Towards AI-driven multiomics, transforming the future of life sciences

Stefan performed his PhD and postdoc studies with focus on the origins of antibiotic resistance in bacterial pathogens at the Department of Infectious Diseases at the University of Gothenburg. He is now working as a Bioinformatics Specialist at the National Bioinformatics Infrastructure Sweden (NBIS) at Chalmers University of Technology, where he supports research projects through bioinformatics analyses.

Roger is a docent and overkemist at Sahlgrenska University Hospital, he has his own company, Nanoxis Consulting, he is an expert in proteomic analysis and has been working for many years on the use of proteomics for rapid identification of clinically-relevant bacteria and antibiotic resistance. Roger recently participated at the Sahlgrenska Global Health Hackaton and won it, with his project DIA-AID, diagnostics of antibiotic resistant infections using AI.

Magnus is a clinical microbiologist and medical doctor at Sahlgrenska University Hospital, PhD student at the Sahlgrenska Academy of the University of Gothenburg and at the same time has a strong computational background. Today he will talk to us about how AI can be used to predict antibiotic resistance in clinical microbiology.

Muhammad Arif joined the the University of Gothenburg this year as an Assistant Professor and DDLS (Data-Driven Life Science) Fellow in the Insitute of Medicine. A computer network engineer by training, he obtained his PhD in Systems Biology from the Royal Institute of Technology (KTH). He then pursued postdoctoral training at the National Institutes of Health (NIH) in the US, using machine learning and biological network analysis to study lung fibrosis and ageing. The current focus of Dr. Arif’s research is cardiometabolic diseases, where he aims to establish a data-driven model that can track longitudinal changes of the molecular landscape during disease progression. Ultimately, this model could be leveraged for improved clinical decision-making and precision medicine.

Jane is Professor in Bioinformatics and Principal Investigator of the Translational Bioinformatics Group at the School of Bioscience, University of Skövde. With over 20 years of experience in omics data analysis and integration, [Name] has led numerous successful research projects at the intersection of academia and industry. Their expertise spans single-cell data analysis, AI modelling, RNA-seq, biostatistics, and multi-omics integration.

Currently serving as project leader for several large-scale initiatives, including the KK-funded projects AI-drive Precision medicine,  Expert-AI, Expert AI-ATMP, and Biomedical AI-driven Data Analytics, as well as three ongoing Vinnova-funded projects under the Advanced Digitalization program. 

Mattias is the CEO and co-founder of IFLAI AB, a company that simplifies AI adoption, making it cost-efficient, rapid, and impactful for all industries. He is Professor of Physics at the University of Gothenburg and Fellow of The Royal Swedish Academy of Engineering Sciences
 

Nidal is a researcher at RISE Research Institutes of Sweden, Adjunct Senior Lecturer in bioinformatics, School of Bioscience, Univeristy of Skövde. She has expertise in bioinformatics and multi-omics data integration, with a focus on transcriptomics, proteomics, methylation, and metagenomics data. Their work centers on developing and applying AI-driven methods to extract meaningful insights from complex biological datasets.

Francisco is a researcher and microbiologist at RISE Research Institutes of Sweden, at the Unit of Medical Device Evaluation. He has expertise in molecular biology, genomics, proteomics and bioinformatics. His research has focussed on the development of methods for rapid diagnostics of infectious diseases and typing and characterization of antibiotic resistant bacteria, including the use of quantitative proteomics to elucidate their responses to antimicrobial compounds.