I am a postdoctoral research fellow in the Machine Learning and
holding the AstraZeneca Data Science Fellowship
. My project focuses on subgroup analysis in clinical trials by developing an artificial intelligence and machine learning framework, to enable robust rankings of putative predictive biomarkers of treatment efficacy.
Prior to that, I did my PhD in the School of Computer Science
under the supervision of Dr Gavin Brown
During my PhD and my postdoctoral career, I have worked in various areas of machine learning, while my main research interests are in the area of information theoretic feature selection in different learning environments and particularly focusing on medical and health informatics applications.
Areas of interest:
, Feature Selection
, Multi-label learning
, Positive-unlabelled learning
, Semi-supervised learning
New publication: "Algorithmic challenges in Big Data analytics"
, accepted in ESANN 2017
New publication: "On the Use of Spearman's Rho to Measure the Stability of Feature Rankings"
, accepted in IbPRIA 2017
New publication: "Exploring the consequences of distributed feature selection in DNA microarray data"
, accepted in IJCNN 2017
New publication: "Disentangling Prognostic and Predictive Biomarkers Through Mutual Information"
, accepted in Informatics for Health 2017
New publication: "Ranking Biomarkers Through Mutual Information"
, accepted in NIPS 2016
Workshop on Machine Learning for Health (ML4HC
My PhD got the Best Thesis Prize
of the School of Computer Science at the University of Manchester 2016 (sponsored by IBM).
New publication: "Estimating mutual information in under-reported variables"
, accepted in PGM 2016
New publication: "Markov blanket discovery in positive-unlabelled and semi-supervised data"
, accepted in ECML/PKDD 2015
. Acceptance rate 89/383 (23.2%).
Gave the tutorial "An introduction to statistical testing and estimation"
for Computer Science PhD students of the University of Manchester, details here
Got the runner-up best paper prize
in the School of Computer Science at the University of Manchester 2016 (sponsored by IBM).
New publication: "Statistical Hypothesis Testing in Positive Unlabelled Data"
, accepted in ECML/PKDD 2014
. Acceptance rate 115/483 (23.8%).
New publication: "Information theoretic feature selection in multi-label data through composite likelihood"
, accepted in SSPR 2014
in Edinburgh, UK.
I would like to thank the one and only Sarah Nogueira
for helping me create this webpage :)