Martin Krallinger
About Martin Krallinger
Martin Krallinger serves as the Head of Natural Language Processing for the Biomedical Information Analysis Unit at the Barcelona Supercomputing Center, where he leads efforts to develop high-quality biomedical NLP resources. He has a background in Molecular Biology and has held various academic and research positions, contributing to advancements in AI-based medical data analytics.
Work at Barcelona Supercomputing Center
Martin Krallinger currently serves as the Head of the Natural Language Processing for Biomedical Information Analysis Unit at the Barcelona Supercomputing Center (BSC). He has held this position since 2023. In this role, he leads initiatives focused on the application of natural language processing (NLP) techniques to enhance the analysis of biomedical information. His unit is part of the Life Sciences Department at BSC, where he works on integrating computational methods into life sciences research.
Education and Expertise
Martin Krallinger holds a Doctorate in Molecular Biology from Universidad Autónoma de Madrid. He also earned a Master's degree in Biology from Paris Lodron Universität Salzburg. His educational background provides a strong foundation for his work in natural language processing and biomedical research.
Background
Before his current role at BSC, Martin Krallinger worked at the CNIO - Spanish National Cancer Research Centre for a total of eight years. His positions there included Technical Researcher, Head of the Biological Text Mining Unit, and a Predoctoral Researcher. He also served as an Honorary/Invited Professor at Universitat Pompeu Fabra for one year. His extensive experience in research and academia has shaped his expertise in biomedical NLP.
Achievements
Under Martin Krallinger's leadership, the NLP4BIA group has developed and released various high-quality biomedical NLP resources. These contributions have advanced deep learning and language model-based solutions through significant open benchmark shared tasks such as BioCreative and IberEVAL. His team is also engaged in generating knowledge graphs from text, focusing on extracting gene regulatory networks and drug-target interactions.
Research Collaborations and Practical Applications
Martin Krallinger's group is involved in both national and international research collaborations aimed at unlocking information from unstructured health data. These efforts are directed towards empowering AI-based medical data analytics tools. The NLP4BIA group is actively working on practical exploitation scenarios in various fields, including cardiology, cardiovascular diseases, occupational health, and rare diseases.