Review effort does not always come unnoticed.. Happy to be listed in the top third of the ICML reviewers.
Author Archives: DAVIDE BACCIU
New JMLR paper
Couldn’t think of a better venue for my 99th research paper than the Journal of Machine Learning Research. Check out our work on deep and probabilistic learning for graphs. Terrific job by Federico Errica!
IEEE Service Award
Extremely honoured to have been nominated among the 2019 Outstanding Associate Editors of the IEEE Transactions on Neural Networks and Learning Systems.
Glad to see that the effort dedicated to reviewing and editorial services does not always go unnoticed!
Deep Learning for graph on Neural Networks
Very proud of the last effort from our group! Our tutorial paper on deep learning for graphs will be published as an invited paper on the Neural Networks journal!
Check out a preliminary version on the Arxiv!
COVID-19 Task Force
If you work in AI and you are willing to contribute to the worldwide fight against COVID-19 please consider joining the CLAIRE-COVID19 task force. I am coordinating the workgroup on omics, chemical and clinical data processing.
You can have a look at the first result of our pan-european collaboration which has been released here: it is a curated repository of protein-viral-drug-disease interactions for helping research in drug repurposing, bio-informatics, etc.
Stanford-UNIPI thesis
Congratulations to Alessio Gravina, for his joint Stanford-UNIPI thesis on deep learning for graphs hitting the news:
Graduation day
While classes are suspended, University is still open and today we had a great (epidemiologically-correct) graduation day with 5 of my students having discussed their B.Sc. and M.Sc. theses. Great works on graph neural networks applied to biochemistry and social-network data, tree transductions in image captioning, machine vision and genomic data processing. Congratulations to them all!
- Alessio Gravina, Machine Learning prediction of compounds impact on Schizoprenia treatment, co-supervision by Corrado Priami and Kevin V. Grimes (Stanford University), M.Sc. in Computer Science & Artificial Intelligence
- Davide Serramazza, Image captioning with structure generation, M.Sc. in Computer Science & Artificial Intelligence
- Francesco Bachini, On the use of sequential learning models to estimate natural selection on Hiv from clinical samples, co-supervision by Matteo Fumagalli (Imperial College London), M.Sc. in Data Science and Business Informatics,
- Gabriele Tenucci, A neural network-based intelligent filter for Youtube videos, B.Sc. in Computer Science
- Lorenzo Gazzella, Analysing privacy-risks in social networks by deep learning for graphs, co-supervision with A. Monreale, B.Sc. in Computer Science
Best PhD project Award
Many congratulations to Francesca Lizzi for winning the best Ph.D. project award at BIOSTEC 2020 with her thesis project on “Deep-learning based analysis of mammograms to improve the estimation of breast cancer risk”. Terrific job!
ISPR course kickoff
The 2019/20 edition of the ISPR course will start with the first lecture on
THURSDAY 20 FEBRUARY 2020 – h. 14-16
CLASSROOM L1 – POLO FIBONACCI (First Floor)
See you there!
Big @ESANN2020
Great success at ESANN this year, with 5 papers in: congrats to Daniele, Francesco, Federico and Marco!!