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Ferran Gonzalez Hernandez

PhD student at UCL & The Alan Turing Institute

About Me

Hey! Thanks for visiting and welcome to my website! My name is Ferran and I am a PhD student at University College London and The Alan Turing Institute. I work on Natural Language Processing (NLP) and Machine Learning (ML), focusing on extracting biomedical information from the scientific literature. During my PhD, I interned at BenevolentAI as a Machine Learning Researcher, working on biomedical Entity Linking. Previously, I obtained an MRes in computational biology at the CoMPLEX centre, and a BEng in Bioengineering at Universitat Politècnica de Catalunya.


My research interests lie in the application of deep learning to tackle current challenges in biomedical research. I am particularly interested on developing practical ML solutions that improve the development of new therapeutics. During my PhD, I worked on NLP models for Named Entity Recognition, Entity Linking and Relation Extraction for processing Pharmacokinetic literature. If you want to see some of the applications I developed, check out this site. On my free time I enjoy playing chess and rock climbing.

Master Projects

Here you can find some of my master 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.

An integrated Approach to characterize Autism Spectrum Disorder

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.

Modelling the self-assembly of COPII outer coat

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.

Modelling post-injury behaviour in chimpanzees using artificial life

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.

Investigation of typical and atypical functional activation patterns in Autism Spectrum Disorder

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.

Modelling Mycobacterium Tuberculosis cultures

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.

Poster presentation session

This is the poster developed during my MRes dissertation at CoMPLEX.