Find Academic Supervisors

• Aeronautics
• Biomedicine
• Electronics
• +7 more

Oscar Flores Arias is a Full Professor in the Department of Aerospace Engineering at the University of Carlos III of Madrid, affiliated with the Gregorio Millán Barbany University Institute for Modeling and Simulation in Fluodynamics, Nanoscience, and Industrial Mathematics. His research spans aerodynamics, biomedical fluid dynamics, and computational modeling. Director of the Aerospace Engineering Research Group Expert in Direct Numerical Simulation (DNS) and turbulent flow analysis His recent work focuses on machine learning integration with Navier-Stokes equations for cardiac flow mapping, patient-specific simulations of thrombogenesis, and bioinspired aerodynamic designs. Collaborations include biomedical institutions and engineering firms, emphasizing interdisciplinary applications. He leads multiple funded projects from Spanish national agencies and private sector partnerships, including: AEI-funded micro-turbine design (2022-2025) Cardiac flow uncertainty quantification (AEI, 2020-2024) MINETUR-funded micro-air vehicle aerodynamics (2016-2020) Supervised theses cover topics from coagulation modeling to bioinspired fluid-structure interaction. Current projects investigate turbulence control, blood flow dynamics, and bioinspired propulsion systems.

• Computer Vision
• Machine Learning
• Pattern Recognition
• +8 more

Sergio Escalera is a Professor at the Department of Mathematics and Informatics, Universitat de Barcelona, and leads the Human Behavior Analysis Group (HuPBA). He holds affiliations at Aalborg University (Distinguished Professor), Computer Vision Center (UAB), and Mathematics Institute of Barcelona. His roles include editorships at journals like TPAMI and Data-centric Machine Learning. He co-created the Codalab platform and co-founded NeurIPS competitions. His research focuses on human-centric AI, including visual and multimodal data analysis, and he has pioneered challenges like ChaLearn Looking at People. Education: Doctorate in Computer Science (Universitat de Barcelona). Research spans computer vision, machine learning, and topological deep learning. He has published over 560 papers and holds patents in AI and biometrics. Research Interests: Inclusive human analysis, transparent AI, affective computing, and sports analytics. Notable projects include SoccerNet for sports video understanding and MyoPS for cardiac MRI analysis. His work bridges theory (e.g., Cellular Transformers) and applications (e.g., mental health monitoring). Awards: ICREA Academia, ELLIS Fellow, AAIA Fellow, multiple best-paper nominations. He has advised 20+ PhD/Master students and led grants totaling millions in funding. Key labs include HuPBA and collaborations with institutions like NVIDIA Jetson Research. Current Projects: MetrikaMind (mental health AI platform), SoccerNet 2024 challenges, and TopoX (topological machine learning software). Active in 3D human motion generation, unlearning algorithms, and robust OOD detection.

• Computer Networks
• Software-Defined Networking (SDN)
• Telecommunications
• +5 more

José Manuel Arco Rodríguez is an Associate Professor in the Department of Automation at the Universidad de Alcalá (Spain). He holds a Doctorate from the same institution for his thesis Propuesta de optimización de la interconexión de redes con calidad de servicio para aplicaciones multimedia (2000), supervised by Dr. Daniel Meziat Luna. His research focuses on intelligent networks, software-defined networking (SDN), edge computing, and telecommunication systems, with particular emphasis on network optimization, protocol design, and AI integration in network architectures. He leads the NetIS research group (Networks and Intelligent Systems), exploring cutting-edge solutions for scalable, reliable data center networks and industrial IoT ecosystems. Key research areas include in-band network control, hybrid SDN architectures, multi-hop edge computing with IoT devices, and low-latency bridging protocols. His work spans theoretical frameworks to hardware implementations (e.g., NetFPGA), with a strong emphasis on practical applications in data centers, campus networks, and industrial environments. Recent contributions address AI-driven network management, plug-and-play routing protocols, and zero-configuration network architectures. Publications highlight advancements in SDN topology discovery (TEDP), scalable addressing (GA3), and path exploration protocols (ARP-Path, All-Path Bridging). His research bridges theoretical networking principles with real-world deployment challenges, often emphasizing interoperability between legacy and modern systems. Arco Rodríguez has collaborated on EU-funded projects and contributed to international standards for network protocols. His lab (NetIS) actively develops open-source tools for network analysis and simulation. Current research trends include AI-enhanced softwarized networks and cloud-edge continuum architectures for IIoT.

• Predictive Analytics
• Social Media Analysis
• Healthcare Informatics
• +5 more

Enrique Caño Marín is an Associate Professor at the Department of Computer Science at Universidad de Alcalá, Spain. His research focuses on predictive analytics, social media analysis, and their applications in healthcare, entrepreneurship, and digital transformation. He holds a doctorate from Universidad de Alcalá, completing his thesis on applying predictive analytics to public data and social media in healthcare (2023), supervised by Dr. Marçal Mora Cantallops and Dr. Salvador Sánchez Alonso. His recent work explores topics such as blockchain in industry funding, generative AI in business transformation, and the role of Twitter in fake news detection. He has published extensively on digital health innovation, pandemic logistics, and women's entrepreneurship in family businesses. Despite no explicit mention of awards, his publications demonstrate strong contributions to interdisciplinary research at the intersection of technology and societal challenges. Research themes consistently emphasize leveraging data science for real-world impact, with a particular focus on social media's role in healthcare, entrepreneurship, and global policy analysis. His work often combines graph analytics, text mining, and machine learning methodologies to address complex problems in digital ecosystems. Enrique collaborates with institutions on projects involving predictive modeling, competitive intelligence, and the ethical implications of AI systems. His email is enrique.canom@uah.es for academic inquiries.

Ana Castillo MartínezView profile

Professor

• Mobile Computing
• Information Technologies in Education
• Internet of Things (IoT)
• +4 more

Ana Castillo Martínez is a Professor at the University of Alcalá's Department of Computer Science. She specializes in Mobile Computing, Educational Technologies, and Internet of Things (IoT) applications. Her research focuses on developing intelligent mobile platforms (PMI group) and leveraging information technologies for training and knowledge dissemination (TIFyC group). She holds a Doctorate from the University of Alcalá (2016) with a thesis on validating meta-tools for engineering optimization. Her work spans interdisciplinary projects including smart city frameworks, gamified educational platforms, and AI ethics studies. Notable contributions include ESCOGPT—an AI-driven occupational search system—and mobile applications for lighting quality assessment. She actively collaborates with EU frameworks for skill alignment and sustainability initiatives. Her research themes repeatedly address human-centric technology integration, accessibility, and urban infrastructure optimization. Recent trends show focus on bridging professional needs with emerging technologies like GPT models and IoT scalability. Ana has led projects on energy efficiency, digital content accessibility, and maintenance systems for public infrastructure. Key labs/teams include: PMI Group: Intelligent Mobile Platforms TIFyC Group: Education Technology Systems

• Machine Learning
• Optimization Algorithms
• Renewable Energy
• +7 more

Laura María Cornejo Bueno is a Professor in the Department of Signal Theory and Communications at the University of Alcalá. She is a core member of the GHEODE research group, specializing in modern heuristics and network design for communication systems. Her research focuses on machine learning applications in renewable energy optimization, climate modeling, and educational technology innovations. She holds a PhD from the University of Alcalá (2018), where her thesis developed novel hybrid neuro-evolutionary algorithms for renewable energy and facilities management. Her work bridges computational intelligence with real-world challenges in energy systems and environmental science. Research interests include: Machine learning for renewable energy prediction (wind/solar) Optimization algorithms (metaheuristics, ensemble methods) Data-driven climate modeling (temperature/wave height prediction) Hybrid learning models in education Recent publications emphasize wind farm layout optimization (2025), hybrid learning pedagogy (2025), and long-term climate forecasting (2024). Her work consistently addresses interdisciplinary challenges at the intersection of AI and environmental engineering. Notable contributions include pioneering fuzzy-based ensemble models for extreme wave predictions and autoencoder frameworks for general forecasting. She has developed novel algorithms for wind power ramp event detection and solar radiation estimation from satellite data.

Luis de la Cruz PirisView profile

Assistant Professor

• Network Optimization
• Cybersecurity
• Intelligent Transportation Systems
• +3 more

Luis de la Cruz Piris is an Assistant Professor in the Department of Telematics Engineering at Universidad de Alcalá. His research focuses on network optimization, cybersecurity, and intelligent transportation systems. He is part of the NetIS research group (Networks and Intelligent Systems). He earned his Ph.D. in 2019 with a thesis on multi-objective optimization strategies for vehicle coordination at urban intersections, supervised by Dr. Iván Marsá Maestre and Dr. Miguel Ángel López Carmona. His research interests include wireless network optimization (e.g., Wi-Fi channel assignment), IoT security frameworks, and AI-driven threat mitigation. Notable projects include the EnvAdapt-CRO-SL algorithm for dynamic channel management and CloudWall, a resilient healthcare IT infrastructure framework. Recent work explores unsupervised learning for cybersecurity, cooperative approaches to Wi-Fi performance, and distributed multi-agent systems for network resilience. His publications span topics like smart traffic light management, OAuth token configuration in IoT, and fuzzy ontology-based driver behavior analysis.

• Renewable Energy Systems
• Photovoltaic Technology
• Microgrid Optimization
• +3 more

Pablo Díaz Villar is an Associate Professor at the Department of Teoría de la Señal y Comunicaciones, Universidad Autónoma de Madrid (UAM). He holds a Ph.D. from Universidad Politécnica de Madrid (2003) with a thesis on photovoltaic system reliability for rural electrification. His research focuses on renewable energy systems, microgrid optimization, and energy storage technologies. He leads the TM Tecnologías Mecánicas, Eléctricas y Térmicas research group. Key research interests include photovoltaic system design, evolutionary algorithms for energy optimization, and sustainable rural electrification. His work spans theoretical models and field implementations in Latin America. Recent studies address cooling methods for PV modules, Industry 4.0 energy management, and adaptive scheduling in microgrids. Publications emphasize practical applications of renewable energy in manufacturing, smart grids, and educational tools like PVLearning for photovoltaic education. His work bridges algorithmic innovation with real-world energy challenges.

• Educational Technology
• E-Learning
• Healthcare Informatics
• +7 more

Rosa María Estriégana Valdehita is an Assistant Professor at the University of Alcalá, affiliated with the Department of Automation. Her research focuses on educational technology, e-learning methodologies, and the integration of information technologies in training and healthcare. She leads research in the MISKC (Healthcare Informatics Research) and TIFyC (Information Technologies for Training and Knowledge) groups, exploring gamification, collaborative learning environments, and technology acceptance models. Her doctoral work (2019) analyzed active learning methodologies and ICT applications in higher education, supervised by Dr. Roberto Barchino Plata and Dr. José Amelio Medina Merodio. Key research themes include virtual learning environments, metaverse applications in education, and the impact of communication on student satisfaction. Recent work addresses post-pandemic e-learning adoption and the role of spirituality in workplace well-being. She has published extensively on topics like cooperative skills development through gamified platforms and predictive analytics in education. Her research spans multiple domains: Educational Technology: Focused on flipped classrooms, virtual labs, and blended learning. Healthcare Informatics: Investigating technology's role in health education and patient care. Organizational Studies: Examining stress reduction in banking via spirituality and post-pandemic tourism safety. Publications emphasize practical applications of technology in education and workforce development. Notable trends include analyzing metaverse potential for online learning and exploring how relational coordination in gamified environments enhances cooperative skills. Her work bridges theoretical frameworks with real-world educational challenges. Grant activity is not explicitly detailed in the text, though her participation in research groups suggests involvement in funded projects. No formal student advisee list is provided, though her pedagogical research implies contributions to student development programs.

• Machine Learning
• Educational Technology
• Materials Science
• +3 more

María del Pilar García Díaz is a Professor at the University of Alcalá, affiliated with the Department of Signal Theory and Communications. She holds a PhD from the University of Alcalá (2014) with a thesis on soft-computing techniques for optimizing mobile access networks under electromagnetic pollution control. Her research focuses on machine learning applications in education and materials science, alongside computational electromagnetism through her participation in the CADIT and GEC research groups. Her educational contributions emphasize flipped classrooms, problem-based learning, and the integration of digital tools (e.g., Trello) in laboratory practices. In materials science, she explores nanocomposite optimization using machine learning and computational modeling. Her work in electromagnetism includes anti-reflective coatings and mobile network deployment algorithms. Recent publications span educational technology, polymer nanocomposite analysis, and machine learning-driven material property prediction. Despite her prolific output, no scientific awards are explicitly mentioned. She actively advises on interdisciplinary projects at the intersection of education, materials science, and signal processing.

Hilario Gómez MorenoView profile

Professor

• Signal Processing
• Machine Learning
• Image Processing
• +3 more

Hilario Gómez Moreno is a Professor at the Universidad de Alcalá, affiliated with the Department of Teoría de la Señal y Comunicaciones. He is part of the COMB research group focused on Communications, Multirate Signal Processing, and Biomedical Engineering. His academic career includes a Doctorate from Universidad de Alcalá (2012), with a thesis exploring statistical learning techniques in image processing. Research interests encompass signal processing, machine learning, image processing, biomedical engineering, computer vision, and education technology. Notable work includes applications in forensic sciences, such as facial recognition and deepfake detection, as well as contributions to ECG analysis and robotics competitions for skill development. His publications span from 2000 to 2025, reflecting long-term engagement with both technical and pedagogical innovations. His articles highlight trends in forensic technology (e.g., facial sketches and speaker recognition), biomedical applications (ECG analysis), and educational methodologies (student performance and robotics-based learning). No scientific awards are explicitly mentioned, but his extensive publication record underscores academic impact. Advising and lab involvement are centered within the COMB group, though specific grants or lab details are not detailed in the text.

• Wireless Communication Systems
• Numerical Simulation Techniques
• Electromagnetic Compatibility
• +3 more

Óscar Gutiérrez Blanco is a Professor at the Universidad de Alcalá , affiliated with the Department of Computer Science within the School of Computer Science and Artificial Intelligence . He is a member of the GTNA Group of Advanced Numerical Techniques , focusing on computational methods and wireless communication systems. He holds a Doctorate in Computer Science from Universidad de Alcalá (2002), with a thesis titled Contribución a la mejora de la óptica física para el cálculo del campo radiado y dispersado por cuerpos complejos , supervised by Dr. Manuel Felipe Cátedra Pérez and Dr. Francisco Manuel Sáez de Adana Herrero. His research emphasizes natural and hybrid localization algorithms , numerical simulation techniques , and wireless communication systems . He has pioneered work in ray-tracing methods for indoor/outdoor localization, real-time kinematic positioning in agriculture, and electromagnetic compatibility in healthcare environments. His interdisciplinary work spans computational biology (avian morphometrics, tick-borne pathogens) and medical research (IGF-I gene therapy for glioblastoma). Key contributions include the FASPRO and FASANT software tools for propagation analysis and antenna modeling. His web-based simulation tool integrates OpenStreetMap data for outdoor path loss estimation. Recent work explores precision agriculture through low-cost RTK systems and high-precision airport safety algorithms. No scientific awards are explicitly listed, but his extensive publication record reflects sustained innovation in computational and applied research. He has advised numerous graduate projects (theses listed in institutional portal) and collaborates internationally on sensor networks and biomedical applications.

José María Gutiérrez MartínezView profile

Associate Professor

• Mobile Computing
• Artificial Intelligence
• Computer Science Education
• +5 more

José María Gutiérrez Martínez is an Associate Professor in the Department of Computer Science at the University of Alcalá. He is part of the PMI (Intelligent Mobile Platforms) research group, focusing on mobile computing, AI, and educational technology. His work integrates interdisciplinary approaches, including IoT, gamification, and healthcare IT. He holds a Doctorate from the University of Alcalá with a thesis on intelligent agents for internet-based learning systems (2006). His academic contributions span over 50 publications since 2017, addressing challenges in accessibility, mobile applications, and sustainable technologies. Research interests include: 1) Developing accessible mobile applications for diverse users, 2) AI-driven solutions for healthcare and education, 3) Optimizing lighting systems for energy efficiency, and 4) Gamification strategies in university environments. Recent projects include ESCOGPT (AI-powered search tools) and μDevOps (cybersecurity microservices). His work bridges theory and practice through collaborations with industry partners. Ongoing efforts focus on applying machine learning to environmental conservation and improving workplace ergonomics via IoT systems.

• Robotics
• Autonomous Vehicles
• Sensor Fusion
• +6 more

Ángel Llamazares Llamazares is a Researcher at the Department of Electronics, University of Alcalá. His work focuses on robotics, autonomous systems, and sensor fusion technologies. He is affiliated with the Robesafe (Service Robotics and e-Safety) and former INVETT (Intelligent Vehicles and Traffic Technologies) research groups. He earned his PhD in 2017 with the thesis Laser-based detection and tracking of moving obstacles to improve perception of unmanned ground vehicles , supervised by Dr. Manuel Ocaña. His research spans topics like SLAM algorithms, obstacle detection, autonomous vehicle perception, and human-robot interaction. Key research areas include autonomous driving systems, multimodal sensor fusion (LiDAR/camera/RADAR), driver activity recognition, and robotics education through competitions. He has explored applications in traffic management, elderly care via voice assistants, and explainable AI for decision-making. Notable contributions include game-theoretic models for electric vehicle charging, modular autonomous driving software architectures, and fusion techniques for HD map validation. His work bridges theoretical advancements with real-world applications in safety-critical systems. Awards: None explicitly listed. Grants: Focus on robotics competitions and university-driven projects. Labs/Teams: Active in Robesafe and INVETT groups, collaborating on robotics competitions like Eurobot Spain to foster skill development among students.

Diego López PajaresView profile

Lecturer

• Networking
• Software-Defined Networking (SDN)
• Internet of Things (IoT)
• +5 more

Diego López Pajares is a Lecturer at the Department of Automática within the Universidad de Alcalá, Spain. His research focuses on Software-Defined Networking (SDN), Internet of Things (IoT), edge computing, and AI-driven network optimization. He is a member of the NetIS research group (Networks and Intelligent Systems), which explores programmable networks and intelligent systems for future communication infrastructures. He earned his Doctorate in Engineering from Universidad de Alcalá with a thesis titled Nuevos conmutadores de red para redes integradas con SDN (New SDN-enabled network switches for integrated networks), supervised by Dr. Juan Antonio Carral Pelayo and Dr. Elisa Rojas Sánchez. His work addresses challenges in scalable network protocols, hybrid SDN architectures, and AI applications in telecommunications. Key research trends include edge computing IIoT systems, fault prediction in smart grids, and 6G-enabling technologies. His publications emphasize in-band control protocols, disjoint path algorithms, and P4-programmable switches. Collaborative efforts with industry and academia aim to bridge theoretical advancements with practical network deployments. Notable contributions include the BareFlow protocol for Layer-2 plug-and-play routing, MDTA algorithm for dynamic environments, and eHDDP for heterogeneous network discovery. These innovations address scalability, security, and interoperability in modern network ecosystems. López Pajares' work intersects with military deployable networks, autonomous vehicle traffic systems (SYROPS), and cloud continuum architectures. His research bridges traditional networking domains with emerging paradigms like AIoT and software-defined infrastructures.