Professor Jens Rittscher: Oxford University, UK
Jens Rittscher is Professor of Engineering Science at the University of Oxford with his appointment held jointly between the Institute of Biomedical Engineering and the Nuffield Department of Medicine. He is a group leader at the Big Data Institute and is affiliated with the Ludwig Institute of Cancer Research and the Wellcome Centre as an adjunct member. Previously, he was a senior research scientist and manager at GE Global Research (Niskyauna, NY, USA). His research interests lie in enabling biomedical imaging through the development of new algorithms and novel computational platforms, with a current focus to improve mechanistic understanding of cancer and patient care through quantitative analysis of image data. He is a co-director of the Oxford EPSRC Centre for Doctoral Training in Health Data Science.
Dr Daniel Sage: EPFL, Switzerland
Dr. Daniel Sage is an expert in computational bioimaging. He currently leads the software development at the Biomedical Imaging Group within the Ecole Polytechnique Fédérale de Lausanne (EPFL). Alongside his role at EPFL, he serves as a lecturer at the EPFL Life Science School, where he teaches the course on Bioimage informatics. With over 25 years of experience, he has extensive expertise in image processing, image analysis, and image reconstruction, primarily focusing on applications in the field of life sciences and microscopy. His main research interests lie in bioimage informatics, specifically in the areas of segmentation, quantification, tracking, directional image analysis, and 3D deconvolution. He is also highly involved in image reconstruction methods for super-resolution microscopy, such as structured illumination microscopy and localization microscopy (SMLM). he organizes the challenges to benchmark SMLM software. He is highly dedicated to bringing the most advanced bioimage tools to end-users, particularly life scientists. In this context, he has recently made significant contributions to the development of zero-code tools for deep learning in various applications of image analysis.
Professor Carlos Oscar Sanchez Sorzano: CNB, Spain
Carlos Óscar Sánchez Sorzano is B.Sc. and M. Sc. Electrical Engineering with two specialities (Electronics and Networking, Univ. Málaga), B. Sc. Computer Science (Univ. Málaga), B.Sc. and M. Sc. in Mathematics, (speciality in Statistics, UNED), Ph.D. in Biomedical Engineering (Univ. Politécnica de Madrid) and Ph. D. in Pharmacy (Univ. San Pablo-CEU). He served as secretary of the Dept. of Engineering of Electronic and Telecommunication Systems of the Univ. CEU-San Pablo (Madrid) between 2005 and 2008, coordinator of the Section on Signal and Communications theory between 2004 and 2009, head of the Bioengineering Laboratory of that University between 2007 and 2008, director of the Summerschool on Advanced Data Analysis and Modelling between 2006 and 2009, and codirector of the Master on Computational Biotechnology between 2007 and 2009. He did his Ph.D. at the Biocomputing Unit of the National Center of Biotechnology (CSIC), and a post-doc at the Biomedical Imaging Group of the Swiss Federal Institute of Technology Lausanne (EPFL). In 2006 he received the Ángel Herrera research prize. He is senior member of the IEEE since 2008. He coordinates the service of image processing and statistical analysis of the CNB since 2011. In 2013, he was accredited as Full Professor. His research topics include the development of data and image processing algorithms for structural, molecular and cell biology.
Dr Rituparna Sarkar: Institut Pasteur, France
Rituparna Sarkar is currently working as an ALgorithm Engineer at KLA corporation, USA. She received her Masters and PhD degree in ELectrical Engineering in 2012 and 2017 from Iowa State University and University of Virginia respectively. She then spent a year at Samsung R&D Institute, Bangalore, India as a Chief Engineer. She then moved to Paris and was a scientific researcher at Institut Pasteur from 2018-2022. In 2022 she moved to the USA and joined KLA corporation. Her research area lies in the conjunction of image processing, computer vision and machine learning with focus on biological image analysis and bioimage informatics. She has developed novel machine learning and deep learning models for image segmentation, object detection, classification, and object shape analysis from microscopy images. She has published 20 peer reviewed articles in esteemed journals and conferences and acts as reviewer for journals such as Transactions on Image processing, Transactions on multimedia, Transactions on Neural network.
Dr Jean-Yves Tinevez: Institut Pasteur, France
Jean-Yves Tinevez is the manager of the Image Analysis Hub, a technological core facility dedicated to Bioimage Analysis. He completed his PhD in sensory biophysics, working on the hair cells of the inner ear, in the lab of Pascal Martin, Institut Curie, Paris. He then joined Ewa Paluch as a postdoc during the creation of her lab at the MPI-CBG of Dresden, and spent the next years working on force generation by the cells, probed by imaging, biomechanics, modeling and image analysis. In the same institute, he founded in 2007 the Image Processing Facility, which he led until 2009. He then joined the Institut Pasteur, Paris, joining the photonic bioimaging core of the Institut Pasteur, led by Spencer Shorte. In 2017, he founded the Image Analysis Hub, a facility entirely dedicated to service in BioImage Analysis. His work focuses on developing novel analysis pipelines, based on quantitative imaging, to advance the research projects of his collaborators. This involves service, facility management, user projects and development projects, for which he uses his skills in imaging, image analysis and computing.
Dr Virginie Uhlmann: EMBL-EBI, UK
Dr Virginie Uhlmann's research focuses on the development of algorithms for quantitative bioimage analysis, with strong interests in approximation theory, machine learning, computational geometry, and statistical shape analysis. She obtained her BSc degree in Life Sciences, MSc degree in Bioengineering, and PhD degree in Electrical Engineering from EPFL, Switzerland. She is also promoting cross-fertilization between image analysis and theoretical modelling in biology through her role as co-chair of the Theory Transversal Theme, an EMBL initiative towards theory-guided paths to understanding and conceptualising the underlying principles of biological systems.