Research Opportunities at the Intersection of Society, Life Sciences, and Technology

Maja Fjaestad. Photo by Jesper Petersen

Dr Maja Fjaestad worked at the EU’s European Artificial Intelligence Office in 2025 and has since returned to Sweden as a strategic advisor at Karolinska Institutet, associate professor at AI Policy lab at Umeå Univerisy and adjunct professor at Luleå University of Technology. She holds a PhD in the history of technology from KTH, has conducted research at the Max Planck Institute, and is affiliated with the Institute for Futures Studies. She is also an expert coordinator at the Centre for Health Crises at Karolinska Institutet, a member of the Royal Swedish Academy of Engineering Sciences (IVA), an author, and a sought-after speaker.

Danica Kragic

Danica Kragic is a Professor of Computer Science at KTH. Her research is in the area of robotics, computer vision and machine learning. She received ERC Starting Grant, Advanced and Synergy Grants, Distinguished Professor Grant from the Swedish research Council and she is a Wallenberg Scholar.

Olli Kallioniemi is Research Director at FIMM, University of Helsinki, and Professor of Molecular Precision Medicine at Karolinska Institutet and SciLifeLab. Trained in medicine and clinical chemistry in Finland, he later held tenure-track and tenured positions at NHGRI/NIH. He served as founding Director of FIMM (2007–2015), Director of SciLifeLab (2015–2024), and inaugural Director of the DDLS program (2022–2025). His research focuses on AI- and data-driven precision medicine, particularly in hematologic and prostate cancers. He has authored over 420 publications, holds more than 20 patents, supervised 27 doctoral theses and over 30 postdoctoral fellows. He is an elected member of EMBO, the Royal Swedish Academy of Sciences, the European Academy of Cancer Sciences, and the Nobel Assembly.

Title: Time-Resolved Imaging and Multi-Channel Evaluation of Cellular Dynamics (TIMED)

Ola Spjuth

Bio: Ola Spjuth received his PhD in Bioinformatics from Uppsala University in 2009 and completed postdoctoral fellowships at Karolinska Institutet in Stockholm and the Finnish Institute of Molecular Medicine (FIMM) in Helsinki. He is currently Professor of Pharmaceutical Bioinformatics at the Department of Pharmaceutical Biosciences, Uppsala University. His research focuses on how AI and automation, together with high-throughput and high-content molecular and cellular profiling technologies, can accelerate drug discovery and address complex challenges in pharmacology and toxicology.

Title: The 3D dynamics of the chromosome

Johan Elf

Bio: Johan has pioneered single-molecule fluorescence microscopy in living cells. This work has been complemented by the development of microfluidics, synthetic biology, and computational analysis tools. His most significant innovations include optical pooled screening and phenotypic antibiotic susceptibility testing at the level of individual bacteria.

Title: Multimodal AI-based Precision Diagnostics and Decision Support for Breast Cancer (AID4BC)

Jens Sjölund

Bio: Jens Sjölund is an assistant professor in AI at Uppsala University, WASP Fellow, and ELLIS member. His research is in machine learning and optimization, with applications across science and medicine. He previously worked as a senior research scientist at Elekta, where his dose optimization work formed the basis for Leksell Gamma Knife Lightning.

Title: Personalized medicine: Ethics and knowledge-making in data-driven medical prediction

Stefan Larsson

Bio: Stefan Larsson is a social science technology researcher at the Department of Technology and Society, Lund University in Sweden, where he leads a research group on AI and society that do interdisciplinary studies on norms, ethics and governance issues linked in the human-AI/robotics intersection.

Markus Lingman

Bio: Markus Lingman is a cardiologist, chief strategy officer and adjunct professor of medicine at University of Halmstad and affiliations at the Sahlgrenska Academy and Karolinska Institutet. His research has a focus on applied AI in healthcare and medicine leveraging real-world data.

Charlotte Högberg

Bio: Charlotte Högberg is a postdoctoral research fellow at The Department of Technology and Society, Lund University, specialized in Science and Technology Studies and medical AI. Her work concerns practices, ethics and epistemologies of the development and use of AI in medicine, healthcare and the public sector.

Title: AI tools for mental health: Clinical Trials

Sverker Sikström

Bio: Sverker Sikström is Professor of Cognitive Psychology at Lund University, and the founder and scientific lead of TalkToAlba, specializing in language based psychometrics and AI for mental health . He is a serial founder and recipient of innovation awards such as Lund University & Sparbanken Finns Innovations Prize and Venture Cup’s Startup of the Year. His academic work has been cited over 7,000 times, with an h index of 33.

Axel Carlsson

Bio: Axel Carlsson conducts broad research on diseases in primary care, with projects ranging from early detection of cancer, cognitive testing and machine learning for early identification of dementia, to studies on high blood pressure and cardiovascular risk in the population, post-COVID syndrome, and mental health.

Title: Explainable and Just AI in Data-Driven Disease Surveillance

Yana Litins’ka

Bio: Yana Litins’ka is an Associate Professor and Senior Lecturer in Public Law at Lund University. She holds an LL.D. degree in Medical Law and has been appointed as Associate Professor in Medical Law at Uppsala University. Her research sits at the intersection of health law, public health, and human rights, with a particular focus on how legal frameworks shape the protection of vulnerable groups. A central thread in her work concerns autonomy in healthcare and the boundaries of coercion and voluntariness. She also engages with rights-based perspectives on access to healthcare, including migrants’ access to health services and the rights of persons with disabilities. Yana works on a range of public health topics within law, including infectious disease control measures and preparedness for future health emergencies, examining, for example, the legal regulation of vaccination, the permissibility of restrictions on freedom of movement and privacy for public health purposes, and requirements for AI-based epidemiological monitoring.

Atiye Sadat Hashemi

Bio: Communications Technology at Technische Universität Braunschweig in Germany during 2020–2021. She was a postdoctoral fellow in Center for Applied Intelligent Systems Research at Halmstad university and currently she is an associate postdoctoral researcher in AI in Medicine at Lund University, Sweden, where she is the Principal Investigator of a Research Initiation Grant from SciLifeLab and serves as Co-Principal Investigator on a grant from Swedish Research Council (VR) focused on the application of artificial intelligence in infectious diseases. Her research lies at the intersection of artificial intelligence and healthcare, with particular emphasis on disease outbreak surveillance, privacy-preserving machine learning, and adversarial learning methods.

Workshop Organizer: Salla Franzén

Description: This workshop aims at creating awareness and collecting feedback around a new initiative to support academic researchers with AI competence through a new company called AI4S AB (AI for Science), funded by Knut and Alice Wallenberg Foundation. We offer AI support to academic researchers with ongoing grants from the three largest Wallenberg Foundations for up to 6 months full time.

Session 1

Workshop Organizer: Charlotte Högberg

Description: The current development of AI-supported precision medicine, and personalization of medical knowledge and treatment, raises concerns about ethics and fair representation. This interdisciplinary workshop examines questions of ethics and knowledge in AI-supported precision medicine, including fairness, prioritization, and changing knowledge practices. The goal is to produce a discussion paper identifying policy proposals and issues in need of further cross-disciplinary discussion.

Session 1

Workshop organizer:  Mais Qandeel

Workshop Description: Large language models contribute to the production of knowledge, such as ideas and recommendations. The accuracy and reliability of this knowledge remain questionable. What if these models contribute to the mass killing of people through mass surveillance? We ask: what does LLMs’ production of knowledge reveal about the ethical and legal dimensions of their use, given the untrustworthiness of their outputs? The discussion follows the ‘Jonsered model’

Session 1

Workshop Organizer: Katalin Kelemen

Workshop Description: How do tech professionals navigate law in real-world design choices? This workshop uses practical scenarios and small-group discussions to examine how programmers interpret, use, or resist legal norms alongside technical and organisational expectations. The session invites computer scientists, legal scholars, and social scientists to reflect on tensions, strategies, and pathways toward more legally conscious technology development.

Session 1

Workshop Organizer: Selcen Ozturkcan

Workshop Description: Generative AI is reshaping how knowledge is accessed, synthesized, and trusted. This interactive workshop explores the rise of zero-click information environments and their risks for transparency, diversity, and epistemic justice. Participants will collaboratively design actionable principles for building responsible AI systems that protect knowledge pluralism, informational autonomy, and public trust.

Session 1

Workshop Organizer: Clemens Wittenbecher

Workshop description: This workshop explores how AI foundation models applied to biomedical and health data can enable personalized prevention and healthcare, considering critical questions of governance, transparency, bias, and clinical integration. We will jointly identify current technical, social, and ethical challenges to leverage foundation models for responsible, data‑driven healthcare in Europe and discuss them with an expert panel.

Session 2

Workshop Organizer: Derya Akbaba

Abstract: In this collaborative and hands-on workshop, we will introduce and lead participants through a series of reflective exercises known as the implosion method. This exercise outlines social and historical considerations around the responsibilities, concerns, and attentions of researchers working on and with technology. Workshop attendees are expected to learn a new method for reflecting on the socio-technical impacts of their research and making connections across disciplines.

Session 2

Workshop Organizer: Sonja Mathias

Description: This workshop introduces SciLifeLab’s national OMERO service – a tool to bridge the gap between data producers and methods developers by enabling collaborative access to (bio)imaging data sets. Built on the globally recognized, open-source, data management platform OMERO1 for the visualization, management, and sharing of biological microscopy images, SciLifeLab OMERO will offer active data storage connected to HPC resources.

Session 2

Workshop Organizer: Data Centre, (Arnold Kochari, Alma Nilsson, Angela Fuentes Pardo)

Workshop Description: Modern machine learning methods open up opportunities for new discoveries, especially when researchers collaborate across fields. For example, a biologist may have collected a novel dataset and collaborate with an ML engineer to build new models. In this session, we will focus on AI-ready data – what it means in practice and how to prepare datasets so they can be shared, understood, and reliably used for AI applications.

Session 2

Workshop Organizer: Selcen Ozturkcan

Workshop Description: As the EU introduces the Digital Product Passport (DPP), this interactive workshop explores how product data can enable genuine circularity—beyond data-driven greenwashing—across production, post-production, and market use. Bringing together perspectives from AI, cybersecurity, governance, and sustainable branding, the workshop explores the technical and organizational challenges in building trustworthy, transparent, and compliant product data systems.

Session 2

Workshop Organizer: Kristen Schroeder

Workshop description: In this interactive workshop we will discuss what makes successful interdisciplinary research, including trust and leadership, fostering an environment where mistakes can be made, and creating a shared working language. Interdisciplinary groups will then create a mock educational experience on a challenging topic to explore how interdisciplinary collaboration in education can prepare young researchers to face global challenges.

Session 3

Workshop Organizer: Ericka Johnson, Francis Lee, Ylva Söderfeldt

Workshop Description: Synthetic data can mean widely varying things, which makes defining and evaluating it difficult. Likewise, it sometimes misaligns with other values, like objectivity, reproducibility and transparency. This workshop will discuss what synthetic data is, why it is useful, and what it does to the science it becomes embedded in. We will engage in hands-on, analogue activities to facilitate collaborative discussion.

Session 3

Workshop organizer: Helena Lindgren

Workshop Description: The art of Human-AI Teaming research is discovering and addressing the complications that matter, which unfold in real practice. New theory, tools and methods are required to capture the rich multi-agent setting including humans. The workshop is an excellent opportunity to expand on this research as a joint effort across expertise in the broad communities of WASP and WASP-HS.

Session 3

Workshop Organizer: Robert Johansson

Workshop Description: Adaptation is central in biology, neuroscience, psychology, and AI – but often means different things. In this workshop, we compare key definitions and methods, from behavioral change to predictive learning and algorithmic information dynamics. Participants will map shared questions, clarify key research gaps, and identify promising cross-disciplinary directions at the intersection of society, life sciences, and technology.

Session 3

Workshop Organizer: Ola Engkvist

Workshop Description: Adaptation is central in biology, neuroscience, psychology, and AI – but often means different things. In this workshop, we compare key definitions and methods, from behavioral change to predictive learning and algorithmic information dynamics. Participants will map shared questions, clarify key research gaps, and identify promising cross-disciplinary directions at the intersection of society, life sciences, and technology.

Session 3