Find and connect with academic supervisors, professors, and scholars for your research journey.
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Professor
Maria Cristina Marinescu is a Professor in the Department of Mathematics and Data Analytics at IQS School of Engineering , with a focus on Applied Data Analytics and Modeling . She has an active research profile in interdisciplinary domains connecting computational methods with public health, social sciences, and medical applications.
Research Professor
Carlos Castillo is an ICREA Research Professor at Universitat Pompeu Fabra, leading the Social and Responsible Computing Research Group. Their work focuses on algorithmic fairness, social computing, and mitigating bias in AI systems across criminal justice, education, healthcare, and hiring. Key projects include the Horizon Europe FINDHR initiative to detect discrimination in algorithmic hiring, causal inference studies on recidivism risk prediction, and analyzing gender biases in student evaluations. Research Interests: Algorithmic fairness, bias mitigation in AI systems, social data ethics, criminal justice analytics, education technology, and health informatics. Notable contributions include the FA*IR fair ranking algorithm and foundational work on auditing algorithms in digital health. Recent Trends in Articles: Recent work emphasizes interdisciplinary applications of algorithmic fairness—e.g., improving representativeness in hiring datasets, analyzing disparities in medical AI models, and addressing bias in student satisfaction surveys. Publications also explore radicalization pathways via recommendation systems and the societal impact of algorithmic decision-making. Awards: Best Paper Awards in CIKM 2022 (Francesco Fabbri), ICAIL 2019 (Marius Miron), and ISCRAM 2013 (Muhammad Imran). Grants: Leads the Horizon Europe FINDHR project and collaborates with the European Commission on algorithmic discrimination research. Labs/Teams: Directs the Social and Responsible Computing Group, focusing on interdisciplinary projects with PhD students and industry partnerships.
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
Research Fellow
Pablo Calleja is a Research Fellow at the Faculty of Computer Science, Polytechnic University of Madrid (UPM), where he has been a member of the Ontology Engineering Group (OEG) since March 2014. His research focuses on Natural Language Processing (NLP), medical terminology mapping, and legal domain applications. He holds a degree in Computer Engineering from San Pablo CEU University (2013) and has prior industry experience as a software developer at IECISA (2008–2011) and a collaboration grant at the Open Access Classroom, San Pablo CEU University (2011–2013). Key contributions include projects like Drugs4covid for pandemic drug discovery, TermitUp for terminological enrichment, and esT5s , a Spanish text summarization model. His work spans legal knowledge graphs, multilingual compliance systems, and NER techniques for academic content analysis. He has also explored accessibility multimedia services and semantic graph applications in tourism ( DBtravel ). Professional roles include collaboration grants at UPM and active participation in interdisciplinary projects such as SNOMED-CT annotation for medical technical sheets. Research trends emphasize cross-domain adaptation (e.g., K-Flares), data augmentation (Widaug), and multilingual NLP solutions. Advising and grants: His current position is supported by a collaboration grant at OEG. Earlier grants include work at San Pablo CEU University. No formal advisees are listed, but he contributes to collaborative research teams. Labs and teams: Core member of the Ontology Engineering Group (OEG), focusing on knowledge representation, NLP, and applied informatics in healthcare and law domains.
Antonio Maria Gonzalez Colas is a Full Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture within the Faculty of Computer Science of Barcelona (FIB). He leads the ARCO research group focused on Microarchitecture and Compilers and is actively engaged in high-impact research in computer architecture, GPUs, and energy-efficient computing. His collaborations extend to the Barcelona Supercomputing Center and various national and European research initiatives. Research Interests: His primary research areas include computer architecture, microarchitecture, compilers, GPUs, and processor design. He focuses on energy-efficient computing, deep neural network (DNN) accelerators, GPU simulation and optimization, memory systems, and architectural support for machine learning and autonomous systems. His work often integrates compiler techniques with hardware design for performance and efficiency. Scientific Production Trends: His recent publications demonstrate a strong focus on energy-efficient hardware for AI workloads, particularly DNN and speech recognition acceleration, GPU architectural innovations, memory optimization, and real-time rendering. He frequently publishes in top-tier venues such as ISCA, MICRO, HPCA, and IEEE/ACM journals. ICREA Academia Award 2024 HiPEAC 2024 Paper Award ACM Senior Member (2020) Advising and Grants: He has advised numerous PhD students whose theses cover topics like energy-efficient architectures for autonomous driving, speech recognition, and neural networks. He leads competitive R&D projects, including an ERC Advanced Grant and projects funded by the Spanish National Program and the ICREA Academia program, focusing on domain-specific architectures and cognitive computing units. Labs and Teams: He is the principal investigator of the ARCO (Microarchitecture and Compilers) research group at UPC, a leading team in computer architecture research in Spain. The group is part of a larger collaborative network within UPC and with international partners.
Daniel Hernández de la Iglesia is a researcher at the University of Salamanca , affiliated with the School of Informatics and the Department of Computer Science and Artificial Intelligence . He completed his PhD at the University of Salamanca in 2018 with the thesis titled "Embedding smart software agents in resource constrained internet of things devices." Research Focus: Specializes in integrating Multi-Agent Systems and IoT for sustainable applications, including electric vehicle optimization, battery reuse, and smart urban solutions. Academic Contributions: Published extensively on AI-driven energy management, smart mobility, and ethical implications of technology. Key Trends in Publications (2022-2025): His work spans IoT , Artificial Intelligence , and Sustainable Mobility , with a focus on electric vehicle battery health, strategic management in digitalization, and ethical considerations in technology. Collaboration: Supervised by Dr. Gabriel Villarrubia González and Dr. Juan Francisco de Paz Santana , his research bridges academic rigor with real-world applications in smart systems and renewable energy.
Researcher
Ahmed AbuRa'ed is a Researcher at the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF), Barcelona. He is affiliated with the TALN research group and the Large-Scale Text Understanding Systems Lab. His work focuses on advancing knowledge in scientific text summarization, information extraction, and machine learning. Education: PhD in Computer Science (2020), UPF, Barcelona, Spain M.Sc. in Computer Science (2015), University of Trento, Italy B.Sc. in Computer Information Systems (2007), An-Najah University, Nablus, Palestine Research Interests: Natural Language Processing (NLP), Machine Learning/Deep Learning, Semantic Web, Information Extraction, Data Mining, and Scientific Document Summarization. His projects include developing systems for automatic generation of state-of-the-art reports, scientific text summarization, and cross-document relation discovery. Publications Focus: His 15 most recent articles (2016–2021) emphasize advancements in scientific literature analysis, including citation detection, text simplification, and cross-document summarization. Notable works involve systems like LaSTUS/TALN for scientific text processing and OlloBot for Arabic health dialogue agents. Labs & Teams: Active member of the TALN research group and the Large-Scale Text Understanding Systems Lab at UPF's DTIC department. Open to collaborations in NLP, Machine Learning, and related fields via email or Skype.
Associate Professor
Isabel Jiménez Gutiérrez is an Associate Professor in the Department of Philology and Translation at Universidad Pablo de Olavide, specializing in French Philology. She holds a PhD from the University of Malaga (2009) with a thesis titled "Approach to anatomical terminology in Spanish, English and French: standardization problems and their implications for the translation of biomedical texts," supervised by Dr. Elena Echeverría Pereda. Her research interests focus on specialized translation, particularly in medical texts, with emphasis on anatomical terminology across Spanish, English, and French. She has made significant contributions to translation pedagogy, developing innovative teaching methods for training future translators. Her work addresses key challenges in reverse translation (translation into non-native language), which has gained increasing importance in the professional translation market. Dr. Jiménez Gutiérrez's recent publications demonstrate a strong focus on translation education methodology, with particular attention to student productivity, self-assessment, and professional skill development. Her work bridges theoretical translation studies with practical classroom applications, emphasizing the use of technology and collaborative learning approaches in translator training. Her research shows consistent engagement with medical terminology, particularly anatomical nomenclature, across multiple languages. This work addresses terminological variation phenomena (synonymy, polysemy, eponymy) that present additional obstacles for medical text translation. She has developed terminological databases to support professional translators working in biomedical fields. As an educator, Dr. Jiménez Gutiérrez has been involved in numerous educational innovation projects, including interdisciplinary collaboration between translators and subject matter experts in scientific-technical translation classrooms. Her teaching innovations focus on developing professional translator competencies aligned with current market demands.
Berta María Guijarro Berdiñas is a Researcher in the Department of Computer Science and Artificial Intelligence at the University of A Coruña , Spain. She is affiliated with the Laboratory for Research and Development in Artificial Intelligence and teaches courses like Machine Learning , Development of Intelligent Systems , and Programming at both undergraduate and postgraduate levels. Research Focus: Her work lies at the intersection of Artificial Intelligence , Machine Learning , and Knowledge-Based Systems . Key contributions include frugal learning (limited data), anomaly explanation , and distributed learning for edge devices. She applies these to areas like health informatics , forest fire management , and human-robot interaction . Recent Publications span explainable AI , anomaly detection , multi-agent systems , and low-power machine learning . Her articles appear in top venues like Expert Systems with Applications and IEEE Transactions on Neural Networks and Learning Systems . Grants & Projects include EU-funded initiatives, Spanish Ministry of Science grants, and regional collaborations. She focuses on AI for healthcare , smart systems , and distributed learning .
Professor
Asier Perallos Ruiz is a Professor in the Faculty of Engineering at the University of Deusto, specializing in the Department of Computing, Electronics and Communication Technologies. His research focuses on RFID technology, wireless sensor networks, and computational intelligence applications with significant contributions to intelligent transport systems and antenna design. Dr. Perallos Ruiz's research interests span multiple domains with a focus on RFID technology , Wireless sensor networks , Internet of Things (IoT) , Computational intelligence , Evolutionary algorithms , and Intelligent transport systems . His work bridges theoretical advancements with practical applications, particularly in transportation systems, healthcare, and industrial automation. His research often involves interdisciplinary collaboration across engineering disciplines. His publication portfolio shows a consistent trend toward improving RFID systems, developing efficient anti-collision protocols, and applying computational intelligence to real-world problems. Recent work has focused on polarization-diversity rotation sensing, customizable RFID platforms, and the integration of RFID with IoT applications. His research demonstrates a progression from foundational RFID technology to more complex system integration and application-specific solutions. Dr. Perallos Ruiz has supervised several graduate students including Muralter Florian (2021), Arjona Aguilera Laura (2018), Cmiljanic Nikola (2018), Lopez Garcia Pedro (2016), and Moreno Emborujo Asier (2016). His research has been supported by various projects focusing on RFID technology, intelligent transportation systems, and wireless communication applications. He leads research teams focused on RFID systems development, wireless sensor networks, and computational intelligence applications. Current work appears to be advancing RFID sensing capabilities, energy-efficient protocols, and system integration for practical applications in transportation and industry.
Cristina Tejedor Martínez is a Professor at the University of Alcalá , Department of Modern Philology . She serves as First Deputy Director of the Doctoral School and coordinates the Linguistic Analysis Research Group , focusing on lexicology, semantics, and translation terminology. Her research spans Anglicisms in Spanish , corpus pragmatics , applied linguistics , and technological tools in language education , with significant projects funded by the Spanish Ministry of Science and European Commission . She has directed studies on tourism language , medical terminology , and dictionary training in pedagogy. Key projects include PRAGMACOR (2022-2026) (corpus pragmatics in telephone interpretation) and Organic.Lingua (2011-2014) (multilingual web portal for agricultural education). She advises PhD students like Soraya García Esteban and collaborates with researchers across Europe. Her publications (15+ peer-reviewed articles) analyze semantic borrowing , machine translation , color metaphors , and neologisms in specialized domains , reflecting her interdisciplinary approach at the intersection of language, technology, and culture.
Professor
Cecilio Angulo Bahón is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Industrial Engineering (ETSEIB) and the Department of Systems, Automatics and Industrial Informatics Engineering . He leads research in Artificial Intelligence and Robotics , with significant contributions to healthcare data analytics, digital twins, and human-robot collaboration. His research spans machine learning for medical data harmonization, generative adversarial networks in health informatics, and evolutionary algorithms for control systems. Recent publications focus on synthetic healthcare data generation, climate-resilient agriculture , and UMAP-based data analysis . His work bridges AI theory with practical applications in industrial and healthcare domains. Scientific awards include the Sant Jordi 2023 Digital Polytechnic Initiative Award . He has supervised doctoral candidates like Carlos Flores-Vázquez and N. Raya, with key collaborations at the IDEAI-UPC Intelligent Data Science and AI Research Group and the Institute of Robotics and Industrial Informatics (CSIC-UPC).
Senior Lecturer
Miquel Moreto Planas is a Senior Lecturer in the Department of Computer Architecture at the Barcelona School of Informatics, Universitat Politècnica de Catalunya (UPC). He is also affiliated with the Barcelona Supercomputing Center (BSC-CNS), a leading institution in high-performance computing. His academic profile is deeply rooted in computer architecture and high-performance computing, with a strong emphasis on practical and theoretical advancements in multicore systems, memory management, and hardware acceleration. His research interests span a wide range of topics including computer architecture, high-performance computing, multicore and manycore systems, cache and memory management, hardware acceleration for genomics and AI, RISC-V processor design, processing-in-memory, interconnection networks, and real-time systems. These interests are reflected in his extensive publication record and collaborative projects. The most recent articles highlight a significant trend toward interdisciplinary research, particularly the application of advanced computer architecture techniques to bioinformatics and healthcare. Key themes include the acceleration of genomic sequence alignment using novel hardware such as processing-in-memory, the development of benchmarks for ARM-based HPC systems in genomics, and the creation of AI-based 3D decision support tools for neurosurgical applications. His work also continues to advance core computer architecture topics like cache management, power-aware resource allocation in heterogeneous systems, and the design of secure, post-quantum cryptographic hardware based on RISC-V. Fulbright Award 2011 HiPEAC Paper Award HiPEAC Paper Award 2024 HiPEAC Paper Award Moreto has been a principal investigator or key contributor to multiple competitive R&D+i projects, such as the STRATUM project for neurosurgical tools, REDIOH for open hardware, and the Laboratorio Zettaescala de Barcelona. He has advised several doctoral students, including López, G., Kostalampros, I., and Haghi, A., and is a core member of the CAP (High Performance Computing) research group at UPC. His work is characterized by strong collaborations with leading researchers like Mateo Valero, Eduard Ayguadé, and Jesús Labarta, often bridging the gap between UPC and BSC-CNS. His laboratory and team affiliations are centered around the CAP group and the Barcelona Supercomputing Center, where he contributes to cutting-edge research in high-performance and embedded computer architectures. His recent work on the BIMSA accelerator and the STRATUM project demonstrates a clear future direction toward applying high-performance computing solutions to critical problems in genomics and medicine.
Associate Professor
Felix Urs Erich Freitag is an Associate Professor in the Department of Computer Architecture at the Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC). He is a key member of the CNDS - Computer Networks and Distributed Systems research group, where he actively contributes to projects in cloud computing, peer-to-peer systems, and IoT networking. His primary research interests include Cloud Computing , Peer-to-Peer (P2P) Systems , Internet of Things (IoT) , LoRa Mesh Networks , Federated Learning , Edge Computing , and Blockchain for IoT . His work spans from fundamental networking protocols to applied research on decentralized systems and sustainable digital technologies. He has also contributed to educational innovation through open project-based learning methodologies. Dr. Freitag's recent publications highlight a strong focus on integrating AI with low-power IoT networks, particularly using LoRa technology for federated learning and secure, decentralized identity solutions. His work demonstrates a clear trend towards enabling intelligent, trustworthy, and resource-efficient distributed systems at the network edge. Scientific Awards: 1er Premi UPC de Ciència Oberta 2024 He has been involved in significant research and innovation projects, including European H2020 and Horizon Europe initiatives, often in collaboration with colleagues like Leandro Navarro and Roque Meseguer. His research is supported by competitive grants focused on digital, industry, and space technologies. He also contributes to educational innovation projects and has supervised student theses, fostering a collaborative research environment within the UPC. His work is associated with the development of experimental testbeds and software libraries for LoRa mesh networks and federated learning, indicating a hands-on approach to building and validating distributed systems.
Pablo José Fernández Galdo is a faculty member at the University of A Coruña, affiliated with the University College of Industrial Design and the Department of Civil Engineering. His expertise lies in Engineering Projects, with a strong focus on industrial design, product development, and additive manufacturing. He is an active member of the research group 'Observatorio para el diseño e innovación en movilidad, medios de transporte y automoción', contributing to innovation in transportation and mobility systems. His research interests span Industrial Design , Product Development , Additive Manufacturing , Automotive Design , Urban Furniture , and Smart Mobility . He emphasizes design methodology, sustainability, and user-centered innovation, particularly in educational and real-world applications. His work integrates design with engineering principles to solve contemporary mobility challenges. The recent articles and project concepts reflect a strong trend toward future mobility , including autonomous vehicles, electric transportation, shared urban mobility, and habitat vehicles for sports tourism. Many projects are linked to industry collaborations, especially with SEAT/Cupra, indicating applied research with commercial relevance. There is a recurring focus on design for experience , adaptability , and innovation in public and personal spaces . He has supervised numerous final-year and master's theses, mentoring students in advanced design projects. His collaborative work includes publications in engineering education and service-learning practices, highlighting his commitment to pedagogical innovation. His research has been supported through various R&D contracts with entities such as Fundación PRODINTEC, TELEVES S.A., CTAG, and LOREFAR S.L., demonstrating strong industry engagement. He has contributed to books and journal articles, particularly in the domain of design education and applied engineering. He is involved in designing experimental projects, models, and prototypes, often in collaboration with students and other researchers. His work environment fosters innovation through hands-on workshops and real-world design challenges, especially in the context of sustainable and intelligent mobility solutions.
