جست‌وجوی استاد و پژوهشگر

• Statistical Inference for Stochastic Processes
• Mathematical Biology
• Mathematical Modeling of Physiological Systems
• +۵ مورد دیگر

Susanne Ditlevsen is a Professor in Statistics at the Department of Mathematical Sciences , University of Copenhagen . Her research spans interdisciplinary domains including statistical inference for stochastic processes, mathematical biology, nonlinear dynamics, and computational neuroscience, with applications to physiological systems and marine mammal behavior. Primary research areas: Statistics , Stochastic Processes , Biomathematics Teaching: Undergraduate and graduate courses in Probability , Regression , and Diffusion Models Research Highlights : Developed statistical methods for Hidden Markov Models to analyze narwhal diving behavior (2019), incorporating long-range dependence. Advanced stochastic differential equations with mixed effects for biomedical data (2020), enabling personalized physiological modeling. Co-authored high-impact studies on climate tipping points (2023), including the AMOC collapse warning, which received global media attention. Contributed to neural network modeling (2017) with multi-class oscillating systems and nonlinear dynamics in neuronal systems (2014). Work on α-stable noise and double well potentials (2025) enhances understanding of noise-driven transitions in biological and physical systems. Collaborations : Co-researcher on interdisciplinary projects with Alberto Samson , Eva Löcherbach , and Mads Peter Heide-Jørgensen . Engages with international teams on climate dynamics , computational neuroscience , and biomedical statistics .

• Forest Ecology
• Dendrochronology
• Climate Change Ecology
• +۴ مورد دیگر

Jesús Julio Camarero is a prominent researcher specializing in forest ecology and dendrochronology with a primary focus on Mediterranean ecosystems. He leads the research group Estructura y Función en Ecosistemas Mediterráneos (Structure and Function in Mediterranean Ecosystems) under the Natural Resources, Energy and Environment research area, and contributes to the Biodiversity and Conservation Biology doctoral program. His work bridges field observations with tree-ring analysis to address critical questions in global change biology. Education: PhD in Ecology from Universitat de Barcelona (1999), thesis: Growth and regeneration patterns and processes in Pinus uncinata Ram. Treeline ecotones in the Pyrenees and in an isolated population in the western distribution limit in Spain , supervised by Dr. Emilia Gutiérrez Merino Dr. Camarero's research centers on tree and forest responses to climate change, particularly drought stress and extreme events. He employs dendrochronological methods to analyze growth patterns, resilience mechanisms, and mortality drivers across diverse ecosystems including Mediterranean woodlands, alpine treelines, and tropical forests. His work examines species-specific adaptations, climate-growth relationships, and the complex interactions between biotic stressors (e.g., pathogens, mistletoe) and abiotic factors. Key contributions include developing frameworks for quantifying drought vulnerability and understanding legacy effects in tree growth. His recent publications reveal a strong global focus with field sites spanning Spain, China, Romania, and the Himalayas. The research consistently uses tree-ring chronologies to decode climate impacts, showing particular emphasis on Mediterranean pine and oak species, alpine shrubline dynamics, and cross-continental comparisons of drought responses. A recurring theme is the decoupling of growth responses from other physiological processes during stress events. Dr. Camarero actively collaborates through initiatives like the Red Ibérica de Decaimiento Forestal inducido por el Clima (ReDeC) (Spanish Network for Climate-Induced Forest Dieback) and contributes to major datasets including the European Beech tree-ring archive (1952-2020) and Basal Area Increment monitoring from Spanish silviculture sites. His work informs forest management strategies under climate change, particularly regarding assisted migration and drought mitigation techniques. He leads the Estructura y Función en Ecosistemas Mediterráneos research group, which investigates biodiversity patterns, ecosystem functioning, and conservation challenges in Mediterranean environments. The team integrates dendroecology with soil science, remote sensing, and physiological measurements to address forest vulnerability across multiple spatial and temporal scales.

Montserrat Pons Vallèsمشاهده پروفایل

استاد

• Game Theory
• Voting Systems
• Operations Research
• +۳ مورد دیگر

Montserrat Pons Vallès is a Senior academic at the Universitat Politècnica de Catalunya (UPC), affiliated with the Escola Politècnica Superior d'Enginyeria de Manresa (EPSEM) and the Departament de Matemàtica Aplicada III. She holds a Bachelor’s in Mathematics and a Doctorate in Mathematics, specializing in Game Theory and Voting Systems. Her research focuses on power indices, voting systems design, cooperative game theory, and applications to social choice and reliability systems. She is part of the GRTJ (Game Theory Research Group) at UPC, a leading team in mathematical and computational studies of decision-making processes. Her work integrates theoretical game theory with practical applications in operational research and reliability engineering. Notable contributions include extending Banzhaf indices for multi-level voting, analyzing power structures in weighted voting systems, and developing measures for component importance in reliability systems. She has collaborated extensively with Prof. Josep Freixas on topics like decisiveness indices, success metrics in voting, and probabilistic power analysis. Over 94 documented activities, Pons has published in journals like Annals of Operations Research and Theory and Decision, and presented at conferences such as the European Conference on Operational Research. Her projects include国家级 funded research on mathematical models for voting and cooperation in social networks and political science. Despite no listed awards, her h-index of 4.0 reflects sustained scholarly contribution. She advises on reliability systems and voting mechanisms, contributing to both academic and applied domains.

Ricardo Gutierrez Diezمشاهده پروفایل

دانشیار

• Statistical Physics
• Dynamical Large Deviations
• Quantum Many-Body Systems
• +۴ مورد دیگر

Ricardo Gutierrez Diez is an Associate Professor (Profesor Titular) in the Department of Mathematics at University Carlos III of Madrid, where he teaches courses in linear algebra, calculus, differential equations and numerical analysis. He is also a member of the Grupo Interdisciplinar de Sistemas Complejos (GISC), contributing to interdisciplinary research in complex systems. His research focuses on theoretical aspects of statistical physics, with particular emphasis on dynamical large deviations, quantum many-body systems, glassy soft matter, and synchronization phenomena in complex networks. His work bridges physics, mathematics, and network theory, exploring fundamental questions about collective behavior and phase transitions in complex systems. Previously, he also conducted research in experimental neuroscience, developing quantitative approaches to brain connectivity analysis. His publication record demonstrates significant contributions across multiple domains of theoretical physics. His recent work shows a strong focus on dynamical phase transitions, network synchronization, and the application of large deviation principles to complex systems. His research often involves collaborations with leading institutions including the University of Nottingham, Weizmann Institute of Science, and various Spanish universities. His academic journey includes positions as Assistant Professor at University Carlos III of Madrid (2019-2021), Assistant Professor at King Juan Carlos University (2017-2019), Marie Skłodowska-Curie Fellow at University of Nottingham (2015-2017), and Postdoctoral Fellow at Weizmann Institute of Science (2013-2014). He completed his PhD in Physics of Complex Systems at Technical University of Madrid (2010-2013).

Gabriel Cardona Juanalsمشاهده پروفایل

استاد

• Bioinformatics
• Computational Biology
• Phylogenetic Networks
• +۳ مورد دیگر

Gabriel Cardona Juanals (b. 1972) is a Full Professor at the Department of Mathematical and Computer Sciences, University of the Balearic Islands, currently serving as Director of the Higher Polytechnic School since 2021. Holding dual degrees in Mathematics (1996) and Telecommunications Engineering (1997) from UPC, he obtained his PhD in Mathematics (2002) from the same institution. His academic journey includes a Researcher Training grant at UPC's Applied Mathematics II department (1996-2000) before joining UIB in 2000. Mathematics degree (1996) - UPC Telecommunications Engineering degree (1997) - UPC PhD in Mathematics (2002) - UPC His research spans two major domains: Algebraic Number Theory (initial focus on genus 2 curves and automorphism groups) and Bioinformatics/Computational Biology (phylogenetic network analysis, tree-child networks, and evolutionary metrics). He has published over 75 works, including 30+ in indexed journals, with recent emphasis on solar energy applications through the OTSun ray-tracing software suite. Key research areas include: Phylogenetic network comparison metrics Algebraic structure of evolutionary trees Optical analysis of solar collectors Automorphism groups in algebraic geometry He coordinates multiple projects with national and European funding, and leads the Bioinformatics and Computational Biology research group (BIOCOM). His teaching focuses on abstract algebra, discrete mathematics, and computational methods across mathematics, telematics, and computer engineering programs.

• Automatic Control
• Model Predictive Control
• Large-Scale Systems
• +۷ مورد دیگر

Pau Segovia Castillo is a Beatriz Galindo Fellow in the Department of Automatic Control at Universitat Politècnica de Catalunya (UPC), where he conducts research in large-scale systems control. He is affiliated with the Advanced Control Systems (SAC) research group at the Research Center for Supervision, Safety and Automatic Control (CS2AC). Previously, he held postdoctoral positions at IMT Lille Douai (2019–2020), Delft University of Technology (2020–2023), and UPC (2023). BS/MS in Industrial Engineering, Universitat Politècnica de Catalunya (UPC), 2015 Joint PhD in Automatic Control, Robotics and Vision, UPC and IMT Lille Douai, France, 2019 His research focuses on non-centralized predictive control approaches for managing large-scale systems, with applications in water resources systems, intelligent transportation systems, and energy systems. He applies model predictive control, digital twin technologies, and switching control strategies to real-world infrastructure such as canals, irrigation networks, and inland waterways. His work emphasizes real-time optimization, robustness, and scalability in complex environments. The recent publications highlight a strong trend in model predictive control applied to waterway and transportation systems. Key themes include coordination of vessels and bridges, digital twin implementation, multilayer control architectures, and observer design for nonlinear systems. The research spans both theoretical advances in control theory and practical implementations using real databases and simulations. Scientific recognition includes: Beatriz Galindo Fellow He advises PhD students, including Javier Pedrosa Alias, and has been involved in collaborative research projects across institutions in Spain, France, and the Netherlands. His work is supported by his fellowship and integrated within the SAC research group, contributing to national and international efforts in smart infrastructure and automation. The research group CS2AC provides a multidisciplinary environment for supervision, safety, and automatic control applications. He is a member of the Advanced Control Systems (SAC) research group at CS2AC, which focuses on developing advanced control methodologies for safety-critical and large-scale systems. The team works on real-time monitoring, fault detection, and optimization of industrial and environmental processes.

Pau Fonseca Casasمشاهده پروفایل

استاد

• Simulation
• Modeling and Analysis
• Operations Research
• +۴ مورد دیگر

Pau Fonseca Casas is a Professor at the Universitat Politècnica de Catalunya (UPC) in the Department of Statistics and Operations Research, affiliated with the Barcelona Informatics School (FIB). His research focuses on simulation modeling, digital twins, optimization algorithms, and their applications in urban mobility, healthcare systems, and education. He leads the IMP (Information Modeling and Processing) research group and collaborates with the inLab FIB (part of the TECNIO Network and CIT UPC). He holds a doctorate from UPC and has over 242 scholarly activities including articles, projects, and awards. Notable contributions include pandemic modeling using digital twins, bike-sharing system optimization, and educational innovations leveraging computational thinking and Industry 4.0 principles. Fonseca Casas has received awards like the UPC's 14th Research Valorization Prize and has served on committees for major simulation conferences like Annual Modeling and Simulation Conference. His work spans interdisciplinary collaborations in sustainability, healthcare, and technology, with ongoing projects on wastewater surveillance networks and smart urban management. He actively publishes in journals like Sustainability , Logistics , and Advanced Theory and Simulations , emphasizing practical solutions for complex systems through rigorous validation processes.

• Non-linear dynamical systems
• Statistical mechanics out of equilibrium
• Complex systems
• +۱۱ مورد دیگر

Dr. Emanuel Gastón Mompó Pavesi is an Assistant Professor in the Institute for Research in Technology (IIT) at Comillas Pontifical University, School of Engineering (ICAI), Madrid, Spain. He joined the institution in January 2023 and is affiliated with the Intelligent Systems research area. His academic background includes a Ph.D. in Mathematical Engineering from Universidad Carlos III de Madrid (2019), where he also served as a lecturer until 2022, and a B.Sc./M.Sc. in Mathematics from Universitat de València (2014). Ph.D. in Mathematical Engineering, Universidad Carlos III de Madrid (2019) B.Sc. & M.Sc. in Mathematics, Universitat de València (2014) His research spans nonlinear dynamical systems and nonequilibrium statistical mechanics, with emphasis on chaotic behavior, noise effects, memory, and anomalous relaxation in physical systems. He also explores applied mathematics topics such as numerical methods, optimization, inverse problems, and machine learning. His recent publications in journals like Physical Review Letters , Physical Review E , and Entropy reveal a strong focus on semiconductor superlattices, geometric diffusion, and relaxation dynamics in many-body systems. These works often intersect chaos, noise, and memory to develop novel physical insights and potential applications. Dr. Mompó is an active reviewer for Physical Review Letters and Physical Review E since 2018. He has delivered multiple invited seminars and organized scientific events, including the Junior Seminars at the Gregorio Millán Barbany Institute. He has also contributed to science communication through media appearances, such as the podcast "Casting the Future." While no formal students are listed, his involvement in mentoring through seminars and conference organization suggests academic leadership. He has not received explicitly mentioned scientific awards, but his publication record in top-tier journals indicates strong recognition in his field. He is involved in research dissemination and education, including upcoming training on AI for teaching and assessment at Comillas. His work is grounded in theoretical and applied physics, with potential applications in random number generation, signal processing, and complex system modeling.

Manuel Lama Penínمشاهده پروفایل

استاد

• Machine Learning
• Process Mining
• Predictive Monitoring
• +۶ مورد دیگر

Manuel Lama Penín is a Full Professor at the Research Center on Intelligent Technologies (CiTIUS) with the University of Santiago de Compostela. His research bridges machine learning, process mining, and semantic modeling to address challenges in healthcare, industry, and e-learning. He has led 29 of 51 R&D projects and authored over 150 scientific works, including 52 journal articles. Research Areas: Process Mining & Conformance Checking Predictive Monitoring & Drift Detection Semantic Modeling & Service Computing Social Workflow Analysis & Data-to-Text AI in Healthcare & Educational Technologies Notable Projects: TRANSFIRESAUDE (2023, EU Health R&I Ecosystems) AQUATECHInn 4.0 (2023, Aquaculture Education) INCEPTION (2021, Concept Drift in Process Mining) Scientific Recognition: Recipient of the Transfer Technology award from the Galician Royal Academy of Sciences for co-founding InVerbis Analytics, a spin-off commercializing process mining research. Article Trends: His recent publications focus on explainable AI integration in EU regulations, drift detection methodologies, and natural language generation for process documentation. Collaborative efforts emphasize cloud-based solutions, healthcare process formalization, and predictive modeling across sectors.

Jose Navarroمشاهده پروفایل

استاد

• Work and Organizational Psychology
• Work Motivation Dynamics
• Affective Events Theory
• +۴ مورد دیگر

Jose Navarro is a Full Professor in Work and Organizational Psychology at the University of Barcelona (UB), Department of Social Psychology. He currently serves as the Delegate of the Rector of the UB for the promotion of research. Navarro is affiliated with several professional organizations including the European Association of Work and Organizational Psychology, the Society for Chaos Theory in Psychology and Life Sciences, and SCEPS (the Spanish scientific association of social psychologists). His educational background includes: Doctor of Psychology (Organizational Psychology) from University of Barcelona (1997-2001) Master's in Groups Psychology from University of Barcelona (1993-1995) Bachelor's in Psychology from University of Barcelona (1991-1993) Professor Navarro's research primarily focuses on work motivation dynamics, particularly the causes of work motivation changes in the short and medium term. His work explores the role of emotions and attributions in workplace motivation, applying within-person analysis approaches to understand temporal dynamics. He has developed expertise in complexity science applications to organizational behavior, nonlinear dynamics in work psychology, and team effectiveness. His research methodology often employs intensive longitudinal designs, day reconstruction techniques, and nonlinear analytical approaches to capture the dynamic nature of workplace phenomena. Navarro has held several leadership positions at the University of Barcelona, including Head of Department from 2016-2020 and Assistant Professor from 1997-2001. His academic contributions span numerous publications in prestigious journals such as European Journal of Work and Organizational Psychology, Journal of Organizational Behavior, and Human Relations. He has published extensively on topics including affect and motivation relationships at work, temporal dynamics in work motivation, within-person analysis of work motivation, teamwork and team competences, and complexity science applications in organizational behavior. His research has practical implications for understanding how work motivation fluctuates throughout the day and week, how emotions influence motivation, and how organizations can design work environments that support sustained motivation. Professor Navarro's work bridges theoretical advancements with practical applications for human resource management and organizational development.

JESUS MARIA RODRIGUEZمشاهده پروفایل

استاد

• Heart Rate Variability Analysis
• Neural Networks
• Pattern Recognition
• +۳ مورد دیگر

Jesus Maria Rodriguez Presedo is a Professor in the Department of Electronics and Computing at the University of Santiago de Compostela (USC), affiliated with the Faculty of Physics and the Center for Research in Intelligent Technologies (CITIUS). He leads the GSI Group (Intelligent Systems Group) and focuses on biomedical signal processing, particularly in Heart Rate Variability (HRV) analysis, neural networks, and telemedicine solutions. His work integrates machine learning, stochastic modeling, and clinical applications to improve cardiac monitoring and diagnostic tools. Dr. Rodriguez earned his PhD from USC in 1994 with a thesis on intelligent ischemia monitoring, advised by Dr. Senén Barro and Dr. Ramón Ruiz Merino. His research emphasizes HRV analysis, biosignal interpretation, and software development (e.g., the RHRV package). He has contributed to telemonitoring systems for patients with chronic conditions like sleep apnea and COPD, leveraging multiagent systems and ubiquitous computing. His recent work explores nonlinear dynamics in time series, stochastic embeddings via variational autoencoders, and adaptive neural networks for multichannel signal analysis. Applications span cardiac event detection, ECG segmentation, and abductive frameworks for medical diagnostics.

Paco Calvoمشاهده پروفایل

استاد

• Plant Cognition
• Philosophy of Biology
• Cognitive Science
• +۳ مورد دیگر

Paco Calvo is a Professor of Philosophy of Science at the University of Murcia, Spain, and Director of the Minimal Intelligence Lab (MINT Lab). His work focuses on plant cognition and intelligence, blending insights from cognitive science, philosophy, and biology to challenge traditional views of animal-centric intelligence. He leads interdisciplinary research on plant behavior, decision-making, and adaptive responses, emphasizing plant sentience and interspecies cognitive comparisons. Calvo’s research areas include Plant Signaling & Behavior, Plant Cognition & Sentience, and the Philosophy of Plant Neurobiology. His lab, MINT Lab, investigates minimal cognition in plants through experimental and theoretical approaches. Notable contributions include the book *Planta Sapiens: The New Science of Plant Intelligence* (2023) and co-editing volumes like *The Routledge Companion to Philosophy of Psychology* (2020). Recent publications highlight plant sentience debates, protein-based intelligence markers, and plant-inspired robotics. Calvo actively engages in public discourse through media appearances, podcasts (e.g., *Behind Greatness Podcast*), and events like *Human Entities 2025* in Lisbon. His work advocates for a broader, ecologically grounded understanding of intelligence across life forms.

• Coastal Engineering
• Computational Fluid Dynamics
• Wave Overtopping
• +۳ مورد دیگر

Corrado Altomare serves as a Researcher at the Department of Civil and Environmental Engineering within the Barcelona School of Civil Engineering at the Polytechnic University of Catalonia (UPC), where his work centers on advanced coastal engineering research at the LIM/UPC Maritime Engineering Laboratory. His educational qualifications include: Master in Civil Engineering (Caminos, Canales y Puerto) Doctorate in Chemical Engineering Specializing in coastal processes, Dr. Altomare's research focuses on wave overtopping phenomena, SPH-based numerical simulations, and hydraulic modeling of maritime structures. His work provides critical insights for coastal protection infrastructure and extreme wave event prediction through high-fidelity computational methods. With 65 indexed journal articles and 251 total academic activities spanning 2009-2025, his publication record demonstrates sustained contributions to coastal engineering. Recent work (2019-2025) shows increasing emphasis on SPH applications for fluid-structure interactions and overtopping prediction in complex marine environments. No scientific awards were listed in the provided information. Details regarding student supervision, research grants, and advising activities were not specified in the source material. Dr. Altomare maintains active affiliation with the LIM/UPC Maritime Engineering Laboratory, a leading research center combining experimental facilities with computational modeling to advance maritime engineering science and practical coastal solutions.

Albert Solé-Dauraمشاهده پروفایل

پژوهشگر

• Computational Chemistry
• Catalysis
• Sustainable Energy
• +۱۳ مورد دیگر

Dr. Albert Solé-Daura is an independent researcher and Junior Leader at the Institut Català d'Investigació Química (ICIQ) in Tarragona, Spain, where he leads a research group focused on computational modeling of catalytic processes for energy and sustainability. He holds a PhD from Universitat Rovira i Virgili (URV) and has conducted postdoctoral research at the Collège de France and the University of Amsterdam. PhD: Universitat Rovira i Virgili (2020) Postdoctoral Experience: Collège de France, University of Amsterdam Current Affiliation: Institut Català d'Investigació Química (ICIQ) His research centers on the computational investigation of polyoxometalates (POMs) and metal-organic frameworks (MOFs) , particularly their roles in CO₂ conversion , N₂ reduction , and thermal oxidation catalysis . He specializes in advanced molecular simulation techniques, including DFT-based molecular dynamics and enhanced sampling methods , to model complex phenomena such as proton- and electron-transfer events and spin-forbidden reactions in explicit environments. His recent publications span themes in photocatalysis , electrocatalysis , and supramolecular materials , reflecting a strong interdisciplinary focus on sustainable chemical processes. His work aims to bridge the gap between computationally feasible models and experimentally relevant systems. la Caixa Junior Leader Fellowship (2024) Margarita Salas Grant (2022) Dr. Solé-Daura supervises a PhD student and collaborates closely with experimental groups. His current project, funded by the "la Caixa" Foundation, develops a novel computational method (SURFXsim) to simulate spin-forbidden events in large catalytic systems. He is based at a Severo Ochoa Centre of Excellence, underscoring the high impact and collaborative nature of his research.

Gherardo Varandoمشاهده پروفایل

استادیار

• Uncertainty Quantification
• Probabilistic Graphical Models
• Graphical Models for Dynamical Systems
• +۴ مورد دیگر

Gherardo Varando is an Assistant Professor at the University of Valencia's Department of Statistics and Operational Research, and a researcher in the Image and Signal Processing Group. His work focuses on causal inference, probabilistic graphical models, and their applications in Earth sciences and health data analysis. He holds a PhD and has been a faculty member since 2024. Research interests include uncertainty quantification, staged event trees, and spatio-temporal causal discovery. Varando has published extensively on topics like causal representation learning, staged tree models, and kernel methods for pairwise causal discovery. His contributions span machine learning theory, statistical methodology, and interdisciplinary applications in climate science and biomedicine. Key achievements include the development of the stagedtrees R package for structural learning of graphical models, and open-source tools like leaflet-map-builder for geospatial visualization. His work bridges theoretical advancements with practical implementations, addressing challenges in causal structure learning and interpretable AI.