CV

Education

• Ph.D in Probabilistic Machine Learning applied to Personalized Medicine (Signal Processing and Communications Engineering PhD program)
  • Universidad Carlos III de Madrid, 2024 (expected)
• M.S. in Information Health Engineering
  • Universidad Carlos III de Madrid, 2020
• B.S. in Telecommunications Engineering (Mention in Signal Processing and Communications)
  • Universidade de Vigo, 2019

Work experience

• Predoctoral researcher (2022-today)
  • Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Grupo de Genética y Clínica de las Neoplasias Hematológicas y el Trasplante Hematopoyético
  • Biomarker discovery for Acute Myeloid Leukemia and CAR-T therapy complications.
  • Supervisors: Pablo M. Olmos and Carolina Martínez-Laperche.
• Research Assistant (2020-2022)
  • Universidad Carlos III de Madrid, Signal Theory and Communications Department
  • Probabilistic Machine Learning applied to biomarker discovery for Acute Myeloid Leukemia.
  • Supervisor: Pablo M. Olmos
• Data Scientist (2020-2022)
  • Evidence-Based Behavior (eB2)
  • Sleep prediction and characterization based on passively-sensed smartphone data.
  • Supervisor: Antonio Artés-Rodríguez
• Trainee and Telecommunications Engineer (Summer 2018)
  • Xtonebox
  • Product design and quality control

Publications

Identification of Predictive Models Including Polymorphisms in Cytokines Genes Associated with Post-Transplant Complications after Identical HLA-Allogeneic Stem Cell Transplantation

Paula Muñiz Sevilla, María Martínez-García, Mi Kwon, Rebeca Bailén, Gillen Oarbeascoa, Diego Carbonell, Julia Suárez González, María Chicano Lavilla, Cristina Andres, Juan Carlos Triviño, Javier Anguita, José Luis Díez-Martín, Pablo Martínez Olmos, Carolina Martinez-Laperche, Ismael Buño; Identification of Predictive Models Including Polymorphisms in Cytokines Genes Associated with Post-Transplant Complications after Identical HLA-Allogeneic Stem Cell Transplantation. Blood 2022; 140 (Supplement 1): 4795–4796. doi: https://doi.org/10.1182/blood-2022-168461

Heterogeneous Hidden Markov Models for Sleep Activity Recognition from Multi-Source Passively Sensed Data

Moreno-Pino, F., Martínez-García, M., Olmos, P. M., & Artés-Rodríguez, A. (2022). Heterogeneous Hidden Markov Models for Sleep Activity Recognition from Multi-Source Passively Sensed Data. arXiv preprint arXiv:2211.10371.

Sleep Activity Recognition and Characterization from Multi-Source Passively Sensed Data

María Martínez-García, Fernando Moreno-Pino, Pablo M. Olmos, and Antonio Artés-Rodríguez. Sleep activity recognition and characterization from multi-source passively sensed data. arXiv preprint arXiv:2301.10156.

Identification of Biomarkers and Risk Factors for Inmune Effector Cell-Associated Neurotoxicity Syndrome (ICANS) in CD19-directed CAR T-Cell Therapy: a Retrospective Machine Learning-based Analysis

M. Gómez-Llobell; M. Martínez-García; C. Serra-Smith; D. Gómez-Costas; G. Oarbeascoa; D.Carbonell; J. Anguita; A. Pérez-Corral; M. Pion; VA Pérez-Fernández; I. García- Fernández; M.Bastos; P. Fernández-Caldas; I. Gómez-Centurión; A. Alarcón; E. Catalá; D. Conde; J. Gayoso; P.Olmos; C. Martínez-Laperche; J. García-Domínguez; Y. Fernández; R. Bailén; M. Kwon; IIdentification of Biomarkers and Risk Factors for Inmune Effector Cell-Associated Neurotoxicity Syndrome (ICANS) in CD19-directed CAR T-Cell Therapy: a Retrospective Machine Learning-based Analysis. EHA2023.

Handling ill-conditioned omics data with deep probabilistic models

M. Martínez-García and P. M. Olmos, "Handling Ill-conditioned Omics Data with Deep Probabilistic Models," in IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2023.3279493.

Reviewing

• Artificial Intelligence and Statistics (AISTATS), 2023

Talks

Handling ill-conditioned omics data with deep probabilistic models.

June 08, 2022

Poster at 9ª Jornada de Investigación e Innovación IiSGM, Hospital G.U. Gregorio Marañón, Madrid, Spain

Handling ill-conditioned omics data with deep probabilistic models.

July 16, 2022

Poster at Cambdrige ELLIS Machine Learning Summer School, Cambrige University, Cambridge, UK

Application of Probabilistic Machine Learning models in clinical research. Case studies carried by our research group.

December 14, 2022

Seminar at Seminarios de Investigación Alberto Tejedor, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain

Teaching

Teacher Assistant in Natural Language Processing

Teacher Assistant in Neural Networks

Teacher Assistant in Deep Learning

Teacher Assistant in AI in Health

Master Thesis Co-director. ‘Unsupervised Genetic Study of Post-Transplant Complications after Identical HLA-Allogeneic Stem Cell Transplantation’

Master Thesis Co-director. ‘Deep Survival Analysis in AML patients’