NICHOLAS ROSSETTI

PhD Student

PhD program:: XXXVII
email: nicholas.rossetti@uniroma1.it
phone: 3392622513

supervisor: Alfonso Gerevini
co-supervisor: Ivan Serina

Research: Deep Learning techniques to tackle the Covid19 pandemic

My research area is the management of medical temporal data (Electronic Health Record). In detail, the study of Deep Learning techniques (Recurrent Neural Networks) applied to predict the mortality of patients affected by Covid19 during their hospitalization and their explanation.
A second study is the use of Deep Learning techniques in the IoT field for the anomalies detection, predictive and preventive maintenance.
My area of study is Deep Learning: neural networks, generative models (GAN, VAE and diffusion model) and large NLP models (Bert, GPT).

Research products

11573/1697118 - 2023 - Recurrent Neural Networks for Daily Estimation of COVID-19 Prognosis with Uncertainty Handling

Rossetti, Nicholas; Gerevini, Alfonso E.; Olivato, Matteo; Putelli, Luca; Chiari, Mattia; Serina, Ivan; Minisci, Davide; Foca, Emanuele - 04b Atto di convegno in volume

conference: 27th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (Athens)

book: Procedia Computer Science, vol 225, 2023 - ()

11573/1671189 - 2022 - Machine Learning Models for Predicting Short-Long Length of Stay of COVID-19 Patients

Olivato, M.; Rossetti, N.; Gerevini, A. E.; Chiari, M.; Putelli, L.; Serina, I. - 04b Atto di convegno in volume

conference: 26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022 (ita)

book: Procedia Computer Science, vol 207, 2022 - ()

11573/1671193 - 2021 - An Application of Recurrent Neural Networks for Estimating the Prognosis of COVID-19 Patients in Northern Italy

Chiari, M.; Gerevini, A. E.; Olivato, M.; Putelli, L.; Rossetti, N.; Serina, I. - 04b Atto di convegno in volume

conference: 19th International Conference on Artiﬁcial Intelligence in Medicine, AIME 2021 (AIME 2021)

book: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - (978-3-030-77210-9)