18th May, Spring meeting 2022: Deep understanding
We are excited to meet live with all of you again. On Wednessday 18th of May 2022 we hope to see you in Zwolle.
During this afternoon we will explore the understanding of deep learning, going from first principals, dynamical visual learning, computational modelling (digital twins) to failure of learning. You will get a lot of insight in the why and how of deep learning. We have found four wonderful speakers for this event.
• Bart ter Haar Romenij (TU/e), our society president will give his farewell lecture on something quite special: understanding deep learning from first principles and the human visual system. To support the credibility: all will be explained with life coding.
• Alex Frangi (Leeds Univ.), an outstanding computer vision researcher from England tells about research at the crossroads of image analysis and modeling with emphasis on machine learning.
• Efstratios Gavves(UvA), will teach us on the so crucial (and rewarding) dynamics of temporal machine learning.
• Veronika Cheplygina(IT Univ. of Copenhagen), also leaving the board, has an exciting lecture about shortcomings of machine learning and recommendations to overcome these.
We start with a lunch and end with drinks, so there will be plenty of time for networking and catching up with everyone.
The meeting (incl. lunch, coffee/tea and drinks) is free for members of NVPHBV, and only 15 euros for others, but free if you become a member (for only 15 euro/year)
Spring Meeting 2022
- 12:00 - 13:00
- Welcome & Lunch
- 13:00 - 13:30
- Society member meeting
- 13:30 - 14:20
- Precision Imaging – from model-based imaging to image-based modelling
Speakers:Prof. Alex Frangi
- 14:20 - 15:10
- Responsible research practices for machine learning in medical imaging
Speakers:Dr. Veronika Cheplygina
- 15:10 - 15:30
- 15:30 - 16:20
- The Machine Learning of Time and Dynamics … with an Outlook towards the Sciences
Speakers:Dr. Efstratios Gavves
- 16:20 - 17:30
- How do deep neural nets really work?
Speakers:Em.Prof. Bart ter Haar Romeny
Dr. Efstratios GavvesUniversity of Amsterdam
Dr. Efstratios Gavves is an Associate Professor at the University of Amsterdam in the Netherlands, an ELLIS Scholar, and co-founder of Ellogon.AI. He is a director of the QUVA Deep Vision Lab with Qualcomm, and the POP-AART Lab with the Netherlands Cancer Institute and Elekta. Efstratios received the ERC Career Starting Grant 2020 and NWO VIDI grant 2020 to research on the Computational Learning of Time for spatiotemporal sequences and video. His background is in computer vision, and the last several years moved his interest to temporal machine learning and systems dynamics, efficient computer vision, and machine learning for oncology.
Dr. Veronika CheplyginaIT University of Copenhagen
Dr. Veronika Cheplygina’s research focuses on limited labeled scenarios in machine learning, in particular in medical image analysis. She received her Ph.D. from Delft University of Technology in 2015. After a postdoc at the Erasmus Medical Center, in 2017 she started as an assistant professor at Eindhoven University of Technology. In 2020, failing to achieve various metrics, she left the tenure track of search of the next step where she can contribute to open and inclusive science. She recently started as an associate professor at IT University of Copenhagen. Next to research and teaching, Veronika blogs about academic life at https://www.veronikach.com. She also loves cats, which you will often encounter in her work.
Em.Prof. Bart ter Haar Romenychairman NVPHBV - Eindhoven University of Technology - Eindhoven NL
Prof. Romeny has spent his whole career in geometrical biomedical image analysis, exploiting ‘brain-inspired computing’. The methods developed in that computer vision community turn out to be today eminently suitable for explainable AI (XAI). Prof. Romeny is a awarded speaker, and will give this extended lecture as his farewell as president of our society for 9 years.
Prof. Alex FrangiUniversity of Leeds
Professor Frangi is Diamond Jubilee Chair in Computational Medicine and Royal Academy of Engineering Chair in Emerging Technologies at the University of Leeds, Leeds, UK, with joint appointments at the School of Computing and the School of Medicine. He directs the CISTIB Center for Computational Imaging and Simulation Technologies in Biomedicine. Prof Frangi is the Scientific Director of the Leeds Centre for HealthTech Innovation and Director of Research and Innovation of the Leeds Institute for Data Analytics.
Professor Frangi’s main research interests lie at the crossroads of medical image analysis and modeling with emphasis on machine learning (phenomenological models) and computational physiology (mechanistic models). He has particular interest in statistical methods applied to population imaging and in silico clinical trials. His highly interdisciplinary work has been translated to cardiovascular, musculoskeletal and neurosciences.
Born in La Plata, Argentina, he moved in 1991 to Barcelona, Spain, where he obtained his undergraduate degree in Telecommunications Engineering from the Technical University of Catalonia (Barcelona) in 1996. He did his PhD in Medicine at the Image Sciences Institute of the University Medical Center Utrecht on model-based cardiovascular image analysis. During this period, he was visiting researcher at the Imperial College in London, UK, and in Philips Medical Systems BV, The Netherlands.
He has edited several books, published 7 editorial articles, and over 260 journal papers in key international journals of his research field, and more than 200 book chapters and international conference papers with an h-index of 69 and over 29,000 citations (Google Scholar).
Professor Frangi is Chair of the Editorial Board of the MICCAI-Elsevier Book Series (2017-2020) and is Associate Editor of IEEE Trans on Medical Imaging, Medical Image Analysis, SIAM Journal Imaging Sciences, Computer Vision and Image Understanding journals. Professor Frangi has received numerous professional awards. Professor Frangi is an IEEE Fellow (2014), MICCAI Fellow (2021), SPIE Fellow (2020), EAMBES Fellow (2013), SIAM Member, and elected member of the Board of Directors of the Medical Image Computing and Computer Assisted Interventions (MICCAI) Society (2014-2018). Professor Frangi serves in the Scientific Advisory Board of the European Institute for Biomedical Imaging Research (EIBIR) and was Chair of the Fellows Committee of the IEEE EMBS (2017-2018).