About
I am Full Professor at the department of Computer Science and Technology of the University of Cambridge and I am a member of the Artificial Intelligence group. I am a member of the Cambridge Centre for AI in Medicine. Background: PhD in Complex Systems and Non Linear Dynamics (School of Informatics, dept of Engineering of the University of Firenze, Italy) and PhD in (Theoretical) Genetics (University of Pavia, Italy). More information is on my personal homepage Other Affliations: Fellow and member of the Council of Clare Hall College, member of Ellis, the European Lab for Learning & Intelligent Systems, I am member of the Academia Europaea; I am listed in www.topitalianscientists.org/Top_italian_scientists_VIA-Academy.aspx I am happy to receive enquiries for PhD applications. I have successfully completed the equality and diversity essentials. My research interest focuses on developing Artificial Intelligence and Computational Biology models to understand diseases complexity and address personalised and precision medicine. Current focus is on Graph Neural Network modeling to build predictive models based on the integration of multi scale, multi omics and multi physics data; integrate deep learning and mechanistic approaches; explainability and interpretability in medicine; exploiting short and long range communications in the human body, between cells and tissues and predict emerging mechanistic properties at systemic medicine level. Develop an AI-based medical digital twin to increase self-awareness; Develop an AI personal decision support system to increase social awareness.
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Experience
Education
Publication
Using AI explainable models and handwriting/drawing tasks for psychological well-being
This study addresses the increasing threat to Psychological Well-Being (PWB) posed by Depression, Anxiety, and Stress conditions. Machine learning methods have shown promising results for se...
Structure-based drug design with equivariant diffusion models
Structure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets. Generative SBDD methods leverage stru...
Dirac-Equation Signal Processing: Physics Boosts Topological Machine Learning
Topological signals are variables or features associated with both nodes and edges of a network. Recently, in the context of Topological Machine Learning, great attention has been devoted to...
ABCMB: Deep Delensing Assisted Likelihood-Free Inference from CMB Polarization Maps
The existence of a cosmic background of primordial gravitational waves (PGWB) is a robust prediction of inflationary cosmology, but it has so far evaded discovery. The most promising avenue ...
AnnoGCD: a generalized category discovery framework for automatic cell type annotation
The identification of cell types in single-cell RNA sequencing (scRNA-seq) data is a critical task in understanding complex biological systems. Traditional supervised machine learning method...
An end-to-end attention-based approach for learning on graphs
There has been a recent surge in transformer-based architectures for learning on graphs, mainly motivated by attention as an effective learning mechanism and the desire to supersede handcraf...
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems
Recent advances in computational modelling of atomic systems, spanning molecules, proteins, and materials, represent them as geometric graphs with atoms embedded as nodes in 3D Euclidean spa...
From Charts to Atlas: Merging Latent Spaces into One
Models trained on semantically related datasets and tasks exhibit comparable inter-sample relations within their latent spaces. We investigate in this study the aggregation of such latent sp...
Fate-mapping lymphocyte clones and their progenies from induced antigen-signals identifies temporospatial behaviours of T cells mediating tolerance
Tissue homeostasis is maintained by the behaviours of lymphocyte clones responding to antigenic triggers in the face of pathogen, environmental, and developmental challenges. Current methodo...
A Novel Mixed Convolution Transformer Model for the Fast and Accurate Diagnosis of Glioma Subtypes
Glioblastoma is the most common adult brain tumor, significantly impacts disability and mortality. Early and accurate diagnosis of glioma subtypes is essential, but manual categorization is ...
Projects
Ultrafast Holographic FTIR Microscopy
Funded by Horizon Europe
Chemometric Histopathology via Coherent Raman Imaging for Precision Medicine
Funded by Horizon Europe
MICA: Mental Health Data Pathfinder
Funded by University of Cambridge
Conference/Seminar/STTP/FDP/Symposium/Workshop
- Jun 2021
7th International Conference on Computational and Mathematical Biomedical Engineering
Politecnico di Milano ,
Cambridge, Cambridge, United Kingdom- Jun 2024
Denoising Probabilistic Diffusion Models for Synthetic Healthcare Image Generation
IEEE - Institute of Electrical and Electronics Engineers ,
Crete, GreeceCertificates
- By : BITS
- Event : BITS Bioinforma...
BITS Bioinformatics Italian Society
Membership
Member
University of Cambridge
From year 2023 to 2023examiner of ACS MPhil
University of Cambridge
From year 2023 to 2023Invited Position
DEGAS at GSP Workshop 2023: AI and Medicine: Graph and Hypergraph Representation Learning
IEEE Signal Processing Society
From year 2023 to 2023https://www.youtube.com/watch?v=IwnwOfcqo2I
OxML 2023
University of Oxford
From year 2023 to 2023https://www.oxfordml.school/2023
The 8th Cambridge-UTokyo Joint Symposium: Parallel Session 3 AI Trends, Opportunities and Threats
West Hub, Cambridge
From year 2023 to 2023https://sp.t.u-tokyo.ac.jp/UTokyo_Cam/activities/the-8th-cambridge-utokyo-joint-symposium-session-3-opportunities-and-threats/
Honours & Awards
Best student paper
AIAI2020
Year: 2020Listed in the top Italian Scientists
Italy
Year: 2019Doctoral and Master Thesis Guided
Deep concept reasoning: beyond the accuracy-interpretability trade-off
Ph.D Thesis (Ph.D. Thesis)
Institute : University of Cambridge
Area of research: Computer Science and Technology
Scholar9 Profile ID
S9-122024-1606868
Publication
(220)
Article Reviewed
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Citations
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Network
(12)
Conferences/Seminar
(2)