Imperial College London


Faculty of MedicineInstitute of Clinical Sciences

Research Associate in Data Science and Machine Learning



p.inglese14 Website




Robert Steiner MR unitHammersmith Campus





I am currently employed as a Research Associate in Data Science and Machine Learning in the Cardiac Computational Imaging Group under the supervision of Prof Declan O'Regan. My role is integrating medical imaging, genomics and clinical data to unveil clinically relevant subgroups of patients affected by cardiac diseases.

In the recent years, I have worked on designing and applying mathematical models of spatial metabolomics data (mass spectrometry imaging). Specifically, I have been responsible for data acquisition optimisation for DESI-MS imaging and the integration of multi-modal spatial data.

I have been awarded a pre-Bologna Laurea degree (eq. to BSc MSc) in Physics (with specialisation in Theoretical Physics) at the Universita' Degli Studi di Bari, Italy. As member of Prof. Roberto Bellotti group, I have worked on applied machine learning for the automatic segmentation of the human hippocampus from structural MRI scans, as part of the Alzheimer's Disease research programme.

As a PhD student, under the supervision of Prof. Robert C Glen and Prof. Jeremy K. Nicholson, I have worked on robust signal processing pipelines for the pre-processing of DESI-MS imaging data, and the application of unsupervised learning techniques to understand the molecular heterogeneity of cancer.

I have continued my research work on DESI-MS imaging data in Prof. Zoltan Takats group. In particular, I have introduced a molecular colocalization approach for DESI-MS imaging data. During this period, I have also started designing and developing optimisation procedures aimed at integrating quality control and analytical references in DESI-MS imaging experiments, to quantify and disentangle the biological from the technical variability of the measured signals.

During 2020, I have worked at the Francis Crick Institute in Dr Paola Scaffidi lab, where I have applied unsupervised learning on scRNA-seq data to model the functional role of the epigenetic regulatory network in cancer resistance and plasticity.



Huang HX, Inglese P, Tang J, et al., 2024, Mass spectrometry imaging highlights dynamic patterns of lipid co-expression with Aβ plaques in mouse and human brains., J Neurochem

Curran L, Simoes Monteiro de Marvao A, Inglese P, et al., 2023, Genotype-phenotype taxonomy of hypertrophic cardiomyopathy, Circulation: Genomic and Precision Medicine, Vol:16, ISSN:2574-8300, Pages:559-570

Kreuzaler P, Inglese P, Ghanate A, et al., 2023, Vitamin B5 supports MYC oncogenic metabolism and tumor progression in breast cancer., Nat Metab, Vol:5, Pages:1870-1886

Dannhorn A, Doria ML, McKenzie J, et al., 2023, Targeted Desorption Electrospray Ionization Mass Spectrometry Imaging for Drug Distribution, Toxicity, and Tissue Classification Studies, Metabolites, Vol:13

Loukas I, Simeoni F, Milan M, et al., 2023, Selective advantage of epigenetically disrupted cancer cells via phenotypic inertia, Cancer Cell, Vol:41, ISSN:1535-6108, Pages:70-87.e14

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