I was born in Argentina and from an early age, I was interested in medicine and understanding how allergies work. Pursuing a career in medical research, I studied a BSc in Biochemistry in Madrid where I further refined my interests into studying the immune system and its diverse responses, especially in the context of infectious diseases. I had the opportunity to do my BSc thesis in genetic factors driving CD8+ memory T-cells where I conducted laboratory and computational experiments. Seeing the potential of in-silico approaches I studied an MSc in Bioinformatics and Systems Biology in Copenhagen. In this period, I learned Machine Learning and had the opportunity to use it to explore MHC-TCR interactions using Deep Learning approaches for my MSc thesis. Currently, I am doing my PhD at Rigshospitalet/University of Copenhagen in applying explainable Machine Learning methods, not only for prediction but also for scientific insights in patients with immune dysfunction and viral infections (HIV and SARS-CoV-2). Methodologically my interests are in survival analysis, representation learning, causal inference and explainable Artificial Intelligence. My research interests are in applying statistical and computational tools to understand the complexity of the immune system and factors that could drive it to dysfunctional states. I have a growing interest in quantifying the impact of Psychogenic and Neurogenic Stressors on immune function.
- PHD STUDENT IN BIOINFORMATICS AND BIOSTATISTICS
March 2019 – Present : University of Copenhagen
Thesis: Interpretable Machine Learning for precision medicine of patients with immune dysfunction
- MSC. BIOINFORMATICS AND SYSTEMS BIOLOGY
Sept 2015 – July 2017 : Technical University of Denmark
GPA: 10/12 | Thesis: Computational analysis of TCR – pMCH interactions (12 / 12)
- BSC. BIOCHEMISTRY
2011 – 2015 : Autonomous University of Madrid
GPA : 8 / 10. Specialization in Molecular Biomedicine.
- PHD FELLOW IN HEALTH AND MEDICAL SCIENCES
CHIP / PERSIMUNE – RIGSHOSPITALET
May 2018 – Present : Copenhagen, DENMARK
Modelling of omics and clinical data for precision medicine.
• Development of explainable machine learning approaches for survival analysis in SARS-Cov-2+ patients.
• Research on biological representation of patients with immune dysfunction (e.g. HIV) using unsupervised learning.
•Statistical and computational support in clinical and research projects.
- RESEARCH ASSISTANT IN BIOINFORMATICS
CENTER FOR TRANSLATIONAL NEUROMEDICINE
November 2017 – April 2018 : University of Copenhagen, DENMARK
Statistical and computational analysis of NGS and omics data of neurological disease models based on iPSCs from patients. Development of tools and workshops on statistical analysis and programming.
- BIOINFORMATICS DEVELOPER
SYMPHOGEN | DEPARTMENT OF ANTIBODY DISCOVERY
April 2016 – June 2017 : Ballerup, DENMARK
Student job as python developer of NGS based Immunoglobulin sequence analysis tools, local web documentation platforms, automated pipelines for Computerome and local HPC management.
UNDERGRADUATE RESEARCH :
IMMUNOINFORMATICS AND DEEP LEARNING
Center for Biological Sequence Analysis
July2016 – July2017 : Technical University of Denmark
Student projects and MSc thesis under the supervision of Morten Nielsen. Application of Deep Learning (LSTMs, CNNs) and Semi-supervised methods for MHC binding prediction based on protein sequences and sub-celullar localization
CHIP-SEQ AND BIOINFORMATICS – MEMORY CD8+ T CELLS
DEPARTMENT OF CELL BIOLOGY AND IMMUNOLOGY
June 2014 – July 2015 : CBMSO-CNB | Madrid, SPAIN
Internship during my BSc thesis at Margarita Del Val’s group. Conserved regulatory network of the transcription factor Eomesodermin and Chromatin Immunoprecipitation optimization in CD8+ T lymphocytes
Python • R • LATEX • HPC• Unix • Machine Learning • Survival Analysis • Statistics
TensorFlow • MySQL • Flask HTML • CSS • Sphinx Familiar :
Spanish and English
Italian, French and Danish
RELEVANT COURSES :
- PhD :
• Causality • Scale Validation
• Fairness and bias in Machine Learning
• University Pedagogy
• Bayesian Analysis
• Advanced statistics in Epidemiology
- MSC :
• Immunological Bioinformatics
• Machine Learning
•Big Data Analysis
• Systems Biology
• High Performance Computing
• Protein structure modelling
• Immunology • Virology
• Clinical Microbiology • Genetics