جست‌وجوی استاد و پژوهشگر

• Biomechanics
• Mechanobiology
• Computational systems biology
• +۷ مورد دیگر

Jérôme Noailly is a Full Professor at the Universitat Pompeu Fabra (UPF), leading the Biomechanics and Mechanobiology Area at the Barcelona Centre for New Medical Technologies. As head of the Multiscale and Computational Biomechanics & Mechanobiology (MBIOMM) group, he specializes in computational modeling of musculoskeletal systems, with a focus on intervertebral discs, osteoporosis, and inflammation-driven degeneration. Education: BSc in Physical Chemistry, Engineer’s/MSc in Materials Science, MSc in Acoustics, and a PhD in Spine Biomechanics (UPC, 2006). Key career milestones include a Marie Skłodowska-Curie fellowship (2006–2009), Ramon y Cajal fellowship (2016), and ERC Consolidator Grant (2023). He currently co-directs the SIMBIOSys group and coordinates EU projects such as Disc4All. Research interests span biomechanical modeling, computational systems biology, medical imaging integration, and machine learning applications. Over 50 peer-reviewed articles, 150+ conference contributions, and 15 PhD supervisions reflect his prolific output. Awards include the UPC Best PhD Thesis (2009) and leadership roles in the European Society of Biomechanics (ESB), including Vice-President (2022–2024). Teaching includes Biomedical Engineering courses at UPF, and leadership roles in academic administration (e.g., Bachelor’s program coordination, international mobility). His work bridges experimental and computational approaches to address complex biomedical challenges like disc degeneration and osteoarthritis.

Nir Lipovetzkyمشاهده پروفایل

دانشیار

• AI Planning
• Search
• Learning
• +۶ مورد دیگر

Nir Lipovetzky is an Associate Professor in Artificial Intelligence at the School of Computing and Information Systems, University of Melbourne. He is affiliated with the Agent Lab and Digital Agriculture, Food and Wine Lab. His research focuses on AI planning, search, and applications in autonomous systems, particularly in agriculture. He holds a PhD from Universitat Pompeu Fabra (2012) and a BSc in Computer Science (2004). Education: PhD in Artificial Intelligence, Universitat Pompeu Fabra (2012) MEng in Artificial Intelligence, Universitat Pompeu Fabra (2007) BSc in Computer Science, Universitat Pompeu Fabra (2004) Graduate Certificate in University Teaching, University of Melbourne (2020) Research interests include AI planning, constraint programming, operations research, and intention recognition. He has developed novel width-based planning algorithms and contributed to planning competitions. Recent work includes adaptive goal recognition and reinforcement learning for decision-making under uncertainty. Publications span topics like count-based novelty exploration, process mining for goal recognition, and human-like goal inference models. Awards include the Best Student Paper Award at AAMAS 2024 and recognition in planning competitions. Advises 10+ PhD and Master’s students on topics like exploration methods, agricultural robotics, and multi-agent systems. Supervises Farm.bot, an open-source platform for AI-driven agriculture. Serves as Conference Chair for ICAPS 2025 and has held roles in AAAI, IJCAI, and ICAPS committees.

Andrés Occhipinti Libermanمشاهده پروفایل

استادیار

• Artificial Intelligence
• Natural Language Processing
• Planning
• +۶ مورد دیگر

Andrés Occhipinti Liberman is an Assistant Professor at the Department of Telematics and Computer Science within the ICAI School of Engineering at Comillas Pontifical University (Madrid, Spain). He teaches Natural Language Processing and Foundations of AI, focusing on search, logic, statistical inference, and Markov decision processes. Education: Ph.D. in Artificial Intelligence and Logic from the Technical University of Denmark (DTU) M.Sc. in Logic (cum laude) from the University of Amsterdam's Institute for Logic, Language and Computation (ILLC) Research Interests: Dr. Occhipinti Liberman specializes in improving language models' reasoning and planning capabilities. His work spans action model learning, epistemic logics, theory-of-mind reasoning, game theory, and formal methods in AI. He explores dynamic term-modal logics for modeling social networks and epistemic planning in multi-agent systems. Publications: His recent work emphasizes formal systems for reasoning about belief dynamics, social network evolution, and grounded symbolic planning. Key themes include decidability in epistemic planning, logical frameworks for theory-of-mind agents, and learning symbolic representations from observations. Awards: No scientific awards explicitly mentioned. Advising & Grants: No students or grants explicitly listed in the provided text. Labs/Teams: No specific lab affiliations mentioned beyond his academic department.

Piotr Zwiernikمشاهده پروفایل

دانشیار

• Graphical Models
• Covariance Matrix Estimation
• Convex Analysis
• +۷ مورد دیگر

Piotr Zwiernik is a Professor Agregat in the Department of Economics and Business at Universitat Pompeu Fabra (UPF), Barcelona, and a member of the BSE Data Science Center. He is currently on leave from the Department of Statistical Sciences and the Department of Mathematics at the University of Toronto. His research bridges statistics, algebraic geometry, and machine learning, focusing on graphical models, covariance estimation, tensors, and algebraic methods in statistics. Research Interests: Graphical Models Covariance Matrix Estimation Convex Analysis Tensors Algebraic and Combinatorial Methods in Statistics Statistical Learning Theory His recent publications span high-impact journals such as the Annals of Statistics , Biometrika , and Journal of the Royal Statistical Society . The work demonstrates a consistent trend in developing mathematically rigorous frameworks for understanding dependence structures, latent variable models, and high-dimensional inference, often leveraging tools from algebraic geometry and convex optimization. Key themes include total positivity, tensor methods, and the geometry of statistical models. Scientific Recognition: Editorial Board Member, Journal of the Royal Statistical Society Series B (JRSS-B) Editorial Board Member, Biometrika Editorial Board Member, Scandinavian Journal of Statistics Editorial Board Member, Algebraic Statistics Zwiernik actively mentors students and is seeking PhD candidates with strong mathematical backgrounds at UPF and the Institute of Mathematics of UPC. He has led the development of several open-source R packages, including golazo , MTP2binary , and StructuralEM , facilitating research in graphical models and latent structures. His work is supported by a network of collaborations with leading statisticians and has significant theoretical and applied implications in data science. Laboratories and Research Groups: Statistics@UPF BSE Data Science Center

Luca Russoمشاهده پروفایل

دانشیار

• Motor and Sports Activity
• Biomechanics
• Human Movement Analysis
• +۷ مورد دیگر

Prof. Luca Russo is an Associate Professor in Methods and Teaching of Motor Activities at the Università degli Studi eCampus, Italy, affiliated with the Department of Theoretical and Applied Sciences. He teaches Ergonomics in Physical Exercise and Adapted Physical Activity, contributing to the academic development of students in motor sciences. His research interests span a broad spectrum of topics including motor and sports activity , biomechanics and human movement analysis , ergonomics , posture , kinesiology , and physical training for preventive, compensatory, adapted, and performance purposes. His expertise is grounded in a PhD in Disciplines of Motor and Sports Activities, a Master in Posturology, specialization in Kinesiology, and a degree in Orthopedic Techniques and Podiatry. His recent publications focus on virtual reality interventions, sports performance in youth and elderly populations, lifestyle interventions for overweight women, and machine learning applications in clinical biomechanics. These works reflect a strong trend in applied biomechanics , motor learning , and interdisciplinary health research , often utilizing advanced measurement techniques and collaborative international studies. Notably, one of his review articles was featured as the cover of its journal issue and received the Best Paper Award 2023 in Sports by MDPI . Best Paper Award 2023 in Sports by MDPI Prof. Russo actively collaborates with researchers such as Gian Mario Migliaccio, Johnny Padulo, and Mike Maric. While specific grant details and advisees are not listed, his publication record and academic role suggest a strong engagement in research mentorship and project leadership. He is involved in studies related to virtual reality rehabilitation , football for aging populations , and biomechanical diagnostics , indicating a forward-looking research agenda in digital health and performance science.

K M Ashraful Islamمشاهده پروفایل

استادیار

• Geospatial Analysis
• Remote Sensing
• Urban Microclimate
• +۵ مورد دیگر

K M Ashraful Islam is currently a PhD candidate and graduate teaching/research assistant in Geography and Geospatial Sciences at Oregon State University (OSU), USA, where he also earned his Master's degree in 2023. Previously, he served as an assistant professor (currently on study leave) in the Department of Urban and Regional Planning at Chittagong University of Engineering and Technology (CUET), Bangladesh. Education: PhD in Geography and Geospatial Sciences (in progress), Oregon State University Master of Science in Geography and Geospatial Science, Oregon State University (2023) Islam's research integrates geospatial analysis, remote sensing, and machine learning to address environmental challenges including urban microclimate, landscape disturbance monitoring, and earth system processes. His work emphasizes developing practical tools for stakeholders through methodologies like deep learning and system digitalization, with particular focus on creating adaptable solutions for mangrove ecosystems and urban environmental phenomena. His publication record reveals strong methodological innovation in geospatial technology application, particularly in leveraging Google Earth Engine for global mangrove monitoring and analyzing urban lightning patterns. These studies demonstrate consistent application of advanced computational approaches to solve complex spatial and temporal environmental problems across diverse geographical contexts.

• Machine Learning
• Approximate Inference
• Optimal Control
• +۶ مورد دیگر

Vicenç Gómez is an Associate Professor in the Department of Engineering at Universitat Pompeu Fabra (UPF), where he leads research in artificial intelligence and machine learning. He serves as Coordinator of the Erasmus Mundus Joint Master in Artificial Intelligence and the MSc program in Intelligent and Interactive Systems, and teaches in the BSc in Mathematical Engineering in Data Science. His research interests include machine learning, approximate inference, optimal control, and complex networks , with applications in social networks, robotics, brain-computer interfaces, and urban systems. He applies advanced AI techniques to model human behavior, network dynamics, and decision-making processes. The recent publications highlight a strong focus on graph-based learning, reinforcement learning, social network analysis, and health informatics . His work integrates theoretical advances in probabilistic modeling with real-world applications in digital platforms, environmental monitoring, and mental health. There is a consistent theme of modeling complex systems through structured AI and interpretable models. Scientific Awards and Recognition: Coordinator of the prestigious Erasmus Mundus Joint Master in Artificial Intelligence Local Chair of UAI 2024, a top-tier conference in AI Program Committee member for ICAPS 2024 Organizer of the EMAI Summer School in collaboration with UCL Advising and Grants: Vicenç Gómez actively supervises PhD and Master's students, including Nur Alvarez-Gonzalez, Roger Garriga, Emily Theophilou, and Sergio Calo. His advising spans topics in emotion detection, mental health modeling, air quality prediction, and representation learning. He has been involved in organizing major academic events and leading international educational programs, indicating significant leadership and collaborative grant activity. Labs and Research Groups: He is a key member of the Artificial Intelligence and Machine Learning group at UPF’s Department of Engineering, based at the Roc Boronat building in Barcelona. His team engages in interdisciplinary research combining AI theory with applications in social, health, and urban domains.

• Aerospace Engineering
• Optimal Control Theory
• Air Traffic Management
• +۵ مورد دیگر

Manuel Fernando Soler Arnedo is a Full Professor in the Aerospace Engineering Department at Carlos III University of Madrid's College of Engineering. His research focuses on Aerospace Engineering with specialization in Optimal Control Theory , Climate Impact Mitigation , and Artificial Intelligence applications for air traffic systems. He leads the Aerospace Engineering Research Group and has contributed extensively to Flight Trajectory Optimization , Weather-Induced Uncertainty , and Network-scale Conflict Resolution . Principal Researcher on EU-funded projects like F4EClim (2024-2027) and KAIROS (2023-2026) Key international collaborations with NEXTOR (UC Berkeley) and ETH Zurich Developed tools like CLIMaCCF V1.0 and ROOST V1.0 for climate-aware flight planning His work integrates Artificial Intelligence with Climate Modeling to address 4D Trajectory Planning , Thunderstorm Avoidance , and Non-CO2 Emission Reduction in aviation. Recent publications emphasize Robust Optimization under meteorological uncertainty and Deep Learning for traffic flow management. He has supervised theses on Data Science for Weather Mitigation and Multi-objective Space Mission Design , with grants from European Commission , Boeing , and Spanish government agencies .

Mario Merino Martinezمشاهده پروفایل

استاد

• Plasma Physics
• Electric Propulsion
• Space Propulsion Systems
• +۶ مورد دیگر

Mario Merino Martínez is a Full Professor of Aerospace Engineering at Universidad Carlos III de Madrid (UC3M), leading the Plasmas and Space Propulsion Team (EP2). His research focuses on advanced electric propulsion systems, particularly electrodeless plasma thrusters (EPTs), magnetic nozzles, and plasma modeling. He holds an ERC Starting Grant (ZARATHUSTRA) to develop next-generation space propulsion technologies and has pioneered numerical tools like PWHISTLER and EP2PLUS for plasma simulation. Merino's work integrates experimental and computational approaches, collaborating with institutions like MIT, ONERA, and Airbus. He has published over 100 peer-reviewed articles on topics such as magnetic nozzle dynamics, ECR thruster optimization, and plasma-wave interactions. His group's experimental lab includes a 1.5m-diameter vacuum chamber with advanced diagnostic systems for thruster testing. Award-winning educator, Merino teaches aerospace courses in English, including a popular edX MOOC ('The Conquest of Space'). He supervises 6 ongoing PhD theses and has advised numerous students on plasma physics and propulsion. Beyond academia, he co-founded 'La Facultad Invisible' to improve STEM education and participates in initiatives like the ST3LLAR lab with SENER Aerospace. Awards: ERC Starting Grant (ZARATHUSTRA), H2020 MINOTOR Project Lead Grants: €3.5M+ funding from EU, Spanish Ministry, and private sector Labs: EP2 Plasma Lab (UC3M), ST3LLAR Collaboration His current projects aim to revolutionize space travel via electrodeless thrusters, addressing challenges in plasma detachment, wave energy absorption, and scalability for deep-space missions.

• Aeronautics
• Biomedicine
• Electronics
• +۷ مورد دیگر

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.

Alejandro F Frangiمشاهده پروفایل

استاد

• Medical Image Analysis
• Computational Physiology
• Machine Learning
• +۳ مورد دیگر

Alejandro F Frangi holds the Diamond Jubilee Chair in Computational Medicine and Royal Academy of Engineering Chair in Emerging Technologies at the University of Leeds, UK, with dual affiliation at the Faculties of Engineering and Medicine, KU Leuven, Belgium. His research bridges medical image analysis and computational modelling, emphasizing machine learning for phenomenological models and computational physiology for mechanistic systems. Key specializations include statistical population imaging and in silico clinical trials, driving innovation in computational medicine. Major scientific recognitions include: IEEE Fellow SPIE Fellow EAMBES Fellow

Jordi Muñozمشاهده پروفایل

دانشیار

• Signal Processing
• Machine Learning
• Pattern Recognition
• +۶ مورد دیگر

Jordi Muñoz is an Associate Professor at the University of Valencia's Department of Electronic Engineering, part of the Faculty of Electronics Engineering. He has been affiliated with the university since 1998 and is a member of the Image and Signal Processing Group (ISP) and Image Processing Laboratory (IPL). His research focuses on signal processing, machine learning, and remote sensing applications in Earth observation, climate science, and vegetation monitoring. He has authored over 170 publications and holds leadership roles in interdisciplinary projects involving AI-driven environmental modeling and educational technology. Research Interests: Through advanced machine learning techniques, Muñoz explores topics such as medicanes forecasting, drought displacement patterns, crop yield estimation, and vegetation parameter retrieval using satellite data. His work bridges signal processing fundamentals with practical applications in climate science and education innovation. Key Projects: Recent contributions include AI models for medicanes monitoring (2024), causal discovery in environmental displacement studies (2024), and GPT-4-based educational tools for automated question generation (2024). He collaborates extensively with institutions like the European Space Agency (ESA) and global research networks. Labs/Teams: Active member of the Image and Signal Processing Group (ISP), leading projects on Gaussian processes for biophysical parameter estimation and cloud detection algorithms. His team develops algorithms for Earth observation data fusion and interpretable machine learning models in geosciences.

• Quantum Information Theory
• Quantum Computing
• Theoretical Physics
• +۳ مورد دیگر

John Calsamiglia Costa is a Professor in the Department of Physics at Universitat Autònoma de Barcelona (UAB), affiliated with the Grup d'Informació Quàntica (GIQ). He holds a PhD in Theoretical Physics from the University of Helsinki (2002) and a Licenciatura in Physics from UAB (1996). His research focuses on quantum information theory, quantum computing, and theoretical physics, with emphasis on quantum metrology and hypothesis testing. He has led major projects such as DigiQ (Digitally Enhanced European Quantum Technology Master) and QENIA (National Quantum Computing Ecosystem for AI). Calsamiglia has supervised 38 students and contributed to over 70 publications. He received the prestigious Ramón y Cajal Fellowship (2005-2010) and has been involved in international collaborations across Europe and the US.

• Microbiology
• Infectious Diseases
• Climate Change Impact
• +۳ مورد دیگر

Jaime Luis Martínez Urtaza is a researcher in the Department of Genetics and Microbiology, affiliated with the Grup de Genòmica, Bioinformàtica i Biologia Evolutiva (GBBE). He leads and co-leads multiple international and national research projects, including the ID Alert initiative for climate-resilient health systems and the Population Genomics of Adaptation study. His work focuses on microbial pathogens like Vibrio species, their environmental drivers, and the impacts of climate change on infectious diseases. He collaborates globally on topics ranging from epidemiology of hemorrhagic fever to bat mortality investigations. Key Projects: EUP_AHW: European Partnership Animal Health and Welfare (2024-2030) POPULATION GENOMICS OF ADAPTATION (2022-2025) ID Alert: Infectious Disease decision-support tools (2022-2027) Research interests include microbial genomics, climate change's role in pathogen dynamics, and application of machine learning for ecological forecasting. Over 135 publications and a h-index of 44 reflect his prolific output in areas like Vibrio parahaemolyticus evolution and nanoplastic toxicity.

• Computer Vision
• Machine Learning
• Pattern Recognition
• +۸ مورد دیگر

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.