Josien Pluim is professor of Medical Image Analysis at Eindhoven University of Technology, with a joint appointment at the University Medical Center Utrecht, for one day a week. She is head of the Medical Image Analysis group. Her research focus is on image analysis (e.g. registration, segmentation, detection, machine/deep learning), both methodology development and clinical applications. The latter is targeted in particular at oncology. Most of the research is performed in close cooperation with clinical partners and/or industry.

Josien Pluim is or was associate editor of five journals (IEEE TMI, IEEE TBME, Medical Physics, Journal of Medical Imaging and Medical Image Analysis). She served as a member of the Executive Board of the MICCAI Society, as conference chair of SPIE Medical Imaging Image Processing 2006-2009, chair of WBIR 2006 and programme co-chair of MICCAI 2010. She is a MICCAI Society and IEEE Fellow.

Sanna Ringqvist is a software engineer and the manager for the 3D reconstruction team at Maxar Sweden. She has a Master's degree in Applied Physics and Electrical Engineering from Linköping University with a specialization in Signal- and Image processing. Maxar is building the Globe in 3D, using satellite imagery and advanced technology to create an accurate representation of Earth for simulation, training, navigation etc. Sanna has been at Maxar since 2013 and has been working with semantic segmentation and 3D reconstruction using both conventional image processing and machine learning methods.

Gustav Eje Henter is a WASP assistant professor in machine learning at the Division of Speech, Music and Hearing at KTH Royal Institute of Technology, Stockholm. His main research interests are probabilistic modelling and deep learning for data-generation tasks, most prominently the synthesis of speech and motion/animation. He has an MSc and a PhD from KTH, followed by post-docs in speech synthesis at the Centre for Speech Technology Research at the University of Edinburgh, UK, and in Prof. Junichi Yamagishi's lab at the National Institute of Informatics, Tokyo, Japan, before returning to KTH in 2018.

Amy Loutfi is a Professor in Information Technology at Örebro University and leads the research group - AASS Machine Perception and Interaction Lab. Amy is also active in the programme management group for Wallenberg Autonomous Sensor Systems Programme in the AI branch. Amy Loutfi received her Ph.D. in Computer Science in 2006 with a research topic in machine perception. Specifically, she researched about how gas sensors could be integrated onto robotic platforms and how these robots can interact with humans in order to solve a range of problems that required sensing and perception. She has since broadened her research interests to include general research directions within machine perception, where AI methods like Machine learning are used for the interpretation of sensor data. She also has broadened her research in the area of Human Robot Interaction where she has studied HRI in various platforms that include fully autonomous robots, but also teleoperated robots. She has a long experience working with industry and the public sector on research projects dealing with AI, robotics and human-robot interaction.