{"id":1018,"date":"2022-10-04T21:05:17","date_gmt":"2022-10-04T21:05:17","guid":{"rendered":"https:\/\/avadawebsites.wpengine.com\/business\/?page_id=1018"},"modified":"2025-11-04T01:59:33","modified_gmt":"2025-11-04T00:59:33","slug":"disciplines","status":"publish","type":"page","link":"https:\/\/www.upo.es\/investiga\/synergialab\/disciplines\/","title":{"rendered":"Disciplines"},"content":{"rendered":"

SIALAB\u2019s<\/strong> disciplines combine Artificial Intelligence (AI) and High-Performance Computing (HPC) to tackle major challenges in health, biology, data infrastructure, and society through interdisciplinary research.<\/div><\/div><\/div><\/div>
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Multimodal AI for Health<\/h4><\/div>

Development of AI models integrating clinical, omics, imaging and biomedical textual data for advanced healthcare applications.<\/p>\n<\/div><\/div><\/div>

Health AI<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div>

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HPC and Supercomputing<\/h4><\/div>

Design and optimization of high-performance infrastructures to accelerate large-scale scientific computing.<\/p>\n<\/div><\/div><\/div>

Computer Science<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div>

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AI-Driven Biomedicine<\/h4><\/div>

Application of AI algorithms to biological data for pattern discovery, feature extraction and biomarker identification.<\/p>\n<\/div><\/div><\/div>

Health AI<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div>

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Big Data Analytics<\/h4><\/div>

Scalable analysis and mining of massive, heterogeneous and high-dimensional datasets using AI techniques across scientific and societal domains.<\/p>\n<\/div><\/div><\/div>

Computer Science<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div>

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AI and HPC for Societal Systems<\/h4><\/div>

Use of AI and HPC to model and analyze social, cultural, environmental and policy-related complex systems and challenges.<\/p>\n<\/div><\/div><\/div>

Societal Applications<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div>

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Data management and FAIR principles<\/h4><\/div>

Efficient management and sharing of scientific data following FAIR (Findable, Accessible, Interoperable, Reusable) principles.<\/p>\n<\/div><\/div><\/div>

Computer Science<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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Synergy – Innovation – Health AI<\/p>\n<\/div>

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Not where you\u2019re from, but where we\u2019re going \u2014 together.<\/h2><\/h2><\/div>

SIALAB promotes interdisciplinary research by connecting artificial intelligence and high-performance computing with the social and life sciences, generating scientific knowledge that contributes to addressing complex societal and biomedical challenges.<\/p>\n<\/div>