Welcome to my Business card
Business Executive | Digital Ambassador | Innovation Leader
Business Executive | Digital Ambassador | Innovation Leader
I began my journey in science with a strong foundation in Biochemistry, which initially shaped my analytical thinking and attention to detail. After completing my degree, I discovered a passion for technology and its potential to transform our understanding of the world. This led me to pursue a Master's in Bioinformatics—a field that allowed me to blend my scientific background with cutting-edge computational methods.
Building on this interdisciplinary approach, I went on to earn a Ph.D. in Computer Science. Throughout my academic career, I explored topics related to digital transformation and artificial intelligence, gaining insights into how technology can drive innovation. Over the years, I've had the opportunity to work for five years in research, where I honed my analytical skills and deepened my understanding of complex systems. More recently, I have spent four years in the industry, applying these insights to practical challenges in digitalization and AI.
I am passionate about staying at the forefront of technological advancements and continually seek out new methods to add tangible value to the projects I work on. I see every challenge as an opportunity to learn and grow, and I thrive when I'm exploring areas that are new to me. My approach is focused on proactive problem-solving—finding solutions rather than dwelling on problems or assigning blame.
Ultimately, I believe that the integration of scientific rigor with technological innovation can lead to transformative breakthroughs. I am committed to leveraging my diverse background to drive progress and create meaningful impact wherever I work.
An innovative web server that transforms high-throughput gene lists into captivating, interactive insights. With its sleek, user-friendly interface, GSAn leverages the power of the Gene Ontology and its weekly-updated annotations to distill complex gene sets into clear, synthetic summaries that bring your research to life.
EPPO codes revolutionize plant and pest identification by offering a concise, universal language that bridges industry and regulation. To overcome rigid data extraction challenges, BASF developed an internal ontology that maps and enriches these codes with external insights (like NCBI Taxon), driving smarter, more agile crop protection solutions.
What started as a seed idea has evolved into a robust computer vision solution that significantly enhances usability and drives greater user engagement across our digital platforms. By integrating seamlessly with complementary systems, this solution fosters improved collaboration and delivers considerable cost efficiencies, all while adhering to the highest standards of quality
I lead a team of Data Science and DevOps professionals, developing comprehensive strategies and roadmaps that align with all stakeholders' interests. In this role, I collaborate closely with domain experts and work with BASF's Digitalization of R&D teams, while also managing external partnerships with universities and research institutes. Additionally, I review project requirements, oversee financial planning, and optimize staffing to ensure consistent delivery and effective prioritization of initiatives.
I led a dedicated team of experts focused on developing robust ontologies tailored for agricultural applications. I developed comprehensive strategies and roadmaps that aligned with the diverse interests of stakeholders across both research and industry. I collaborated closely with agricultural domain experts and worked with Digitalization of R&D teams to drive innovative solutions in crop protection and agronomy. Additionally, I managed external partnerships with universities and research institutes, fostering collaborative research that enriched our ontological frameworks. I also reviewed project requirements, oversaw financial planning, and optimized staffing to ensure consistent delivery and effective prioritization of our initiatives.
During my postdoctoral research, I spearheaded the development of an innovative method that combines semantic similarity with machine learning to enhance gene prediction by controlling complex traits in Norwegian pine. This project involved integrating gene network analysis with advanced annotation techniques to refine predictive models and deepen our understanding of underlying genetic mechanisms. My role required a blend of computational expertise and biological insight, ultimately contributing to more precise trait control and advancing research in forest genomics.
I focus on predicting viral DNA sequences using advanced machine learning and bioinformatics techniques. My work supports early detection and rapid diagnosis of viral infections, contributing to more effective treatment strategies and improved patient outcomes.
I developed innovative computational methods for the synthetic annotation of gene sets by leveraging bioinformatics, ontology frameworks, and semantic similarity techniques. This approach enhances functional annotation and streamlines the integration and visualization of complex genetic data, providing a comprehensive tool for gene set analysis.
Universidad Internacional de la Rioja (UNIR)
Universidad de Murcia
Universidad de Murcia