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GIORGIO ROFFO

PhD, Research Associate,

University of Glasgow

Pattern Recognition, Machine Learning, Social Signal Processing

Sir Alwyn Williams Building, G12 8RZ

Giorgio.Roffo@Glasgow.ac.uk

+44 141 330 4933

ABOUT ME


Giorgio Roffo is with the University of Glasgow where he is a Research Associate at the School of Computing Science. He received a European Ph.D. degree in computer science from the University of Verona, Italy. Previously, he was with the Italian Institute of Technology (IIT), Genoa, Italy.

His main research interests are in statistical pattern recognition and computer vision, mainly in deep learning, explainable AI, and feature selection. On these topics, he has published several papers in prestigious journals and conferences.


He acts as an Associate Editor of the ICPR 2020, the premier world conference in Pattern Recognition.


He is a reviewer for the premier journal of the field IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).


He has been awarded the CVPR 2019 Outstanding Reviewers Award (cvpr2019.thecvf.com).


He is in the technical program committee of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), the IEEE International Conference on Computer Vision (ICCV), IEEE European Conference on Computer Vision (ECCV), International Joint Conferences on Artificial Intelligence (IJCAI). 


His publishing track record shows one or more A* papers (top 1% of the SCImago SJR index) per annum while being associated with different institutions. 


        SELECTED PUBLICATIONS

  • Automating the Administration and Analysis of Psychiatric Tests: The Case of Attachment in School-Age Children. G.Roffo, D.-B.Vo, A.Sorrentino, M.Rooksby, M.Tayarani, S. Di Folco, H. Minnis, S.Brewster and A.Vinciarelli. In ACM CHI Conference on Human Factors in Computing Systems, (ACM CHI 2019) [pdf][bibtex]
  • Discrete-time evolution process descriptor for shape analysis and matching. Melzi, S., Ovsjanikov, M., Roffo, G., Cristani, M. and Castellani, U. ACM Transactions on Graphics, (TOG 2018). [pdf][bibtex]
  • Infinite Latent Feature Selection: A Probabilistic Latent Graph-Based Ranking Approach. G. Roffo, S. Melzi, U. Castellani, and A. Vinciarelli. In Conf. IEEE International Conference on Computer Vision (ICCV 2017). [pdf][bibtex]
  • Infinite Feature Selection. G. Roffo, S. Melzi and M. Cristani. In Conf. IEEE International Conference on Computer Vision (ICCV 2015). [pdf][bibtex]
  • Online Feature Selection for Visual Tracking. G. Roffo, S. Melzi. In Conf. The British Machine Vision Conference (BMVC 2016). [pdf][bibtex]
  • Ranking to Learn: Feature Ranking and Selection via Eigenvector Centrality. G. Roffo, S. Melzi. Springer Book Chapter: New Frontiers in Mining Complex Patterns, 2017. [pdf][bibtex]

 

LATEST NEWS


                      SICSA PECE Grant 2019

                      July 2019


Awarded a SICSA Postdoctoral and Early Career Researcher Exchanges (PECE). 



                     MATLAB Central Coin 2016

                     April 10, 2017


Matlab FileExchange - Recognition for Outstanding Contributions (2016) in Feature Selection. The  Feature Selection Library (FSLib) received more than 3,000 unique downloads in 2016, avg. ~300 downloads pcm (see FSLib online).

CVPR 2019 Reviewer Award

December 2019


 CVPR 2019 Outstanding Reviewers Award

GIORGIO ROFFO


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