Hey! Thanks for visiting and welcome to my website! My name is Ferran and I am a graduate researcher at University College London and The Alan Turing Institute. I am currently pursuing my PhD at the CoMPLEX centre, working in text mining, natural language processing (NLP), pharmacokinetics and machine learning. My career goal is to make an impact in the fields of healthcare and personalised medicine by developing computational models that help us to better understand the mechanisms underlying human diseases. Another aspect of my life is chess, my main hobby. I have been playing competitive chess for a long time and I am nowadays training different groups of chess students. In this web, you can find details about the research projects I have worked on so far.
Here you can find some of my reserach projects with their PDFs. In the MRes year at CoMPLEX I performed 3 interdisciplinary mini-projects across different labs at UCL and one final summer project. In addition, in this section you will find the poster developed during the summer project and my undergraduate dissertation thesis.
Autism spectrum disorder (ASD) is a neurodevelopmental condition with a complex pattern of deficits at multiple levels. Most findings report a high degree of heterogeneity among affected individuals, presenting an uneven pattern of deficits at the behavioural, genetic and neural levels across the whole spectrum. This study aimed to investigate the discriminant capacity of machine-learning approaches at the single-subject level when considering different aspects of behavioural and neural deficits of ASD subjects.
An essential cellular process is the exchange of molecules (cargoes) between organelles. However, the physical mechanisms by which certain groups of proteins are able to deform and cut the membrane of specific organelles to form transport vesicles is still not well understood. In this project, one subunit (outer coat) of a specific protein complex (COPII) was studied. A coarse-grained model was developed to investigate the key elements controlling the self-assembly of COPII outer coat subunits using molecular dynamic simulations.
Injury affects individuals’ health and fitness in a direct manner, and pain-related behaviours promote escaping, healing and recovery. Therefore, communicating pain might be an advantageous strategy in certain social contexts, but it can also come at a cost if predetors perceive vulnerability. For this project, an agent-based model was developed to study post-injury behaviour in a hierarchical community of wild chimpanzees, where the presence of dominance rank influences the adequacy of certain strategies.
fNIRS is a neuroimaging technique that measures the same physiological signal as fMRI but with fewer constrains on the environmental set-ups in which experiments can be performed. This is particularly useful in the study of autism spectrum disorder (ASD), where cognitive deficits become particularly evident in naturalistic situations. Here, multivariate pattern analyses were applied to identify characteristic patterns in the neural signal of 26 high-functioning ASD individuals in comparision to 27 controls.
Tuberculosis (TB) is currently one of the three main causes of death from infectious diseases worldwide. The development of new drugs and combinations of antibiotics to better deal with resistant strains of Mycobacterium tuberculosis (Mtb) has become a major priority in the treatment of TB. In this project, an individual-based model was developed to better understand the interaction of different antibiotics with Mtb.
This is the poster developed during my MRes dissertation at CoMPLEX.