A Joint Conference between DDLS, WASP and WASP-HS

The conference will focus on different aspects of research, where collaboration over scientific domains is essential, and will explore the following topics:

– How data- and AI-driven research is shaping the future of life science
– Development of new approaches to human-in-the-loop technologies and their use
– The need for studies at the intersection of society, AI, and data driven life sciences

Participants will have the opportunity to network, be inspired by excellent international keynote speakers, and take part of the latest research in Sweden. In addition to plenary keynotes, the program will offer a panel discussion, a poster session and ample time to mingle.

Practical Details

Venue
Wallenberg Conference Center, Medicinaregatan 20 A, Gothenburg

Registration to the Conference

The registration is closed.

Program

25 September

08:30-9:30 Project presentation WASP DDLS (4*15 min)
Ingrid Hotz, Tino Ebbers, Characterization and visualization of cardiac spectral imaging data
Sebastian Westenhoff, cryoSPHERE: Single-particle heterogeneous
reconstruction from cryo EM
Andreas Kerren, Visual Analytics for Enhancing Quality and Trust in Genome-wide Expression Clustering and Annotation
Minh Hoang Vu, Anonymization of Data in Precision Medicine Research
Chair, Olli Kallioniemi

09:30-10:45 Magnet mingle including coffee
Chair, Rebceka Jörnsten and Christofer Edling

10:45-11:30 Keynote Speaker: Klaus Høyer
All the data from everywhere all at once: data integration, AI imaginaries, and their unpredictable outcomes
Chair, Christofer Edling

11:30-12:15 Panel on common research challenges
Sunduz Keles, Ross King, Klaus Hoyer, Andreas Kerren, Tino Ebbers
Moderators, Rebecka Jörnsten and Stefan Larsson

12:15 Closing remarks, Program Directors
Christofer Edling, WASP-HS
Olli Kallioniemi, DDLS
Rebecka Jörnsten WASP

12:30 Lunch to go

Keynote Speakers

Title: Integrative Approaches to Single-Cell Genomics for Personalized Medicine
Bio: Dr. Keles obtained her Ph.D. in Biostatistics from the University of California at Berkeley. After a year-long postdoctoral appointment at UC Berkeley, she joined the Department of Biostatistics and Medical Informatics and the Department of Statistics at the University of Wisconsin, Madison. She has twenty years of experience in developing statistical and computational methods for genomics, including serving as an ENCODE PI, and pioneering foundational statistical models for leveraging multi-mapping reads in high throughput sequencing data analysis (ChIP-seq, Hi-C).

Her research interests span developing statistical and computational methods for denoising and signal extraction from sequencing data and modeling of high dimensional data. Her computational approaches led to fundamental contributions on how GATA factors mediate transcriptional regulation in HSPCs and erythroid cells. Dr. Keles is an elected fellow of the American Statistical Association.

Title: All the data from everywhere all at once: data integration, AI imaginaries, and their unpredictable outcomes
Bio: Klaus Hoeyer is professor of Medical Science and Technology Studies at the Centre for Medical Science and Technology Studies, University of Copenhagen. His research focuses on the links between policy, practice and experience in relations to medical research and clinical practice. In recent years, he has focused mainly on what he calls intensified data sourcing in healthcare and how it interacts with and changes the health services. This research is primarily financed by the European Research Council.

Title: The automation of science
Bio: Ross D. King did his PhD on applying machine learning to predicting protein structure at the Turing Institute in Glasgow. He has joint positions at Chalmers Institute of Technology, and the University of Cambridge. He is one of the most experienced machine learning researchers in Europe.

His main research interest is the interface between computer science and science. He originated the idea of a ‘Robot Scientist’: integrating AI and laboratory robotics to physically implement closed-loop scientific discovery. His Robot Scientist ‘Adam’ was the first machine to autonomously discover scientific knowledge. His Robot Scientist ‘Eve’ is currently searching for drugs against neglected tropical diseases, and COVID.  His other core research interest is DNA computing.

Title: Unraveling the secrets of nature’s high-performance fiber
Bio: Hedvig Kjellström is a Professor in the Division of Robotics, Perception and Learning at KTH Royal Institute of Technology, Sweden, and also affiliated with Swedish University of Agricultural Sciences, Swedish e-Science Research Centre, and Max Planck Institute for Intelligent Systems, Germany. She received an MSc in Engineering Physics and a PhD in Computer Science from KTH in 1997 and 2001, respectively, and thereafter worked at the Swedish Defence Research Agency, before returning to a faculty position at KTH. Her present research focuses on methods for enabling artificial agents to interpret human and animal behavior. These ideas are applied in the study of human aesthetic bodily expressions such as in music and dance, modeling and interpreting human communicative behavior, and the understanding of animal behavior and experiences. In order to accomplish this, methods are developed for agents to perceive the world and build representations of it through vision.

Hedvig has received several prizes for her research, including the 2010 Koenderink Prize for fundamental contributions in computer vision. She has written around 150 papers in the fields of computer vision, machine learning, robotics, information fusion, cognitive science, speech, and human-computer interaction. She is mostly active within computer vision, where she is an Editor-in-Chief for CVIU, a Program Chair for CVPR 2025, and regularly serves as Area Chair for the major conferences.

Title: Characterization and visualization of cardiac spectral imaging data
Bio: Ingrid Hotz is a professor at Linköping University in Sweden, leading the Scientific Visualization group in the Department of Science and Technology. She holds an M.S. in theoretical physics from Ludwig Maximilian University, Munich, and a Ph.D. in computer science from the University of Kaiserslautern. Hotz has held research positions at the Institute for Data Analysis and Visualization (IDAV) at UC Davis, the Zuse Institute Berlin, and the German Aerospace Center (DLR). Since 2015, she has been a professor at Linköping University and was named the Dr. Ram Kumar IISc Distinguished Visiting Chair Professor at the Indian Institute of Science in 2022.

Her research focuses on scientific visualization and topological data analysis, aiming to develop advanced visual analysis tools for complex datasets across various fields, including engineering, physics, chemistry, and medicine. She integrates methods from computer science and mathematics, such as computer graphics and computational topology, with a participatory design approach to ensure practical and relevant solutions.

Title: Characterization and visualization of cardiac spectral imaging data
Bio: Tino Ebbers is a professor of physiological measurements at Linköping University, with a focus on cardiac imaging, modeling, and simulation. He holds an MSc in Electrical Engineering from the University of Twente and a PhD in Biomedical Engineering from Linköping University. After completing his PhD, he worked at Philips Medical Systems before returning to academia. He also served as a visiting professor at the University of California, San Francisco.

With over 100 publications in leading scientific journals and numerous contributions to international conferences, Tino Ebbers has made a significant impact through his multidisciplinary approach to merging technical research with clinical applications. He is best known for pioneering 4D flow MRI, a breakthrough technology now widely used to study cardiovascular blood flow in both research and clinical settings. His contributions have greatly advanced cardiovascular imaging and led to major innovations in the diagnosis, treatment, and management of cardiovascular diseases.

Background

Since 2021 the Wallenberg AI, Autonomous Systems and Software Program (WASP) and the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) are collaborating through joint research projects with the ultimate goal of solving ground-breaking research questions across disciplines.

In line with this, the programs will now host the first joint annual conference, where common research topics are highlighted. Additionally, the increasingly important humanity and societal aspects of the research will be addressed through participation of the WASP-HS program (Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society).

WASP
DDLS
WASP-HS

Open Calls

The conference is an opportunity to find collaborators for the two open calls:

WASP-DDLS: NEST projects https://wasp-sweden.org/calls/call-for-joint-wasp-and-ddls-nests/

WASP-HS-DDLS: Research Initiation Grants for Data-Driven Life Sciences and Society
 https://wasp-hs.org/open-call-research-initiation-grants-for-data-driven-life-sciences-and-society/