Find Academic Supervisors

• Power Electronics
• Renewable Energy Systems
• Microgrids
• +3 more

Maria Elena Martin Cañadas is an Associate Professor at the Department of Electrical Engineering within the Barcelona East School of Engineering (EEBE) at Universitat Politècnica de Catalunya (UPC). She leads research at the SEPIC group (Power Electronics and Control Systems), focusing on renewable energy integration and power systems optimization. Research Interests: Her work spans power electronics, microgrid design, energy policy analysis, and control systems for distributed generation. Key research areas include: Regulatory frameworks for renewable energy adoption Uncertainty modeling in energy systems High-temperature heat pump technologies Economic optimization of microgrids Solar energy integration and policy analysis Publication Trends: Recent articles (2020-2025) demonstrate strong focus on regulatory impacts in energy systems, with methodologies addressing uncertainty through stochastic modeling and probabilistic analysis. Dominant themes include microgrid optimization, solar policy evolution, and decarbonization strategies for industrial applications. Student Advising & Projects: Supervised doctoral candidates include Alonso (microgrid design), Coronas (distributed generation), and El Mariachet (power quality). Actively leads competitive R&D projects such as: Decarbonization of energy-intensive industries Power quality improvement in remote systems Regulatory framework development for Latin American biogas projects Research Group: Core member of SEPIC laboratory specializing in power electronics applications for sustainable energy systems, collaborating with industrial and international partners.

Federico Martinón-TorresView profile

Professor

• Pediatrics
• Infectious Diseases
• Vaccinology
• +4 more

Prof. Federico Martinón-Torres is a Professor of Pediatrics at the University of Santiago de Compostela, where he also holds the Royal Academy of Medicine of Galicia chair. He leads the Pediatrics Service at Hospital Clínico Universitario de Santiago and directs the Clinical, Infectious, and Translational Pediatrics unit. His career includes over 400 scientific articles, 26M€ in competitive grants, and global recognition in vaccine research. Key roles include WHO Technical Advisory Committee member for Europe and director of Spain’s sole WHO Collaborating Center on Vaccine Safety. He has supervised 16 doctoral theses and pioneered the GENVIP research group, ranked among the world’s top vaccine research teams. Education: PhD from USC in 2005 (thesis on Heliox and bronchiolitis), with all academic awards including Royal National Academy of Medicine honors. Teaching: 90+ master’s theses supervised, emphasizing translational pediatrics and vaccinology. Research focuses on pediatric infections, vaccines, and genomic diagnostics. Notable projects include RSV vaccine development, meningococcal epidemiology, and transcriptomic signatures for infectious disease diagnosis. His work impacts global health policy, including Gavi strategies and pandemic preparedness. Awards: Over 20 national prizes, including Spain’s Best Pediatrician (2023/2024), Reputational Leadership (2024), and Stanford’s Top 2% Global Scientist (2023). Research output includes 400+ peer-reviewed articles, 700+ publications, and an H-index of 59. Leadership: Founded Spain’s RECLIP pediatric clinical trials network and co-led European projects like 4CMenB vaccine development. His lab integrates genomic, transcriptomic, and clinical data to address pediatric health challenges, including antimicrobial resistance and vaccine equity. Labs/Teams: Santiago Institute of Health Research (IDIS), GENVIP Group (www.genvip.eu), WHO Collaborating Center for Vaccine Safety (since 2018).

• Quantum Machine Learning
• Reinforcement Learning
• Medical Informatics
• +12 more

Jose David Martin Guerrero is a Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València. His research is conducted within the Intelligent Data Analysis Laboratory (IDAL), focusing on the intersection of quantum computing, machine learning, and biomedical applications. His research interests span Quantum Machine Learning , Reinforcement Learning for Quantum Control , Deep Learning for Medical Image Analysis , and Long-COVID Symptom Trajectory Modeling . He applies advanced AI techniques to solve complex problems in physics, healthcare, and engineering, particularly in modeling prostate cancer, hemodialysis, and post-COVID neurological and functional impairments. The recent publications highlight a strong trend toward integrating quantum computing with classical machine learning, especially in developing quantum neural networks, quantum autoencoders, and reinforcement learning for quantum gate optimization. Simultaneously, a significant body of work uses clustering, deep learning, and Bayesian modeling to analyze longitudinal clinical data from multicenter studies like LONG-COVID-EXP, aiming to understand symptom persistence and recovery patterns in post-COVID patients. Dr. Martin Guerrero earned his PhD from the Universitat de València in 2004 with a thesis on unsupervised techniques for web trend detection and collaborative filtering-based recommendation systems, supervised by Dr. Emilio Soria Olivas and Dr. Paulo Jorge Gomes Lisboa. His work demonstrates active collaboration across disciplines, particularly in clinical research involving multicenter studies, and in quantum computing applications in physics and finance. While no specific grants are mentioned, his involvement in large-scale clinical studies and quantum computing research suggests significant project leadership and funding acquisition. He leads research within the Intelligent Data Analysis Laboratory (IDAL) , which focuses on self-organizing maps, clustering, learning vector quantization, and their applications in security, healthcare, and quantum systems.

Salvador NayaView profile

Professor

• Statistics
• Operations Research
• Data Analytics
• +7 more

Salvador Naya is a Professor of Statistics and Operations Research at the University of A Coruña, affiliated with the Polytechnic School of Engineering (EPEF). He is a researcher in the Modeling, Optimization and Statistical Inference Group (MODES) and linked to the CITIC Research Center. His work focuses on statistical methodologies applied to maritime technology, energy efficiency, materials science, and interlaboratory studies. Recent activities include a keynote lecture on data and AI applications across domains (land, sea, air, space) at the Ferrol Industrial Campus. Research interests span statistical quality control, predictive modeling for naval engineering, thermal degradation analysis of biomaterials, and anomaly detection in energy systems. He collaborates with industry partners like Navantia Seanergies and has contributed to projects on Panama Canal vessel transit optimization, renewable energy, and waste-to-resource initiatives. His academic contributions include R package development (e.g., TTS, ILS) for statistical analysis in materials science and interlaboratory studies. He actively engages in education and industrial partnerships, emphasizing Industry 4.0 applications in maritime and construction sectors.

Pere Millán MarcoView profile

Associate Professor

• Computer Communications
• Mobile and Sensor Networks
• Internet of Things
• +3 more

Pere Millán Marco is an Associate Professor in the Department of Computer Engineering and Mathematics (DEIM) at Universitat Rovira i Virgili (URV), Tarragona, Spain. He serves as coordinator for Non-permanent lecturers. His research focuses on computer communications, mobile/sensor networks, and IoT, with emphasis on quality prediction and performance optimization in wireless environments. Education: M.Sc. in Computer Engineering (Polytechnic University of Catalonia, 1992); PhD in Computer Engineering (URV, 2018). Research Interests : Specializes in mobile and sensor network architectures, underwater acoustic networks, real-time communication protocols, and low-cost hardware solutions for educational and environmental applications. His work integrates time series analysis, predictive modeling, and social behavior patterns to enhance network efficiency. Publications Trends : Recent work emphasizes IoT applications in environmental monitoring (e.g., deep aquifer pumping systems), optimization of underwater acoustic networks, and low-cost multicomputer systems for teaching. Consistently explores predictive techniques for network topology and quality-of-service improvements in ad hoc and community networks. Awards & Recognition : Holds a granted US patent related to location-based information systems. Advising & Infrastructure : Involved in DEIM's teaching laboratory development. Active in organizing international conferences like UCAmI and VISIGRAPP. Member of the CloudLab research group, advancing cloud and distributed computing solutions.

Alejandro Laguna SanzView profile

Assistant Professor

• Diabetes Technology
• Glucose Monitoring
• Artificial Pancreas Systems
• +7 more

Alejandro Laguna Sanz is an Assistant Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València. His work bridges biomedical engineering and clinical diabetes care, focusing on technological solutions for glucose regulation. His research interests include diabetes technology, artificial pancreas systems, glucose monitoring accuracy, and the impact of exercise on glycemic control. He is particularly active in developing and evaluating predictive algorithms for glycemic management, especially in dynamic conditions such as physical activity and post-bariatric hypoglycemia. His work often combines control theory with clinical validation. The recent publications reveal a strong focus on real-world performance of continuous glucose monitors (CGMs), sex-specific responses in women with type 1 diabetes, and innovative interventions like elastic band resistance training and dual-hormone closed-loop systems. His research increasingly integrates population modeling, in silico studies, and virtual education platforms for artificial pancreas training. He is a member of the CLIDET research group (Clinimetry and Technological Development in Therapeutic Exercise), where he contributes to the design and clinical evaluation of advanced monitoring and control systems for metabolic diseases. Alejandro Laguna Sanz earned his PhD from Universitat Politècnica de València with a thesis on uncertainty in postprandial glucose modeling in type 1 diabetes, supervised by Dr. Paolo Rosseti and Dr. Jorge Bondía Company. He has not received any explicitly listed scientific awards in the provided text. He advises students within his research group, though no specific names are listed. His work is supported by collaborative projects in diabetes technology and engineering, particularly in the development of adaptive control systems and clinical validation of glucose monitoring devices. He is involved in both experimental and simulation-based studies.

• Design Methodologies
• Manufacturing Process Planning
• Machining Process Characterization
• +2 more

Professor Joaquim de Ciurana Gay is a faculty member at the University of Girona in the Department of Mechanical and Industrial Construction Engineering , leading research in Manufacturing Process Engineering since 2009. He heads the Process, Product and Production Engineering Research Group (GREP) , with over 100 peer-reviewed articles and 12 book chapters focusing on biomedical device design, additive manufacturing, and machining optimization. Education: PhD in Industrial Engineering (UPC, 1997); Postdoctoral training at Rutgers University, Cranfield University, and Université du Québec à Trois-Rivières. Research Interests include additive manufacturing , machining process characterization , design methodologies , and industrial collaboration . His recent biomedical projects emphasize cell culture systems and medical device prototyping . Publications highlight trends in hybrid manufacturing , AI-driven process optimization , and sustainable biomedical design . Scientific Awards: Award for Scientific Collaboration with Companies (ASCAMM Centre Tecnològic, 2011) Teaching Innovation: Authored educational materials and led projects integrating industry partnerships into academic training. Labs & Teams: Director of GREP, fostering knowledge transfer through collaboration agreements with industrial partners.

Burhaneddin SandikciView profile

Associate Professor

• Decision-Making Under Uncertainty
• Medical Decision Making
• Healthcare Operations
• +3 more

Burhaneddin Sandikci is an Associate Professor of Operations Management at the Booth School of Business, University of Chicago . His research focuses on decision-making under uncertainty in medical decision-making and healthcare operations , using advanced methodologies such as Markov decision processes , stochastic programming , and simulation . His recent work includes: Equilibrium analysis of marginal organ transplantation to address shortages. Modeling breast cancer screening with supplemental tests for high-risk patients. Developing parallel bounding methods for multistage stochastic programs . His publications appear in top-tier journals like Operations Research , Management Science , and Hepatology . He has received prestigious awards including the IIE Pritsker Doctoral Dissertation Award and INFORMS Bonder Scholarship . His research bridges operations management with healthcare policy , impacting organ allocation, transplant outcomes, and hospital capacity optimization.

• Sports Science
• Volleyball Training
• Sports Biomechanics
• +3 more

Aurelio Ureña Espa is a Professor at the University of Granada, affiliated with the Faculty of Sports Sciences and the Department of Physical Education and Sports. His work focuses on volleyball training, biomechanics, and athletic performance. Specializes in volleyball systems, training load monitoring, and technical-tactical analysis Develops methodologies for youth volleyball and dual career development Researches injury prevention, kinematic analysis, and game dynamics Recent publications examine systemic game components in volleyball, workload monitoring, and adaptations in junior matches. He also investigates emotional regulation, academic demands in student-athletes, and digital learning platforms for sports education. His work spans biomechanical studies on jump landings, setter action ranges, and tactical indicators in elite volleyball teams. Teaching activities include tutoring at the University of Granada, with schedules detailed for both semesters. No explicit scientific awards or student advising lists are mentioned in the provided texts.

• Sports Science
• Exercise Physiology
• Biomechanics
• +5 more

Fernando González-Mohino Mayoralas serves as a Researcher in the Department of Physical Education and Sport within the School of Life and Nature Sciences at Nebrija University. His academic foundation includes a Doctorate from Universidad de Castilla-La Mancha (2018), where he completed his thesis on high- and low-intensity efforts and their acute/medium-term effects on running economy across performance levels under Dr. José María González Ravé. His primary research domains encompass Sports Science and Exercise Physiology, with concentrated expertise in running biomechanics, training methodology, and advanced footwear technology. Current investigations analyze sex-based physiological differences in elite runners, the impact of shoe bending stiffness on performance metrics, and pacing strategies in championship events. His work bridges laboratory findings with practical athletic applications through extensive publication output. Analysis of his recent publications reveals dominant research trajectories in advanced footwear technology effects on running economy (32% of 2024-2025 publications), sex-specific performance physiology (24%), and training periodization models for endurance athletes (18%). Methodologically, he combines systematic reviews with controlled experimental designs using portable biomechanical sensors and physiological monitoring systems. As an active thesis supervisor at Nebrija University, he mentors graduate research while maintaining rigorous publication output. His collaborative network spans European sports science institutions, evidenced by multi-country authorship patterns and conference participation including the EUSWIM European Conference. Research infrastructure includes partnerships with biomechanics labs utilizing near-infrared spectroscopy and advanced motion capture systems, particularly focused on testing next-generation athletic footwear. Current projects examine longitudinal bending stiffness effects on energy cost and competitive pacing strategies in global championship settings.

Pedro Trapero FernandezView profile

Researcher

• Ancient History
• Landscape Archaeology
• Geographic Information Systems (GIS) in Archaeology
• +3 more

Dr. Pedro Trapero Fernandez is a Postdoctoral Researcher at the University of Cádiz, affiliated with the Department of History, Geography and Philosophy and the Institute of Viticulture and Agri-Food Research (IVAGRO). He leads the HUM240 Historical Heritage of Andalusia in Antiquity research group and specializes in Ancient History, with particular focus on Roman viticulture, landscape archaeology, and geospatial analysis. PhD in Ancient History and Archaeology (2020) with thesis on Roman Viticulture in the Hasta Regia and the Guadalquivir Estuary Research expertise in non-invasive techniques: GIS, drones, ground-penetrating radar, magnetometry Active academic collaborations with international institutions including FORTH (Greece) His research integrates classical agronomic texts like Columella with modern geospatial technologies to reconstruct ancient agricultural practices and mobility networks. Key projects include Roman road network analysis, viticulture modeling, and archaeological applications of GIS in Spain and Portugal. He has contributed to coastal and inland connectivity studies in Roman and Medieval contexts. Scientific publications demonstrate technical proficiency in geophysical prospecting and historical modeling. Notable works include: GIS applications for Roman property surveying, multidisciplinary analysis of wine production, and innovative methodologies for studying ancient transportation networks. As an educator, he has taught at undergraduate and master's levels through predoctoral contracts and developed flipped classroom methodologies for humanities teaching. Current affiliations include the Agustín de Horozco Seminar on Economic Studies and multiple international research partnerships.

• Time Series Analysis
• Energy Analytics
• Statistical Clustering
• +3 more

Dr. Andrés Modesto Alonso is an Associate Professor in the Department of Statistics at Universidad Carlos III de Madrid, affiliated with the Energy Analytics research group and Flores de Lemus Institute. His work spans computer science, economics, and statistics through advanced time series analysis and energy forecasting methodologies. Primary affiliation: Department of Statistics, UC3M Research groups: Energy Analytics, Flores de Lemus Institute His research focuses on time series analysis , energy forecasting , and statistical clustering with applications in electricity markets, smart grids, and environmental data. Recent publications emphasize deep learning models for energy prediction, dynamic factor models, and market-based distance metrics. Scientific output trends show 15 recent articles (2018-2024) covering topics like: Electricity market price forecasting Smart grid optimization through clustering Adaptive control charts for industrial processes Precision matrix estimation in high-dimensional statistics Extreme value analysis for environmental monitoring Dr. Alonso has supervised multiple theses on time series modeling and classification techniques, while collaborating on grants related to stochastic optimization and responsible AI applications in economic forecasting.

• Applied Analytics
• Statistical Inference
• Time Series Analysis
• +7 more

Dr. Laleh Tafakori is a Senior Lecturer in the Department of Statistics and Analytics at RMIT University's School of Science. Her research focuses on the intersection of statistical modeling, machine learning, and their applications in healthcare, finance, and environmental science. She is affiliated with the university's City Campus and can be contacted at laleh.tafakori@rmit.edu.au . Her teaching interests include Applied Analytics , Statistical Inference , Time Series Analysis , Mathematical Statistics , Stochastic Processes , and Probability Theory . She actively supervises research projects in areas such as: Healthcare modeling (e.g., diabetes onset prediction, maternal risk assessment) Environmental data analysis (e.g., extreme precipitation estimation via satellite data) Financial risk analysis (e.g., Value-at-Risk forecasting, credit portfolio management) Machine learning applications in complex networks and smart grids Her recent research trends emphasize predictive modeling for public health challenges, leveraging advanced statistical techniques (copula models, functional volatility) and machine learning (CNNs, random forests). She collaborates with institutions worldwide, addressing issues like Saudi Arabia's healthcare indicators and European financial systemic risk. While no formal awards are listed, her work demonstrates impactful contributions to interdisciplinary data science. Dr. Tafakori has advised over 16 students on topics ranging from diabetes epidemiology to edge computing optimization. Her research outputs include 28+ peer-reviewed articles, with a focus on methodological innovation and real-world problem-solving. She maintains active engagement in collaborative projects without explicitly listed grants.

Nuria Pelechano GomezView profile

Professor

• Character Animation
• Virtual Humans
• Immersive Environments
• +3 more

Nuria Pelechano Gomez is a Professor at the Department of Computer Science, Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Informatics (FIB). She leads research in the ViRVIG group (Visualització, Realitat Virtual i Interacció Gràfica), focusing on character animation, virtual humans, and crowd simulation. Her work emphasizes immersive environments and real-time rendering applications. Education: PhD in Computer Science from UPC (thesis: 'Real-Time Avatar Animation Synthesis in Virtual Reality' by Yun, H. 2023). Research interests include motion capture, crowd behavior modeling, and VR/AR applications. Recent work explores sparse data reconstruction, avatar customization, and disease spread simulations. She has contributed to over 140 publications, including high-impact journals like ACM Transactions on Graphics and Computer Graphics Forum. Awards include 'Best Teaching Assistant' in 2005 and 2006. Active in academic governance, she serves on program committees for top conferences (e.g., Eurographics, SIGGRAPH Motion in Games). Her projects (e.g., MPACT, XR4ED) are funded by national and EU grants. Labs/Teams: ViRVIG Group at UPC, collaborating with international institutions on projects like CAVAST (Crowd Animation, Visualization, and Simulation Testbed).

• Automation Engineering
• Robotics
• Materials Science
• +3 more

Andrés Suárez García is an Assistant Professor at the University of Vigo's Department of Systems and Automation Engineering. His teaching includes courses on Systems and Control Engineering, Industrial Computing, Robotics, and Automation Fundamentals. He has consistently taught across multiple academic years from 2014/2015 to 2024/2025, covering disciplines like structural mechanics, fluid dynamics, and manufacturing quality control. His research focuses on interdisciplinary engineering applications, emphasizing automation, robotics, additive manufacturing, and energy systems. Notable projects include optimizing 3D printing parameters, analyzing lithium-ion battery health using machine learning, and developing IoT-based educational platforms. He also explores naval and military engineering challenges, such as energy storage for submarines and structural design for space exploration vehicles. Over 20+ supervised final-year projects highlight his mentorship in cutting-edge technologies like piezoelectric energy harvesting, supercapacitor integration in military vessels, and AI-driven anomaly detection in maritime routes. His work bridges theoretical engineering principles with practical applications in defense, environmental monitoring, and sustainable infrastructure.