Lemuel Puglisi

University of Catania, Queen Square Analytics.

profile_picture.jpeg

Department of Mathematics

and Computer Science

Office address:

Stanza 200, I blocco

PhD student at University of Catania and Imaging Research Scientist at Queen Square Analytics.

Short bio. I graduated cum laude with a Bachelor’s degree in Computer Science from the University of Catania in July 2021, and I have completed my Master’s degree in Computer Science, specializing in data science, also with a cum laude distinction from the same institution in April 2023. I started my internship at Queen Square Analytics in September 2022 and have joined the QSA team as an imaging research scientist since March 2023. From August 2023, I have started my PhD at University of Catania on data-driven neurodegenerative disease progression modeling under the supervision of Prof. Daniele Ravì.

My research interests center around the application of artificial intelligence (AI) to medical imaging with a focus on the study of neurodegenerative diseases, particularly Multiple Sclerosis and Alzheimer’s disease.

news

May 13, 2024 Brain Latent Progression (BrLP) early-accepted (top 11%) at MICCAI 2024
Nov 24, 2023 Our work on Automatic Artifact Detection has been published in the Journal of Medical Image Analysis (MEDIA).
Jul 28, 2023 Won the Archimede Award (XIX edition) from University of Catania
Jul 7, 2023 Won a PhD scholarship at University of Catania.
Apr 28, 2023 Received Master’s degree in Computer Science

selected publications

2024

  1. brlp-plot-2.gif
    Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge
    Lemuel Puglisi, Daniel C Alexander, and Daniele Ravì
    In International Conference on Medical Image Computing and Computer Assisted Intervention, 2024
    🌟 Early-Accept (top 11%)

2023

  1. deepbrainprint-plot.png
    DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification
    Lemuel Puglisi, Arman Eshaghi, Geoff Parker, and 3 more authors
    In Medical Imaging with Deep Learning, 2023