Mens X Machina

Our software

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Projects



Huawei Technologies

Causal discovery and inference for surrogate-assisted optimization

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CAUSAL PATH

Next Generation Causal Analysis inspired by the induction of biological pathways from cytometry data

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HUNT

Our aim is to develop a blood test for screening of smokers and asbestos exposed individuals to detect and cure these cancers.

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STATEGRA

Statistical methods and tools for the integrative analysis of omics data

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Our Team

Publications

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About Us

Mens Ex Machina, Mind from the Machine or “Ο από Μηχανής Νους” paraphrases the latin expression Deus Ex Machina, God from the Machine. The name was suggested by Lucy Sofiadou, Prof. Tsamardinos’ wife.

We are a research group, founded in October 2006, led by Professor Ioannis Tsamardinos, interested in Artificial Intelligence, Machine Learning, and Biomedical Informatics and affiliated with the Computer Science Department of University of Crete. The aims of the group are to progress science and disseminate knowledge via educational activities and computer tools. Our group is involved in

Research:

Theoretical, algorithmic, and applied research in all of the above areas; we are also involved in interdisciplinary collaborations with biologists, physicians and practitioners from other fields.

Education:

Educational activities, such as teaching university courses, tutorials, summers schools, as well as supervising undergraduate dissertations, masters projects, and Ph.D. theses.

Systems and Software:

Implementation of tools, systems, and code libraries to aid the dissemination of the research results. Funding is provided from and through the University of Crete, often originating from European and International research grants.

Current research activities include but not limited to the following:

  • Causal discovery methods and the induction of causal models from observational studies. Specifically, we have recently introduced the problem of Integrative Causal Analysis (INCA).
  • Feature selection (a.k.a. variable selection) for classification and regression.
  • Induction of graphical models, such as Bayesian Networks from data.
  • Analysis of biomedical data and applications of AI and Machine Learning methods to induce new biomedical knowledge.
  • Activity recognition in Ambient Intelligent environments.

Ioannis Tsamardinos

Professor, Department of Computer Science, University of Crete