Research areas
Machine Learning and
Computational Intelligence.
Biomedical, bioinformatics, business, and other
applications of ML and CI.
Research projects
Until 2023 I worked, as amain
researcher (investigador principal - IP)in KAPPA-AIM,
KAPPA-AIM 2 and ML-PROMOLDYN
(investigating, using deep learning methods, the molecular
dynamics of GPCR proteins) Spanish AEI
TIN area research projects in the area of
pharmacoproteomics.
From 2023, I am working as IP of eyeAI(Machine Learning-based decision support
in ophthalmology from multi-modal retinal images)
in the area of Ophthalmology, in collaboration with Dr.
Javier
Zarranz (Institut Clínic de Oftalmologia (ICOF), Hospital
Clínic de Barcelona).
Some past special sessions/workshops
over five years old: ESANN
2018 (Bruges, Belgium) "Deep
Learning in Bioinformatics and Medicine", IWBBIO
2018 (Granada, Spain) "Interpretable
Models in Biomedicine and Bioinformatics", IJCNN
2017 (Anchorage, Alaska,
USA) "Machine Learning for Enhancing
Biomedical Data Analysis", and NIPS
2017 (Long Beach, CA, USA) "Transparent
and interpretable Machine Learning
in Safety Critical Environments"
Research students
Already
doctors Iván
Olier Variational Bayesian
Algorithms for Generative Topographic Mapping and its
Extensions. Awarded, Dec'08. Raúl
Cruz Generative Manifold Learning for
the Exploration of Partially Labeled Data. Awarded, Sept'09 Carlos
Julio ArizmendiSignal
Processing Techniques for Brain Tumour Diagnosis from
Magnetic Resonance Spectroscopy Data. Awarded, Feb'12
Sandra Ortega-MartorellOn the Use of Advanced Pattern
Recognition Techniques for the Analysis of MRS
and MRSI Data in Neuro-Oncology. Awarded,
June'12 (UAB) Vicent
RibasOn the Intelligent
Management of Sepsis at the Intensive Care Unit. Awarded January'13 David GarcíaExploration of
Customer Churn Routes Using Machine
Learning Probabilistic Models.Awarded April'14 Alessandra TosiVisualization and Interpretability in Probabilistic Dimensionality Reduction Models.Awarded
December '14[ESTEVA-VIVANCO
FAMILY PRIZE: BEST PHD THESIS ON ARTIFICIAL INTELLIGENCE
(accessit)] Albert VilamalaMultivariate Methods for
Interpretable Analysis of Magnetic Resonance Spectroscopy
Data in Brain Tumour Diagnosis. Awarded December '15 Victor Mocioiu
Towards an automated
analysis pipeline for MRS data: a prototype based on brain
tumors. Awarded, July'16 (UAB) Martha Ivón Cárdenas
A Computational Intelligence Analysis of G
Protein-Coupled Receptor Sequences for
Pharmacoproteomic Applications. Awarded, September'17 Caroline
KönigAnalysis of Class CG-Protein Coupled Receptors Using
Supervised Classification Methods. Awarded, October'18 Yanisleydis Hernández
Desarrollo de Técnicas de Control de
Calidad Automatizado para la Mejora de la Clasificación de
Tumores Cerebrales a partir de sus Espectros de Resonancia
Magnética Usando Convex NMF. Awarded,
January'22
(UAB) Gulnur
UnganOn the Use of Machine Learning
Techniques for the analysis of MRS and MRSI Data from Brain
Tumors. Awarded,
November'23 (UAB)
Doctors-to-be
Ricardo Fernández (XAI in Banking domain)
Carla Pitarch
(Glioblastoma analysis / Neuroncology)
Eurecat Mario
Alberto Gutiérrez Mondragón (MD data analysis using DL / Proteomics) Juan
Manuel López Correa (MD data analysis using DL
/ Proteomics)
MSc
Jorge
S. Velazco:The Effect of
Noise and Sample Size in the Performance of an Unsupervised
Feature Relevance Determination Method for Manifold Learning.
Awarded, June'08 Julià Amengual:Advanced
Statistical Machine Learning Methods for the Analysis of
Neurophysiologic Data with Medical Application. Awarded,
June'10 Martha
I. Cárdenas:Kernel-Based
Manifold Visualization of GPCR Sequences. Awarded,
June'11 Àngela
Martín: Cartogram Representations of Self-Organizing
Virtual Geographies. Awarded,
September'13 Stavros
Koulas:
Using Fuzzy Methods for Rule Extraction in the
Discrimination of Class C GPCR Subtypes from their Subsequences .
Awarded, September'14 Christiana
Halka: Class C GPCR Metabotropic Glutamate Receptor
Subtype Discrimination Using Computational Intelligence Methods. Awarded, November'14 Emil
Racec: A Stochastic Approach for Automatic Layout
Synthesis in Interior Design, Using a Learning-Based Scoring
Function. Awarded, July'16 Stefania
Budulan: Probabilistic Methods for Furnishing Bedrooms in
Interior Design: Bayesian Networks for occurrence Modeling and
GMMs for Furnishing Arrangement. Awarded,
July'16 Carla
Morant: Random Forest-Based Discrimination of G
Protein-Coupled Receptors. Awarded,
September'16 (Universitat de
Vic - UVic) Carles Morales: Investigating
Prognostic Factors in Sepsis Using Computational Intelligence
Methods. Awarded, October'16 Ilmira Terpugova Protein
Classification from Primary Structures in the Context of Database
Biocuraton. Awarded May'17 Elva
Sinaí Gutiérrez: A Virtual Reality Mobile App for
Exploratory Data Navigation in Data Mining Education. Awarded, July'17 Helen Byrne: Using
peptidomics and machine learning techniques to predict
mortality of patients with septic shock. Awarded April'18 Ahsan Bilal: Big Data Analytics for
Obesity Prediction. Awarded April'18 Alex Aushev: Clinical assessment of Shock through
Machine Learning techniques. Awarded
April'18 Olga
Fetisova: Store
layout optimization for a luxury fashion retailer. Awarded June'18 Andrés di
Giovanni: Análisis de Datos para la Detección de
Anomalías en Procesos de Soldadura, Awarded
June'18 Ángel Astudillo:Advanced Models
of Visualization of Cosumption Curves for Electricity
Supply Companies.Awarded October'18 Xavier
Schmoor:Providing
Data Support to Health and Social Care Small and Medium-sized
Enterprises as part of the Big Data Corridor team at Birmingham
City University. Awarded October'18 Daniel Duato: Decoding neural
representations of auditory frequency sweeps in the human
brain using computational intelligence methods.
Awarded October'18 Malika
Ibrahimova: Predicting
financial distress through Machine Learning. Awarded January'19 Adrián Bazaga: Genome-wide investigation of gene-cancer
associations using machine learning on biomedical data for the
prediction of novel therapeutic targets Awarded
July'19 Rachel Rapp: A
framework for Artificial
Data Generation Based on Anatomical Differences for
Electroencephalography-Based Brain-Computer Interfaces
enhancing subject-independent classification by
forcing anatomical invariance. Awarded
July'19 Nafiseh
Banirazimotlagh: Classification
of neurodegenerative diseases using AI methods. Awarded October'20
Ricard Meyerhofer Parra: Forecasting
football results. Awarded October'20
Damián Rubio Cuervo: Exploratory
analysis of the molecular dynamics of Cannabinoid
receptor proteins. Awarded October'20
Joel Cantero Priego: Predicting
the number of likes on Instagram with TensorFlow. Awarded October'20
Ann Christin Rathert:Prediction
of Diabetic Retinopathy (DR), DR Progression and Relationship
with Clinical Data using Optical Coherence Tomography
Angiography (OCTA), OCT and Retinal Fundus Images Awarded October'21
Guifré Ballester Basols:Text
summarization of online hotel reviews with sentiment analysis.
Awarded October'21 Anass
Benali Bendhamane:Using
machine learning on the sources of retinal images for
diagnosis by proxy of diabetes mellitus (DM) and diabetic
retinopathy (DR). Awarded June'21 Sofía Orfelia Nuñez:
Sistema de
Recomendación de Canciones. Awarded January'22 Albert Mercadé:Analytical Tools
for Retail Marketing. Awarded
January'22 Aleix
Dalmau: Machine
Learning for SaaA
Observability and Anomaly
Detection. Awarded
June'22 Gabriela
León:
Data
visualization and
forecasting of a
clothing
representative sale: A
real case from a
Brazilian brand. Awarded June'22 Yazmina Zurita: Prediction of Diabetic
Retinopathy
(DR), DR
Progression
and
Relationship
with Clinical
Data using
Optical
Coherence
Tomography
Angiography
(OCTA), OCT
and Retinal
Fundus Images.
Awarded
January'23 Demokan Çoban: Application of Generative Models
on Modeling
Biological
Molecules. Awarded
May'23
Goran
Kirov: Comparing
Algorithms for
Predictive
Data
Analytics.
Awarded
June'23
Marta
Gil García:
Using deep
learning to
predicting
Diabetic
Retinopathy in
OCTA images
adding
clinical
information. Awarded October'23
Main research collaborators
Paulo
JG
Lisboa (Neural Computation.
Liverpool John Moores University. Liverpool, UK)
Wael
El-Deredy (Cognition and Cognitive
Neuroscience. The University of Manchester. Manchester, UK)
