giorgos-bouritsas
Giorgos Bouritsas
RESEARCH INTERESTS

Giorgos’ research lies within the fields of Geometric and Graph Deep Learning and involves the design and theoretical analysis of data-driven methodologies for geometric and symmetric data, such as complex networks, physical systems and 3D objects. His contributions and interests lie in two conceptual axes: the theoretical underpinnings of graph/geometric neural networks (expressive power, inductive biases) and graph/geometric data synthesis (generative models and compression). As part of his appointment at Archimedes, he aims to expand these axes towards problems of increasingly complex nature, in particular learning on multimodal, as well as dynamically evolving geometric data (e.g. multilayer and dynamic networks).

SHORT BIO

Giorgos Bouritsas is a machine learning researcher and currently holds a postdoctoral fellow position with the Archimedes AI unit / Athena Research Center, working within the group of Prof. Yannis Panagakis. He obtained his PhD in computer science from Imperial College London (2023), under the supervision of Prof. Michael Bronstein and Prof. Stefanos Zafeiriou, and his MEng in electrical and computer engineering from the National Technical University of Athens (2017). Previously, he was a research scientist intern at Google Deepmind, a visiting PhD researcher at École Polytechnique Fédérale de Lausanne, a research associate at NCSR Demokritos and a visiting undergraduate student researcher at Universitat Politècnica de Catalunya. He has conducted basic and applied research on topics in the intersection of machine learning with other scientific fields, such as computer vision, network science and physics, and his work has been published in leading conferences (NeurIPS, CVPR, ICCV, ECCV) and journals (TPAMI). In addition, he regularly performs educational activities, such as tutorials and teaching postgraduate courses, while he provides academic service as a reviewer in machine learning conferences (e.g. ICLR, ICML, NeurIPS) and journals (e.g. TPAMI, TMLR), for which he has received outstanding reviewer awards.

 

The project “ARCHIMEDES Unit: Research in Artificial Intelligence, Data Science and Algorithms” with code OPS 5154714 is implemented by the National Recovery and Resilience Plan “Greece 2.0” and is funded by the European Union – NextGenerationEU.

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