جستجوی استاد راهنمای دانشگاهی

• Data Mining
• Bioinformatics
• Machine Learning
• +۳ مورد دیگر

Domingo Savio Rodríguez Baena is a Professor at Pablo de Olavide University, affiliated with the Department of Computer Languages and Systems. His research focuses on data mining, bioinformatics, and computational biology, with a particular emphasis on biclustering algorithms, gene co-expression networks, and high-performance computing applications. PhD in Engineering, Data Science, and Bioinformatics (2012) from Pablo de Olavide University His work spans interdisciplinary domains, including recommender systems , livestock behavior analysis , and biological data interpretation . Recent articles highlight his contributions to multi-GPU optimization , ensemble learning , and historical database construction . Key collaborations include the DATAi Intelligent Data Analysis and DASE Data Analytics Science & Engineering research groups. He has developed tools like the CyEnGNet–App for gene network visualization and BIGO for gene enrichment analysis. Contact: dsrodbae@upo.es

Federico Divinaمشاهده پروفایل

استاد

• Bioinformatics
• Evolutionary Computation
• Machine Learning
• +۵ مورد دیگر

Federico Divina is a Professor in the Department of Sports and Computer Science at Universidad Pablo de Olavide, Spain. His research focuses on evolutionary computation, machine learning, and bioinformatics. PhD in Artificial Intelligence from Vrije Universiteit Amsterdam Former postdoc at University of Tilburg (NEWTIES EU project) Research Interests : Bioinformatics, Evolutionary Computation, Machine Learning, Big Data, and Soft Computing. He specializes in knowledge extraction from massive datasets through genetic algorithms and heuristic optimization. Recent Publications span time series forecasting, feature selection in high-dimensional data, and biomedical image analysis. His work combines evolutionary algorithms with practical applications in energy consumption prediction, ocular disease diagnosis, and genomic data analysis. Labs & Collaborations : Leads the DS&BD Data Science & Big Data Lab and has collaborated with groups like DATAi and DASE. His projects include Differential (multi-university energy analysis), GALICIAME (SMA genetic data analysis), and NEWTIES (artificial society modeling).

Luis Antonio Belanche Muñozمشاهده پروفایل

استاد

• Machine Learning
• Kernel Methods
• Neural Networks

Luis Antonio Belanche Muñoz is a Professor at the Department of Computer Science , Faculty of Informatics of Barcelona (FIB) , Universitat Politècnica de Catalunya (UPC) . He is affiliated with research groups SOCO - Soft Computing and IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Group . His career spans over 25 years, with 216 documented activities. His research focuses on Machine Learning , Kernel Methods , and Neural Networks . He has pioneered techniques in feature selection, similarity measures, and hybrid models connecting deep learning with kernel methods. His work applies to diverse domains including finance, microbiology, cancer diagnostics, and environmental engineering. Recent publications highlight trends in kernel matrix analysis using entropy, microbiome data integration , and drug resistance prediction in HIV. Earlier work includes knowledge-based systems for wastewater treatment diagnostics and educational technologies for MOOC environments. He has collaborated with 75+ researchers across UPC's research network, contributing to projects funded under Spain's State Research Plans and Catalonia's RIS3CAT strategy. His 2011 thesis on Feature selection in brain tumor MRS data demonstrates interdisciplinary applications.

• Molecular Biology
• Neurobiology
• Genetics
• +۳ مورد دیگر

Dr. Gemma Carreras Badosa is a Lecturer in the Department of Biology at the Universitat de Girona. She holds a PhD in Biology (2015) and a Master's in Neuroscience. Her research focuses on microRNA expression, RNA delivery as therapeutic tools, gene expression, and inflammatory markers related to allergic diseases, prenatal/postnatal growth alterations, metabolic disorders, and neurobiology. She has secured competitive funding including principal investigator roles in two national projects (MOBJD526, MOBJD106) and participation in international projects like SPIOMET4HEALTH (H2020). Her scientific work has resulted in 16 principal publications and 42 co-authored papers with 808 citations and an H-index of 16. She has developed technical skills in DNA/PCR techniques, RNA/microRNA analysis (qPCR, TLDA, microarrays), protein assays (ELISA, Western blot), cell culture, nanotechnology for RNA delivery, histology, microscopy (confocal, electron), and animal experimentation (Wistar rats, CBL mice). She has also collaborated on clinical data management, biobanking, and statistical analysis (SPSS, R). Scientific awards include: Postdoctoral grant (CD19/00172, Sara Borrell, ISCIII) Predoctoral grant (pFIS, ISCIII) She has mentored undergraduate, Master's, and ongoing PhD students at UdG and participated in science outreach activities including workshops for students (2017, 2021) and the "Women in Science" video series (2023).

• Machine Learning
• Metabolomics
• Chemical Sensor Systems
• +۷ مورد دیگر

Santiago Marco Colás is a Full Professor in the Department of Electronics and Biomedical Engineering at the University of Barcelona and leads the Signal and Information Processing for Sensing Systems group at IBEC. His research focuses on advanced computational methods for chemical sensor arrays, gas chromatography-ion mobility spectrometry (GC-IMS), mass spectrometry, and NMR data analysis in metabolomics, biomedical diagnostics, and environmental monitoring. Developed open-source tools like GCIMS R-package for untargeted IMS data analysis Innovated drone-based chemical sensing systems for indoor/outdoor odor mapping Created IoT-enabled respiratory impedance devices with mobile app control Explored machine olfaction algorithms for biomarker discovery in colorectal cancer and COPD Investigated dielectric excitation methods for metal oxide semiconductor sensors His recent work addresses real-time odor quantification in wastewater plants, predictive modeling for postoperative complications, and low-cost IoT respiratory monitoring. Publications span sensor signal processing, calibration transfer techniques, and collaborative STEM education initiatives.

Rodrigo Santamaría Vicenteمشاهده پروفایل

دانشیار

• Bioinformatics
• Information Visualization
• Microarray Data Analysis
• +۴ مورد دیگر

Rodrigo Santamaría Vicente is an Associate Professor in the Department of Computer Science and Automation within the Faculty of Sciences at the University of Salamanca. His academic career centers on bridging computer science with biological research through advanced data analysis and visualization techniques. He serves as director of the Diploma of Specialization in Bioinformatics and Computational Genomics, demonstrating leadership in specialized academic programming. Dr. Santamaría earned his PhD in Computer Science from the University of Salamanca in 2009 with his thesis "Visual analysis of gene expression data by means of biclustering," supervised by Dr. Luis Antonio Miguel Quintales and Dr. Roberto Therón Sánchez. His academic journey began with an M.S. degree in Computer Science from the same institution. His research primarily focuses on Bioinformatics and Information Visualization, with particular emphasis on integrating diverse data sources, analysis algorithms, and visual representations to enhance understanding of complex biological problems. His work spans multiple subdomains including gene expression analysis, biclustering algorithms, phylogenetic tree visualization, and collaborative tagging systems. Santamaría's research group affiliations include both the BIOINFORMÁTICA research group and the CaUSAL (Cultura Académica, Patrimonio y Memoria Social) research group at the Institute of Functional Biology and Genomics. His publication record reveals a consistent trajectory of scholarly output since 2006, with recent work showing increased focus on biological applications of computational methods. His most significant contributions appear in the integration of visualization techniques with bioinformatics analysis, particularly through tools like BicOverlapper and Voronto that facilitate interactive exploration of complex biological data. The evolution of his work demonstrates progression from foundational algorithm development to increasingly sophisticated applications in systems biology. Author of the book "How Machines Organize: An Introduction to Distributed Systems" Director of the Diploma of Specialization in Bioinformatics and Computational Genomics Active contributor to R programming ecosystem with the biclust package As an educator, Santamaría teaches across multiple programs including the Master's Degree in Computer Engineering and previously taught Bioinformatics for the Biotechnology degree program. His teaching portfolio spans Bioinformatics (from both computer science and biology perspectives), Distributed Systems, and Service-Oriented Architectures. He maintains an active research laboratory focused on developing visualization tools for biological data analysis, with current projects emphasizing integration of gene expression data with biological ontologies and advanced biclustering techniques.

José Antonio Castellanos Garzónمشاهده پروفایل

دانشیار

• Bioinformatics
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

José Antonio Castellanos Garzón serves as an Associate Professor in the Department of Computer Science and Automation at the University of Salamanca, where he is affiliated with the Biomedical Research Institute of Salamanca (IBSAL) and leads the ESAL Expert System and Applications Lab (ESALAB). He earned his doctorate from the University of Valladolid in 2013 with a thesis on evolutionary frameworks for DNA microarray cluster analysis, supervised by Dr. Fernando Díaz Gómez. His academic foundation bridges computer science and biomedical applications through advanced computational methodologies. His research spans Bioinformatics, Artificial Intelligence, Machine Learning, Data Mining, Evolutionary Computation, and Biomedical Informatics, emphasizing algorithmic solutions for genomic data analysis. Previously, he contributed to the BISITE research group focused on Bioinformatics, Intelligent Informatic Systems, and Educational Technology, demonstrating cross-disciplinary expertise in computational biology and AI-driven healthcare systems.