Grigorios Tsagkatakis
Assistant Professor, Computer Science Department, University of Crete
Collaborating Researcher, Signal Processing Lab, ICS‑FORTH
My research focuses on signal processing and machine learning for extracting usable science from observations that are incomplete, noisy, quantised or simply too few, primarily in remote sensing, astrophysics and neuroscience.
I hold a Diploma (2005) and M.Sc. (2007) in Electronic and Computer Engineering from the Technical University of Crete, and a Ph.D. in Imaging Science from the Rochester Institute of Technology (2011), where I worked with Prof. Andreas Savakis on dimensionality reduction and sparse representations in computer vision. I was a Marie Curie Fellow at ICS‑FORTH from 2011 to 2013, and a Marie Skłodowska‑Curie Global Fellow with Prof. Mahta Moghaddam at the University of Southern California. Since April 2023 I have been an Assistant Professor in the Computer Science Department at the University of Crete, and since 2025 a founding member of the Institute of Astrobiology at the University's Research and Innovation Centre.
greg@ics.forth.gr · gtsagkatakis@gmail.com · +30 2811 392725
Computer Science Department, University of Crete ·
Institute of Computer Science, FORTH
N. Plastira 100, Vassilika Vouton, GR‑700 13 Heraklion, Crete, Greece
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Sep 2026Co-organising the Workshop on Physics-Informed Machine Learning at FORTH, 16–18 September, co-sponsored by TITAN and the IEEE Geoscience and Remote Sensing Society.
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Jun 2026“The More, the Merrier: Contrastive Fusion for Higher-Order Multimodal Alignment” selected as a Highlight paper at CVPR 2026. PDF
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Apr 2026Invited talk, “Parsimony in Distributed Learning,” at SPTDC 2026, the School on the Practice and Theory of Distributed Computing, FORTH.
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Sep 2025Co-organised MINOAS, a workshop on machine intelligence for inverse imaging, observation analysis and sensing, at FORTH.
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Aug 2025Co-organised the session on Physics-Informed Machine Learning in Remote Sensing at IGARSS 2025.
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Jun 2025Invited talk on uncertainty-aware machine learning for astronomical data analysis at UniversAI, organised by the International Astronomical Union, Athens.
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2025–2028COMPASS — Computational Intelligence for Signal Sensing and Analysis Principal Investigator · HFRI
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2026–2028AIRGUS — Neural compression for bandwidth and power efficiency on space missions Technical lead for FORTH · ESA, with OHB Hellas
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2023–2027TITAN — Frugal Artificial Intelligence and Applications in Astrophysics Technical coordination of the astroinformatics programme · ERA Chairs
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2022Multi-Frame Super-Resolution — self-supervised on-board super-resolution, deployed on ESA's OPS‑SAT in orbit Technical lead for FORTH · ESA, with OHB Hellas
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2020–2022Fusion of Passive and Active Microwave Remote Sensing Data Co‑PI · NASA ROSES, with M. Moghaddam (USC)
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2019–2022CALCHAS — Computational Intelligence for Multi-Source Remote Sensing Data Analytics Fellow · H2020 MSCA Global Fellowship
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2026S. Koutoupis, M.A. Zervou, K. Kontras, M. De Vos, P. Tsakalides, G. Tsagkatakis, “The More, the Merrier: Contrastive Fusion for Higher-Order Multimodal Alignment,” CVPR. Highlight PDF
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2026A. Lahiry, T. Díaz-Santos, J.L. Starck, N. Roy, D. Anglés-Alcázar, G. Tsagkatakis, P. Tsakalides, “Deep and sparse de-noising benchmarks for spectral data cubes of high-z galaxies: from simulations to ALMA observations,” Astronomy & Astrophysics. PDF
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2024J. Fagin, G. Vernardos, G. Tsagkatakis, Y. Pantazis, A.J. Shajib, M. O'Dowd, “Measuring the substructure mass power spectrum of 23 SLACS strong galaxy–galaxy lenses with convolutional neural networks,” MNRAS. PDF
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2023E. Troullinou, G. Tsagkatakis, A. Losonczy, P. Poirazi, P. Tsakalides, “A Generative Neighborhood-based Deep Autoencoder for Robust Imbalanced Classification,” IEEE Transactions on Artificial Intelligence. PDF
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2022G. Drakonakis, G. Tsagkatakis, K. Fotiadou, P. Tsakalides, “OmbriaNet — Supervised Flood Mapping via Convolutional Neural Networks Using Multitemporal Sentinel-1 and Sentinel-2 Data Fusion,” IEEE JSTARS. PDF
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2021A. Aidini, G. Tsagkatakis, P. Tsakalides, “Tensor Decomposition Learning for Compression of Multidimensional Signals,” IEEE Journal of Selected Topics in Signal Processing. PDF
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2020G. Vernardos, G. Tsagkatakis, Y. Pantazis, “Quantifying the structure of strong gravitational lens potentials with uncertainty-aware deep neural networks,” MNRAS. PDF
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2020T. Geiller, B. Vancura, S. Terada, E. Troullinou, S. Chavlis, G. Tsagkatakis, et al., “Large-Scale 3D Two-Photon Imaging of Molecularly Identified CA1 Interneuron Dynamics in Behaving Mice,” Neuron. PDF
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2019G. Tsagkatakis, A. Aidini, K. Fotiadou, M. Giannopoulos, A. Pentari, P. Tsakalides, “Survey of Deep Learning Approaches for Remote Sensing Observation Enhancement,” Sensors. PDF
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2018A. Aidini, G. Tsagkatakis, P. Tsakalides, “1-Bit Tensor Completion,” Electronic Imaging Symposium. Best paper PDF
Computer Science Department, University of Crete.
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2023–CS‑573 Optimisation Methods Graduate
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2023–CS‑485 Introduction to Data Science Undergraduate elective
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2019–CS‑110 Calculus I Undergraduate, required
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2018–2024CS‑111 Calculus II Undergraduate, co-taught
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2019CS‑570 Statistical Signal Processing Graduate
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2015–2018CS‑541 Wireless Sensor Networks Graduate, co-taught
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CurrentChair, Working Group on Physical Model Informed Machine Learning, IEEE GRSS Modeling in Remote Sensing Technical Committee.
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2025Evaluator, European Commission.
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2025Co-organiser and speaker, tutorial on bio-inspired approaches to video coding and compression, IEEE ICME, Nantes.
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2024Co-organiser, 10th Astronomical Data Analysis Summer School, Hersonissos, Crete.