EPFL AI Center and AITHYRA Initiate New Research Collaboration

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The EPFL AI Center and AITHYRA have launched a new research collaboration to advance cross-institutional work at the interface of artificial intelligence, computational biology, and bioengineering.

This partnership builds on the shared commitment to advancing AI-driven science and innovation. Together, both institutes will explore cross-institutional challenges, strengthen the exchange of knowledge, and develop cutting-edge research that integrates computational modeling, machine learning, and biochemical engineering.

As part of this collaboration, Bruno Correia, Professor at EPFL’s School of Engineering, has been appointed Global Adjunct Principal Investigator at AITHYRA. He will coordinate two joint projects between EPFL and AITHYRA:

  • Project 1: Development of machine-learned representations for protein design and interaction prediction
  • Project 2: Generative AI for small-molecule design

Bruno Correia’s research at EPFL focuses on developing computational tools for protein design and immunoengineering, integrating method development with the experimental characterization of designed proteins. His work exemplifies the powerful synergy between artificial intelligence and molecular science, paving the way for new breakthroughs in vaccine design, cancer immunotherapy, and computational drug discovery.

Through this collaboration, EPFL and AITHYRA aim to advance the future of AI-driven research in life sciences, uniting world-class expertise to address some of the most complex problems in biology and medicine.

About the AITHYRA
The mission of AITHYRA, the Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences is to fundamentally transform biomedical science by embedding artificial intelligence as a co-pilot throughout the entire scientific process-from hypothesis generation and experimental design to biological interpretation and therapeutic innovation. Through a coherent integration of AI/ML across biological scales, the goal is to improve our understanding of the root cause of diseases, their diagnosis and the conceptualization of novel therapeutic strategies while inspiring new innovations in AI/ML. 
https://www.oeaw.ac.at/aithyra

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