pyHaiCS: Python in Hamiltonian for Computational Statistics
Library for Hamiltonian-based Markov-Chain Monte-Carlo in Computational Statistics Applications.
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portfolio
publications
Analysing the Impact of Images and Text for Predicting Human Creativity Through Encoders
Published in Proceedings of the 11th International Conference on Information and Communication Technologies for Ageing Well and e-Health ICT4AWE - Volume 1, 15-24, 2025
This paper belongs to a series of publications exploring the intersection between neuroscience, human creativity, and Machine Learning.
A Bayesian Approach to Modeling Tamoxifen Resistance in Breast Cancer Cells Through Adaptive Hamiltonian Monte Carlo Posterior Sampling
Published in University of Deusto, Bilbao, Spain, 2025
My BSc thesis, supervised by Dr. Aitor Almeida and done in collaboration with the Basque Center for Applied Mathematics (BCAM), focuses on the application of Bayesian methods to model tamoxifen resistance in breast cancer cells.
A Transformer-Based Approach to Analyzing Public Opinion and Political Trends
Published in Proceedings of the 10th International Conference on Smart and Sustainable Technologies (SpliTech) - Volume 1, 1-6, 2025
This paper presents a novel approach to analyzing public opinion and political trends using transformer-based models and unsupervised topic modeling techniques.
A Deep Learning Approach to Artifact Removal in Transcranial Electrical Stimulation: From Shallow Methods to Deep Neural Networks and State Space Models
Published in Journal of Neuroscience, 2025
This paper presents a novel approach to denoising EEG signals contaminated by artifacts from transcranial electrical stimulation (tES) using deep learning techniques. We explore various architectures, including Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and state space models, to effectively separate neural signals from stimulation-induced artifacts.
Differential Privacy: Gradient Leakage Attacks in Federated Learning Environments
Published in ArXiv, 2025
This paper presents a comprehensive study on the vulnerabilities of federated learning systems to gradient leakage attacks, emphasizing the need for robust privacy-preserving mechanisms.
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Introduction to Computers (ICO)
1st Year Undergraduate Course, University of Deusto (Faculty of Engineering), 2025
Introduction to Computers (ICO) course for first-year undergraduate students at the University of Deusto. The course covers fundamental concepts of computer science, including hardware, software, programming basics, and an introduction to shell scripting and assembly language. Hands-on labs and projects are integral parts of the curriculum, providing students with practical experience designed to reinforce theoretical knowledge.
Natural Language Processing (NLP)
4th Year Undergraduate Course (Elective), University of Deusto (Faculty of Engineering), 2025
Natural Language Processing (NLP) course for fourth-year undergraduate students at the University of Deusto. The course covers semantic textual representations such as Word2Vec, GloVe, topic vectors, contextual embeddings; modern transformer-based architectures, and key NLP applications and tasks such as information extraction, sentiment analysis, machine translation, question answering, etc.