Paolo Andreini is a researcher at the University of Siena (Italy), he has a degree in computer science and a PhD in Information Engineering and Science. His PhD thesis focused on proposing new multi-stage generative models that can be trained from very limited datasets and can be used as data augmentation. His research activity focuses on artificial intelligence with applications in computer vision, generative models and bioinformatics. He is the author of over 29 publications in international journals and conferences.
He has been involved in different projects, often cooperating with clinicians and industries, with particular application to the automatic analysis of biomedical images. In particular, his main research topics include the analysis of biomedical images, object detection, semantic segmentation, weakly-supervised and unsupervised learning and generative models. From a practical point of view, he worked on a variety of domains including agar plates, retinal images, skin lesions, brain MRI, oocites images, kidney histological images, text detection and recognition, ribo-seq profiles etc.