David A. Clifton

David A. Clifton is Professor of Clinical Machine Learning in the Department of Engineering Science of the University of Oxford, and OCC Fellow in AI & Machine Learning at Reuben College, Oxford. He is a Research Fellow of the Royal Academy of Engineering, Visiting Chair in AI for Healthcare at the University of Manchester, and a Fellow of Fudan University, China. He studied Information Engineering at Oxford's Department of Engineering Science, supervised by Prof. Lionel Tarassenko CBE, Chair of Electrical Engineering. His research focuses on the development of machine learning for tracking the health of complex systems.

Julia Schnabel

Julia Schnabel graduated with a Diplom (MSc equivalent) in Informatics at the Technical University Berlin in 1993, and a PhD in Computer Science at University College London (UCL) in 1998. In 2014 she became full Professor of Engineering Science at Oxford, and in 2015 joined King’s as a Chair in Computational Imaging. In 2021 Julia joined Helmholtz Center Munich (Helmholtz Distinguished Professorship) and Technical University Munich (TUM Liesel Beckmann Distinguished Professorship) as Professor for Computational Imaging and AI in Medicine. Julia's research interests are in machine/deep learning for image reconstruction, image quality, motion modelling, segmentation and classification tasks in cancer, cardiovascular diseases, and fetal health.

Cristina Soguero Ruiz

Cristina Soguero Ruiz received the Telecommunication Engineering and the Business Degree from Rey Juan Carlos University, Spain, in 2011, and the Ph.D. Degree in machine learning with applications in healthcare, with the Joint Doctoral Program in Multimedia and Communications in conjunction with Rey Juan Carlos University and the University Carlos III of Madrid, in 2015. She was supported by FPU Spanish Research and Teaching Fellowship (granted in 2012). She won the Orange Foundation Best Ph.D. Thesis Award by the Spanish Official College of Telecommunication Engineering. She has published more than 30 papers in JCR journals and 50 international conference communications. She has participated in several research projects (with public and private fundings) related to healthcare data-driven machine learning systems, being principal investigator of 5 (including an european project). Her current research interests include machine learning, data science, and statistical learning theory.

Habib Zaidi

Professor Habib Zaidi is Chief physicist and head of the PET Instrumentation & Neuroimaging Laboratory at Geneva University Hospital and faculty member at the medical school of Geneva University. He is also a Professor of Medical Physics at the University of Groningen (Netherlands), and Adjunct Professor of Molecular Imaging at the University of Southern Denmark. He is actively involved in developing imaging solutions for cutting-edge interdisciplinary biomedical research and clinical diagnosis in addition to lecturing undergraduate and postgraduate courses on medical physics and medical imaging.

Bart Geerts

Bart Geerts is an anaesthetist, intensive care physician and clinical pharmacologist from Amsterdam, the Netherlands. Bart is an academic researcher with an interest in perioperative process optimisation. In his clinical work, through research and innovation, his aim is to achieve better outcomes by enabling more proactive provision of care and getting more insights from existing data. Three years ago, Bart started This start-up of eight people is currently performing clinical trials in three European sites to study the impact of a machine-learning tool, called PERISCOPE, that predicts infections after surgery in adults. He is hoping to make a dent in one of the major problems occurring in surgical care today. Bart has an MD, PhD in intensive care medicine, and an MSc in Biomedical Sciences from Leiden University (the Netherlands), and an MBA from IE University in Madrid (Spain).

Brita Elvevåg

Brita Elvevåg is an academic researcher internationally recognized for her research in psychiatry that uses natural language processing methods to improve assessment. Her current research focuses on the viability of artificial intelligence to enable the remote monitoring of patients’ cognitive and mental states, specifically via speech. She started her research career with a PhD in experimental psychology (cognitive neuroscience) from the University of Cambridge (UK), and then continued full-time research at the National Institute of Mental Health in Maryland (USA). In 2010 she joined the University of Tromsø – the Arctic University of Norway – where she is Professor of Psychiatry at the Department of Clinical Medicine. She has published over 100 scientific articles.

Stian Normann Anfinsen

Stian Normann Anfinsen is head of the Machine Learning Group at UiT The Arctic University of Norway. He received the M.Sc. degree in communications, control, and digital signal processing from the University of Strathclyde in Glasgow, UK (1998), and the Cand.mag. (1997), Cand.scient. (2000) and Ph.D. degrees (2010) in physics from UiT The Arctic University of Norway in Tromsø, Norway. Since 2014 he has been an Associate Professor with the Department of Physics and Technology at UiT, formerly with the Earth Observation Group and currently with Machine Learning Group, where he is leading research activities on energy analytics and machine learning for oncological medical imaging. He leads the machine learning work package in the preclinical project of 180N - Norwegian Nuclear Medicine Consortium, and is also affiliated with the machine learning work package in the clinical project. His research interests are in statistical modelling, pattern recognition and machine learning algorithms for image, graph and time series analysis.

Anne Kjersti Befring

Anne Kjersti Befring er i dag ansatt som førsteamanuensis ved juridisk fakultet i Oslo med et særskilt ansvar for helserett og life science. Hun disputerte i 2019 med temaet: Genetisk kartlegging som grunnlag for persontilpasset medisin, rettslige perspektiver, og var redaktør for en artikkelsamling fra 2020 med tittelen: Kunstig intelligens og big data i helsesektoren. Befring har bakgrunn fra helsemyndighetene, advokatpraksis og som juridisk direktør i Legeforeningen, før hun startet ved UiO i 2014.

Tor Ingebrigtsen

Tor Ingebrigtsen is professor of clinical neurosurgery in the Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø, Norway, and a visiting professor to the Australian Institute of Health Innovation, Macquarie University, Sydney, Australia. He is one of the co-founders of the Norwegian Registry for Spine Surgery (NORspine). His research focuses on clinical quality registries in cerebrovascular and spine surgery, guideline development and implementation and health IT. At the conference, he will review publications about utilization of artificial intelligence and machine learning in analysis of register data, and present ongoing work in the NORspine-registry, which aims to develop a machine learning-based real-time decision support for spine surgery, fully integrated in the electronic health record.

Kasper Jensen

Kasper Jensen is a solution architect and healthcare solution expert who is passionate about driving change in both the public and private healthcare through IT-architecture. He has been working with digitalization, healthcare, and natural language processing for a decade with both a PhD from the Technical University of Denmark and a Postdoc from the Norwegian Centre of E-health research. He has serval high impact research publications in journals including Nature Scientific Reports and Nature Communications.

Robert Jenssen

Robert Jenssen @jenssen_robert is the Director for Visual Intelligence, a Centre for Research-based Innovation (SFI) funded by the Research Council of Norway and Consortium partners. Please see and @SFI_VI for more information. Jenssen is a professor in the Machine Learning Group at the Department of Physics and Technology at UiT The Arctic University of Norway. He is also a professor at the Department of Computer Science at the University of Copenhagen, and at the Norwegian Computing Center, Oslo. Jenssen's research interests are within the development of new and advanced machine learning methodology, particularly deep artificial neural networks, for image analysis and data analysis in general. Jenssen has been active at the intersection of health and technology by leveraging AI for novel decision and diagnosis support. Jenssen is a chair for the annual Northern Lights Deep Learning (NLDL) Conference

Finn Henry Hansen

Finn Henry Hansen er direktør i stab i Helse Nord RHF. De siste årene har han hatt særlig ansvar for samhandling, e-helse og nasjonale kvalitetsregistre, men har tidligere ellers hatt bredt ansvar innen en rekke felt av helsetjenesten. Hansen er utdannet statsviter og har jobbet med helsetjenesten i hele sin yrkeskarriere, både som forsker og leder. Hansen har vært tilknyttet Universitetet i Bergen, Universitetet i Tromsø og Høgskolen i Bodø, har hatt forskningsopphold ved University og Wisconsin-Madison og Stanford University, og har hatt flere opphold i National Health Service i England. Han var fylkeshelsesjef i Hordaland 1991-97, fylkeshelsesjef i Nordland 1997-2000, forskningssjef i SINTEF 2000-2001, og har siden siden 2002 inngått i ledelsen i Helse Nord RHF, de fleste av disse årene som stedfortreder for adm .direktør. Hansen har ledet og deltatt i en rekke nasjonale og regionale utvalg og arbeidsgrupper innen helsetjenesten. De siste 8 årene har han vært medlem av styringsgruppen for Nasjonalt senter for telemedisin (2011-2015) og Nasjonalt senter for e-helseforskning (2016-2019).

Vibeke Binz Vallevik

Vibeke Binz Vallevik is deputy program manager and principal researcher with the DNV Healthcare research program ( She is currently leading the BigMed project ( through the intervention center at Oslo University Hospital. With over 20 partners from academia, clinic and industry, BigMed is an NFR funded lighthouse project with a vision to pave the way for clinical implementation of precision medicine. Building on her expertise in complex projects and risk management, she has contributed to establishing several important initiatives, ranging from a joint research centre with the China National Health Economics Institute on managing risk in the 2020 Healthcare reform to developing DNV’s precision medicine activities and the establishment of the Nordic Alliance for Clinical Genomics ( ). Key focus areas include assurance needs in the clinical implementation of precision medicine, and Vibeke is passionate about ensuring an up to date healthcare service through safe adoption of new technology.

Lars Ailo Bongo

Lars Ailo Bongo is a professor in health technology at the Department of Computer Science, UiT The Arctic University of Norway. He is the principal investigator in the Health Data Lab. He received his Ph.D. from the University of Tromsø in 2008, and spent two years as postdoctoral researcher at Princeton University. His main research interest is to build and experimentally evaluate infrastructure systems that support the methods under development by our bioinformatics and health science collaborators. In particular, designing and implementing systems for big data storage, scalable and reproducible data processing, machine learning based data analysis, and data exploration tools. Homepage:

Kristian Svendsen

Kristian Svendsen is an associate professor of Pharmacoepidemiology at the Department of Pharmacy, UiT The Arctic University of Norway. His PhD is from NTNU in 2012, and after this he spent 2 year working for the European Medicines Agency (EMA) in London as a data manager and data analyst. His main research interest is studying how various medicines can be used more rationally in the population and how newer methodologies can be used in pharmacoepidemiology. He is also involved in clinical research projects in collaboration with the Northern Norway Hospital Pharmacy Trust as well as a wide variety of projects in collaboration with various clinicians. Adverse drug reactions are a point of particular interest since working with these type of european data at EMA. Contact details and list of publications at UiT page:

Tomoyuki Irino

Tomoyuki Irino is an assistant professor in the Department of Surgery at Keio University in Tokyo, Japan. He attended Keio University School of Medicine (Japan) and trained in surgery at Keio University Hospital and its affiliated hospitals. After completion of his specialty training he pursued fellowship training at Cancer Institute Hospital, one of the top cancer centres in Japan, studying minimally-invasive surgery for upper gastrointestinal cancers and during his fellowship program he has worked for Karolinska University Hospital (Sweden) for two years as a fellow surgeon. He has an MD, PhD in medicine from Keio University (Japan) and an MSc in Clinical Trials from London School of Hygiene and Tropical Medicine (UK). His current research focuses on artificial intelligence in cancer diagnosis and surgery using medical images and its clinical application.

Solveig Hofvin

Solveig Hofvin er leder av Mammografiprogrammet og mammografiseksjonen på Kreftregisteret. I tillegg har hun en professor II stilling på radiografiutdanningen på OsloMet. Arbeidet 15 år på SiA (nå Ahus), primært med mammografi den siste tiden før hun startet på Kreftregisteret, hvor hun tok sin doktorgrad på data fra Mammografiprogrammet i 2005. Har hatt to-års gjesteopphold i USA og har et stort nasjonalt og internasjonalt nettverk. Mer enn 180 fagfellevurderte artikler innen brystkreft, mammografi og mammografiscreening.

Ishita Barua

Ishita Barua is a MD and a PhD candidate in the Clinical Effectiveness Research Group at Oslo University Hospital and the University of Oslo. She is currently a Fulbright Fellow at BIDMC/Harvard Medical School. Her research focuses on the use of artificial intelligence in colorectal cancer diagnosis and colonoscopy, and the general integration of AI in clinical decision-making. She is co-founder of and lecturer in the elective subject called "AI, Innovation, Big Data and Clinical Decision Support", for medical students at the University of Oslo. In 2021, she was named one of top 30 women in Norway changing the field of Artificial Intelligence, by NORA (The Norwegian Artificial Intelligence Research Consortium). She is a deputy member of The Norwegian Biotechnology Advisory Board appointed by the Norwegian government, president of Young Internists of Norway, board member of The Nordic Privacy Center and the Norwegian Council of Digital Ethics (NORDE).

Bjørn Anton Graff

Bjørn Anton Graff er forsknings- og innovasjonsansvarlig i Klinikk for medisinsk diagnostikk i Vestre Viken helseforetak. Han er sivilingeniør innen biofysikk med doktorgrad fra Radiumhospitalet. Han har tidligere jobbet som forsker og seksjonsleder i Nasjonalt kunnskapssenter for helsetjenesten og hadde der et spesielt fokus på vurdering av nye metoder. Senere har han jobbet som seksjonsleder både på Oslo Universitetssykehus og i Vestre Viken. Bjørn trives best i kupert terreng både på jobb og fritid og bruker nå mest tid på prosjektledelse, primært et prosjekt hvor Vestre Viken og Sykehuset i Vestfold skal implementere kunstig intelligens innen bildediagnostikk.

Siv Fjellkårstad

Siv Fjellkårstad er prosjektleder i Helsedirektoratet med utdannelse fra helse og IT. Hun leder det nasjonale koordineringsprosjektet «Bedre bruk av kunstig intelligens» som er en del av arbeidet med Nasjonal Helse- og sykehusplan 2020-2023. Prosjektet hjelper og veileder aktørene kan lykkes med å ta i bruk kunstig intelligens i den offentlige helsetjenesten.

Frida Holmberg Hansen

Frida Holmberg Hansen er samfunnsviter med fordypning i teknologi og innovasjon. Hun arbeider som prosjektleder i Helsedirektoratet og har ledet kartleggingsarbeidet om god klinisk praksis og behov for normering ved bruk av kunstig intelligens innenfor radiologi. Dette arbeidet er et tiltak under det nasjonale koordineringsprosjektet «Bedre bruk av kunstig intelligens».

Stein Olav Skrøvseth

Stein Olav Skrøvseth er senterleder ved Nasjonalt senter for e-helseforskning. Han er utdannet sivilingeniør med doktorgrad i matematisk fysikk fra Norges teknisk-naturvitenskapelige universitet (NTNU) i Trondheim. I 2008 arbeidet han som postdoktor ved University of Sydney i Australia, før han ble ansatt som forsker ved Nasjonalt senter for samhandling og telemedisin i Tromsø i 2009. Her arbeidet han i og ledet flere forskningsprosjekter innen statistikk, medisinsk bildebehandling, maskinlæring, mønstergjenkjenning og dataanalyse. I 2013-14 var han gjesteforsker ved IBM Thomas J. Watson forskningslaboratorium i New York. Han var med i opprettelsen av Nasjonalt senter for e-helseforskning, og har siden april 2016 vært senterleder ved senteret. I 2017 gikk han nasjonalt topplederprogram for spesialisthelsetjenesten.

Ira Haraldsen

Dr. Ira Ronit Hebold Haraldsen, MD PhD, Neurology and Psychiatry. Adm. expertise of clinical department- and research group leadership. Research background in neuroendocrinology, neurobiology of ageing, and translational innovation project management. She is the PI of AI-Mind (project No. 964220), a 14 million Euro Research and Innovation Action (RIA) H2020-SC1-BHC-06-2020 project. Dr. Haraldsen has a proven track record in heading, participating and stimulating several national and EU projects (ENIGI 2007-2017,) Glasgow-Oslo Sheep Study, Cost actions BM1105. and BM1303. She is leading the Cognitive Health Research group (CoHR) at OUS which has published only during the last 3 years more than 60 papers.