Dr Michele Svanera                                                                                       


After obtaining my Bachelor and Master degrees working on Signal Processing, Computer Vision and Machine Learning, since the second year of my PhD I became more and more interested in neuroscience, thanks to multiple collaborations with different Brain centres (Maastricht and Tel Aviv). Wandering across Cognitive Neuroscience and Artificial Intelligence (specifically deep learning), I am interested to address the goal to understand the brain activities in relation with movie stimulus applying recent advances in machine learning. I joined Prof. Lars Muckli’s lab since May 2017, as postdoctoral researcher, to extend my studies also to high-field fMRI and localisation of non-feedforward sources in primary visual cortex.

Publications

Bontempi, D., Benini, S.,  Signoroni, A., Svanera, M., Muckli, L. (2020). CEREBRUM: a fast and fully-volumetric Convolutional Encoder-decodeR for weakly-supervised sEgmentation of BRain strUctures from out-of-the-scanner. Medical Image Analysis62, 101688.

Svanera, M., Morgan, A.T., Petro, L.S., Muckli, L. (2020). An unsupervised deep neural network for image completion resembles early visual cortex fMRI activity patterns for occluded scenes. bioRxiv. 

Svanera, M., Savardi, M., Benini, S., Signoroni, A., Raz, G., Hendler, T., Muckli, L., Goebel, R., & Valente, G. (2019). Transfer learning of deep neural network representations for fMRI decodingJournal of Neuroscience Methods, 328, 108319. 

Svanera M., S. Benini, G. Raz, T. Hendler, R. Goebel, and G. Valente. “Deep driven fMRI decoding of visual categories”. In: NIPS Workshop on Representation Learning in Artificial and Biological Neural Networks (MLINI, 2016). url: https: //arxiv.org/abs/1701.02133.

Benini, S., M. Svanera, N. Adami, R. Leonardi, and K.A. Bálint. “Shot Scale Distribution in Art Films”. In: Multimedia Tools and Applications, 2016. doi: 10.1007/s11042- 016-3339-9.

Gordiychuk, A., M. Svanera, S. Benini, and P. Poesio. “Size distribution of micro bubbles for a venturi type bubble generator: effect of different parameters on bubble mean size, statistics of the distribution”. In: Experimental Thermal and Fluid Science, 2016. doi: 10.1016/j.expthermflusci.2015.08.014.

Svanera M., U. Riaz Muhammad, R. Leonardi, and S. Benini. “Figaro, hair detection and segmentation in the wild”. In: Proceedings of IEEE International Conference on Image Processing (ICIP, 2016). doi: 10.1109/ICIP.2016.7532494.

Svanera M., S. Benini, N. Adami, R. Leonardi, and K.A. Bálint. “Over-the-Shoulder Shot Detection in Art Films”. In: 13th International Workshop on Content-Based Multimedia Indexing (CBMI, 2015). doi: 10.1109/CBMI.2015.7153627.

 

Contact:

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Room 662, Dept of Psychology, 62 Hillhead Street, Glasgow, G12 8QB