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<title>Carlos Fernandez-Lozano</title>
<meta name="description" content="Associate Professor at University of A Coruña (Spain), PhD and MSc in Computer Science, MSc in Bioinfomatics and Biostatistics. Main research interests include feature selection, kernel-based techniques, machine learning, deep learning, support vector machines, data integration, computer vision and complex biological systems.
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<h1 class="post-title">Carlos </br> <strong>Fernandez-Lozano</strong></h1>
<h5 class="post-description"><a href="https://pdi.udc.es/en/File/Pdi/QY8UJ">Associate Professor</a>. Universidade da Coruña (UDC)</h5>
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<article class="post-content Carlos </br> <strong>Fernandez-Lozano</strong> clearfix">
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<p>Office number: D1.07</p> <p>Faculty of Computer Science</p> <p>A Coruña (Spain)</p>
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<p>Associate Professor (Profesor Titular de Universidad) and vice-dean of computing resources of the Faculty of Computer Science at the
University of A Coruña (UDC), Department of Computer Science and Information Technologies. Affiliated Researcher at the Centre for Information and Communications Technology Research (CITIC).</p>
<p>I obtained my PhD in computer science in 2014
from UDC and in 2020 a MSc in Bioinformatics from the Open University of Catalonia and the University
of Barcelona. During my PhD, I was also a visiting student at the University of Parma
(supervisor: Dr. Stefano Cagnoni) and University of Bristol (supervisor: Dr. Colin Campbell).
Before joining the UDC in 2018, I held a Juan de la Cierva - Formación (FJCI-2015-26071), a highly
competitive research grant with a 13.46% success rate (in the Computer Science and Information
Technology call) at the Institute of Biomedical Research of A Coruña (INIBIC). During this fellowship, I was
also a visiting scholar at the Stanford University under the supervision of Dr. Christina Curtis.</p>
<p>Current research lines include the conception and development of multi-omic data integration strategies with special focus on genome,
transcriptome and metagenome data to monitor complex and multifactorial diseases. Hence, I am committed to
build a research program on how biological interactions are manifested at the disease level through the use, development
and application of kernel-based integrative computational approaches. Carved out a distinguished academic and research career, culminating in the establishment of his own research laboratory in September 2023 –
<a href="https://mall-lab.citic.udc.es">the Machine Learning in Life Sciences Laboratory</a>.</p>
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Please feel free to contact me if you have any questions or concerns.
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