جستجوی استاد راهنمای دانشگاهی

• Nanophotonics
• Quantum Dots
• Optoelectronic Materials
• +۲ مورد دیگر

Dr. Rajesh Bera is a Research Fellow at ICFO's Functional Optoelectronic Nanomaterials group specializing in quantum-confined nanostructures. His research examines ultrafast carrier dynamics, excitonic properties, and optoelectronic applications of nanomaterials including quantum dots, nanoplatelets, and hybrid nanostructures. Current investigations focus on intraband transitions in doped nanocrystals, orientation-dependent excitonic behavior in 2D materials, and charge transfer mechanisms in heterostructure devices. Work bridges fundamental photophysics with applications in photodetection, sensing, and energy conversion. Recent publications demonstrate expertise in time-resolved spectroscopy of quantum materials, nanomaterial synthesis via colloidal chemistry, and rational design of optoelectronic devices. Continually develops novel characterization methods to probe ultrafast processes at nanoscale interfaces.

Chang-Tai Hsiehمشاهده پروفایل

استاد

• Economic development
• Growth in Asia and Latin America
• Applied economics
• +۴ مورد دیگر

Chang-Tai Hsieh is the Phyllis and Irwin Winkelried Distinguished Service Professor of Economics at the University of Chicago Booth School of Business. He is also a PCL Faculty Scholar with the university. His academic appointments include being a Research Associate for the National Bureau of Economic Research, a Senior Fellow at the Bureau for Research in Economic Analysis of Development, and a member of the Steering Group of the International Growth Center in London. His research interests focus on economic development, growth in Asia and Latin America, and applied economics, with particular expertise in macroeconomics. He has conducted extensive research on growth and development patterns across different regions, with special attention to China's economic transformation. His work examines resource allocation, innovation dynamics, trade policy impacts, and structural economic changes. Hsieh's recent publications reveal a strong focus on US-China economic relations, Chinese economic development, and the dynamics of innovation and growth. His research spans multiple subfields including trade policy, resource allocation, economic measurement, and the political economy of development. He has made significant contributions to understanding the economic transformation in East Asia, particularly regarding China's growth model and its implications for global trade. Alfred P. Sloan Foundation Research Fellowship Elected Member of Academia Sinica Two-time recipient of the Sun Ye-Fang Prize Fellow of the American Academy of Arts and Sciences Fellow of the Econometric Society Hsieh has been a visiting scholar at multiple Federal Reserve Banks (San Francisco, New York, and Minneapolis), the World Bank's Development Economics Group, and the Economic Planning Agency in Japan. He is also an active commentator on economic policy, with numerous opinion pieces published in Commonwealth Magazine, Project Syndicate, and other major outlets, particularly focusing on US-Taiwan-China economic relations and trade policy.

Paolo Rotaمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Multimodal AI
• +۹ مورد دیگر

Paolo Rota is a tenure-track Assistant Professor at the University of Trento, affiliated with the Department of Information Engineering and Computer Science (DISI) and the Center for Mind/Brain Sciences (CIMeC). His research lies at the intersection of computer vision, machine learning, and multimodal AI, with a strong emphasis on vision-language models and activity recognition. His research interests include zero-shot action recognition, temporal action localization, open-world recognition, and person image synthesis. He explores how large multimodal models can be leveraged for practical applications in video analytics and industrial AI, often developing training-free or source-free adaptation methods that improve model generalization. Recent publications show a consistent trend in utilizing large vision-language models (e.g., CLIP, LMMs) for tasks such as image classification, domain adaptation, and action recognition, emphasizing simplicity, zero-shot capabilities, and real-world applicability. His work frequently appears in top venues including CVPR, NeurIPS, ICCV, and ICIAP. He actively mentors PhD students including Benedetta Liberatori, Jiaqi Liu, Yan Shu, Shiyao Xu, and Alessandro Conti, often co-advising with faculty such as Elisa Ricci and Nicu Sebe. He also contributes to teaching, including delivering lectures on machine learning for the MSc in Data Science program. He co-founded Mountain Maps, a startup using AI to enhance outdoor navigation and mountain exploration. His work bridges academic research and practical innovation, aiming to increase the real-world impact of AI systems.

Mariano Cabezasمشاهده پروفایل

پژوهشگر

• computer vision
• medical imaging
• magnetic resonance imaging (MRI)
• +۵ مورد دیگر

Mariano Cabezas is a researcher in medical imaging and computer vision, currently affiliated with Macquarie University and as an affiliate at the University of Sydney . His work focuses on automating brain MRI analysis for pathologies like multiple sclerosis, Alzheimer's disease, and tumors, with additional contributions to UAV image analysis. PhD in Computer Science (2013), University of Girona MSc in Automation, Computation, and Systems (2010), University of Girona BSc in Computer Science (2009), University of Girona Research Interests : Specializes in magnetic resonance imaging , lesion detection , deep learning , and image processing , with applications in multiple sclerosis , hearing loss , and UAV-derived ecological data . His recent work includes federated learning frameworks for cross-site MS lesion segmentation and pseudo-labeling techniques for longitudinal brain volume estimation. Publication Trends : Over the past five years, his research has emphasized federated learning (4 articles), lesion segmentation (9 articles), and UAV image analysis (3 articles), with a strong focus on clinical validation and cross-institutional collaboration. Labs & Collaborations : Contributed to the NIC-VICOROB group at the University of Girona and maintains affiliations with the Research Institute of the Hospital Vall d'Hebron (VHIR) in Barcelona and Macquarie University in Sydney. Actively develops open-source tools hosted on GitHub.

Francisco Martinez Sanchezمشاهده پروفایل

استاد

• Industrial Organization
• Game Theory
• Competition Economics
• +۲ مورد دیگر

Francisco Martinez Sanchez is Professor in the Department of Quantitative Methods for Economics and Business at Universidad de Murcia's Faculty of Economics and Business. His research focuses on industrial organization, intellectual property protection, competition policy, and game theory applications in software markets and media industries. He leads the Time Series and Econometrics research group. His extensive publication record examines piracy economics, market competition, privatization policies, and behavioral economics. Education includes a PhD from Universitat d'Alacant (2008) on commercial piracy economics. Contact: fms@um.es

Antonio Cabralesمشاهده پروفایل

استاد

• Economic Networks
• Mechanism Design
• Experimental Economics
• +۳ مورد دیگر

Antonio Cabrales is a Full Professor (Research Chair in Economics) at Universidad Carlos III de Madrid. He holds a Ph.D. in Economics from the University of California, San Diego, and a B.A. from Universidad Complutense. He previously served as Professor and Head of the Economics Department at University College London and Professor at Universitat Pompeu Fabra in Barcelona. Currently, he is Executive Vice President of the European Economic Association and an Honorary Fellow of both the European and Spanish Economic Associations. His research focuses on social networks, mechanism design, learning and evolutionary games, experimental economics, behavioral economics, and industrial organization. He has held editorial roles at the Journal of Economic Theory , Journal of the European Economic Association , and SERIEs , among others. Recent work explores topics such as gender stereotypes in team formation, climate change mitigation strategies, and the impact of education policies. Cabrales’ experimental studies often address policy-relevant questions, including redistributive politics, bullying prevention, and vocational training efficacy. His contributions bridge theoretical insights with practical applications in education, labor markets, and environmental policy. Scientific Awards: Honorary Fellow, European Economic Association Honorary Fellow, Spanish Economic Association Grants & Advising: Extensive funding for projects on climate policy, education reform, and social norms. Advised numerous institutions on policy design, including experimental evaluations of school systems and labor market interventions. Labs & Teams: Leads research initiatives such as TeensLab, focusing on adolescent economic behavior, and collaborates with interdisciplinary teams on climate change and social network dynamics.

• Macroeconomics
• Financial Frictions
• Entrepreneurship
• +۷ مورد دیگر

Andrea Caggese is an Associate Professor in the Department of Economics and Business at Universitat Pompeu Fabra (UPF), Barcelona, Spain. He is a member of the Applied Macroeconomics and Quantitative Methods Research Group and actively contributes to research in macroeconomics, financial frictions, firm dynamics, and innovation. Research Interests: His research spans macroeconomics, financial constraints, entrepreneurship, investment, and productivity. He investigates how financial frictions affect firm behavior, labor allocation, and innovation, particularly focusing on intangible capital and the impact of economic shocks such as the 2020 pandemic recession. Recent Publications Trends: His recent work, published in journals like the Journal of Banking and Finance and European Economic Review , emphasizes the interplay between financial constraints, innovation types (radical vs. incremental), and macroeconomic fluctuations. A recurring theme is the amplification of shocks through firm-level financial vulnerabilities and the role of policy in mitigating misallocation. Scientific Awards: ICREA Acadèmia (2023–2029) Grant for Institutions and Financial Assts under Asymmetric Information (2006) Grant for Financial Decisions under Imperfect Information (2002) Grant for Fiscal and Monetary Policy under Market Imperfections (2002) Advising and Grants: He has advised PhD students including Roger Magi Gomis Porquet and Alfonso Ugarte Ruiz. He leads multiple research projects, such as Intangibles, Technology Diffusion and Public Policies (European Investment Bank) and Heterogeneidad de empresas y hogares, fluctuaciones agregadas y políticas macroeconómicas (Spanish National Research Agency). He has also participated in editorial boards for journals including American Economic Review and Economic Journal . Labs and Teams: He is a core member of the Applied Macroeconomics and Quantitative Methods Research Group at UPF, collaborating with researchers across Europe and contributing to policy-relevant macroeconomic analysis.

• Signal Processing
• Machine Learning
• Acoustics
• +۷ مورد دیگر

Luis Antonio Azpicueta Ruiz is an Associate Professor in the Department of Signal Theory and Communications at Carlos III University of Madrid. He leads research in the Signal Processing and Learning Group (GTSA) and Machine Learning for Data Science (ML4DS) group, focusing on interdisciplinary applications spanning acoustics, telecommunications, and machine learning. Research Interests: His work bridges signal processing theory with practical applications in environmental acoustics, adaptive filtering systems, and machine learning. Key research themes include: Advanced adaptive filtering architectures for nonlinear systems Distributed estimation in sensor networks Acoustic echo cancellation and room equalization Psychoacoustic evaluation methods Machine learning applications in noise monitoring and sound analysis Research Projects: Principal investigator for multiple funded projects including: Diagnóstico del ruido de chorro en aeronaves (AEI, 2022-2025) LearnINg FLow and Noise Dynamics via AI (COMUNIDAD DE MADRID, 2024-2026) BODYinTRANSIT - Sensory-driven Body Transformation (EUROPEAN COMMISSION, 2022-2026) Aprendizaje Automático para análisis Big Data (MINISTERIO DE ECONOMÍA, 2018-2021)

• Numerical Methods
• Partial Differential Equations
• Computational Mathematics
• +۳ مورد دیگر

Francisco Manuel Bernal Martínez is an Associate Professor in the Department of Mathematics at Carlos III University of Madrid. His research focuses on numerical methods, partial differential equations, and computational mathematics, with applications in industrial engineering and materials science. He leads projects such as 'Financiación adicional 5º año (2022)' and collaborates on initiatives like 'Clustering Automático de Comportamientos de Invertebrados en Libertad mediante Imagen 3D.' His work emphasizes domain decomposition algorithms, radial basis functions, and stochastic control problems. He has advised at least one PhD thesis and holds grants from regional and national funding bodies. Key research interests include meshless methods, probabilistic domain decomposition, and uncertainty quantification in energy systems. Recent publications highlight advancements in hybrid algorithms for large-scale PDEs and volatility modeling. Bernal Martínez actively participates in academic networks and has presented at international conferences on computational methods and industrial mathematics.

Belen Masiaمشاهده پروفایل

دانشیار

• Computational Imaging
• Applied Perception
• Virtual Reality
• +۴ مورد دیگر

Belen Masia is a tenured Associate Professor in the Computer Science Department at Universidad de Zaragoza , Spain. She is affiliated with the Graphics & Imaging Lab (part of the I3A Institute ) and the Vision, Image and Neurodevelopment Group (within the IIS Aragon Institute ). Her research bridges computational imaging , applied perception , and virtual reality , focusing on modeling human visual behavior and improving graphics/vision algorithms through perceptual insights. Education : Ph.D. in Computer Science (Eurographics PhD Award 2015), postdoctoral work at Max Planck Institute for Informatics . Research Highlights : Virtual Reality : Studying user behavior, saliency prediction, multimodal perception, and cinematography in VR. Appearance Modeling : Developing intuitive material representations and metrics for editing. Applied Perception : Leveraging human vision insights to diagnose defects in non-verbal patients. Computational Displays : Exploring HDR imaging and display optimization. Scientific Awards : Eurographics Young Researcher Award 2017 Eurographics PhD Award 2015 MIT Technology Review Top Ten Innovators Below 35 in Spain 2014 NVIDIA Graduate Fellowship 2012 Leonardo Fellowship from BBVA Foundation 2020 Leadership & Editorial Roles : Co-chair of Full Papers track at Eurographics 2026 Associate Editor for ACM Transactions on Graphics, Computers and Graphics, and ACM Transactions on Applied Perception Co-founder of DIVE Medical , a startup for automated visual function diagnosis PhD Students : Dario Lanza (2025, Modeling, Perception and Editing of Volumetric Materials ) Daniel Martin (2024, Computational Models of Visual Attention in VR , Best PhD Thesis Award EGSE) Julia Guerrero-Viu (2023, WiGRAPH Rising Star) Sandra Malpica (2023, VR Gaze Behavior ) Manuel Lagunas (2021, BBVA/SCIE Young Researcher Award) Ana Serrano (2019, Eurographics PhD Award & Unizar Outstanding Thesis) Collaborations & Grants : Involved in the EU-funded PRIME Innovative Training Network (predictive rendering and appearance reproduction) and leading projects on deep learning for pediatric visual diagnosis.

• Regional Economic Growth
• Technological Innovation
• Intangible Capital
• +۷ مورد دیگر

Maria Mercedes Gumbau Albert is an Associate Professor at the Faculty of Economics, Universitat de València, Spain, where she works in the Department of Economic Analysis, focusing on the Fundamentals of Economic Analysis. Her research centers on regional economic growth, technological innovation, intangible capital, and entrepreneurship, with empirical applications to Spanish and OECD regions. Research Interests: Her work spans regional productivity , technological spillovers , human capital , and infrastructure economics . She investigates how intangible assets, health, and education influence regional performance, and how innovation and entrepreneurship respond to economic crises. Her methodological approach is largely empirical and econometric, often using regional datasets. Recent Publications Trend: Her most recent articles (2022–2024) emphasize intangible capital as a driver of labor productivity and entrepreneurship, marking a shift toward knowledge-based growth analysis. Earlier works focused on transport infrastructure, patents, and technological inequalities, showing a consistent interest in regional disparities and innovation systems. Scientific Contributions: PhD in Economics from Universitat de València (1996) Supervised doctoral research (e.g., thesis on technological innovation) Active publication record from 1993 to 2024 Focus on policy-relevant economic analysis for Spanish regions Advising and Grants: While specific grants and advisees are not listed, her supervision of a PhD thesis indicates mentoring experience. No explicit funding sources are mentioned in the provided text. Labs and Teams: No specific research labs, centers, or collaborative teams are mentioned in the available information.

• Consumer Behavior
• E-commerce
• Marketing Strategy
• +۳ مورد دیگر

Marta Arce Urriza is a Post University Professor at the Public University of Navarra, specializing in Business Management within the Department of Business Management at the Institute for Advanced Research in Business and Economics (INARBE). Her research focuses on consumer behavior in online and offline channels, multichannel retail strategies, and the impact of emerging technologies like AI on marketing and consumer adoption. She has contributed to doctoral programs in Economics, Business, and Law at her university and collaborates with institutions like the Autonomous University of Barcelona. Education: Earned a Doctorate in Business Administration and Management from the Public University of Navarra in 2009. Participated in research stays at the University of Chicago and University of Groningen. Research Interests: Consumer adoption of new technologies (e.g., AI chatbots, 3D printing) Online review dynamics and their influence on consumer decisions Privacy concerns in virtual assistant interactions Strategic comparisons between private labels and national brands in multichannel environments Recent Article Trends: Focus on generative AI’s role in retail, privacy implications of voice assistants, and leveraging text mining for brand analysis. Articles span journals like Journal of Retailing and Consumer Services and Technology in Society . Grants & Collaborations: Lead or co-PI in projects such as 'Generative AI Solutions for Intelligent Storytelling' (2025–2027) and 'Interaction with Virtual Assistants' (2022–2025), funded by Navarra Government and the Spanish Ministry of Science. Active in editorial roles for journals like Journal of Interactive Marketing . Labs/Teams: Involved in interdisciplinary research teams focusing on AI ethics, consumer behavior analytics, and multichannel strategy. Supervised doctoral student Miriam Alzate Barricarte’s thesis on electronic word-of-mouth implications.

Sergio Gómez Jiménezمشاهده پروفایل

دانشیار

• Complex Networks
• Complex Systems
• Neural Networks
• +۴ مورد دیگر

Sergio Gómez Jiménez is an Associate Professor in the Department of Computer Engineering and Mathematics at Rovira i Virgili University (URV), Tarragona, Spain. He joined URV in 1995 and has held his current position since 1997. He obtained degrees in Physics (1990) and Mathematics (1995) and a PhD in Physics (1994) from the Universitat de Barcelona. His research focuses on complex networks, including community structure analysis, epidemic spreading, urban congestion, and applications to biology, medicine, and social systems. He has authored over 100 publications in high-impact journals like Nature Methods and Physical Review Letters. He coordinates the interuniversity Master's in Biomedical Data Science and the PhD Program in Bioinformatics. His editorial roles include Associate Editor of Complexity and Review Editor of Frontiers in Physics. Notable awards include the American Physical Society's Outstanding Referee (2015) and the Web Science Trust's Test of Time Award (2024). His work on modeling the spatiotemporal spread of epidemics, such as the 2020 COVID-19 pandemic, has received significant attention. He also contributed to urban traffic congestion analysis and developed algorithms for hierarchical clustering (e.g., MultiDendrograms). Collaborations span institutions like the University of Oxford and CERN, reflecting his interdisciplinary approach to complex systems.

• Consumer Behavior
• Consumer Choice Models
• Diffusion Models
• +۵ مورد دیگر

Antonio Ladrón de Guevara is an Associate Professor at Universitat Pompeu Fabra. His research focuses on consumer behavior, diffusion models, and network effects in marketing and economics. He holds a PhD from Universidad Carlos III de Madrid and has published extensively in journals like International Journal of Research in Marketing and Review of Economic Studies. His work combines theoretical models with empirical applications, addressing topics such as hybrid consumption patterns, technology interactions, and price competition dynamics. Key areas of exploration include the impact of network effects on market diffusion and strategic rivalry analysis in multi-market environments. Ladrón de Guevara’s methodologies frequently integrate multivariate analysis techniques and optimization algorithms to solve complex market problems. His academic contributions span over two decades, with notable papers analyzing the Spanish loans market, telecom industry evolution, and consumer decision-making processes. While no specific awards are listed, his prolific publication record reflects sustained scholarly impact. His research often bridges economic theory and applied marketing strategies, offering insights into both theoretical frameworks and practical market phenomena. Though no formal grants or labs are mentioned, his work indicates involvement in collaborative research teams focused on quantitative modeling and interdisciplinary market studies. His advising activities and educational roles remain unspecified in the provided texts.

Santiago Badiaمشاهده پروفایل

استاد

• Computational Science and Engineering
• Numerical Analysis
• Finite Element Methods
• +۳ مورد دیگر

Santiago Badia is a Full Professor of Computational Science and Engineering at Universitat Politècnica de Catalunya (UPC), holding an adjoint researcher position at the International Center for Numerical Methods in Engineering (CIMNE). He leads the Large Scale Scientific Computing (LSSC) group at CIMNE, focusing on finite element methods, numerical analysis, and high-performance computing. His research emphasizes fluid dynamics, multiphysics problems, and scalable solvers for large-scale systems. Previously, he worked at Politecnico di Milano and Sandia National Labs. He developed the FEMPAR software framework, a parallel finite element tool for PDE simulations, achieving landmark scalability (e.g., 60 billion unknowns on 458,672 cores). FEMPAR is recognized in the High-Q Club of European codes. His expertise includes discontinuous Galerkin methods, XFEM, and domain decomposition preconditioners. Research interests span metal additive manufacturing, superconductor devices, and nuclear engineering applications. Awards include FEMPAR's High-Q Club inclusion. He advises PhD and MSc students (e.g., Jesus Bonilla, Eric Neiva, Marc Olm) and has open positions in postdoc/PhD levels. His team includes researchers like Javier Principe and Alberto Martín. Ongoing projects involve advancing parallel algorithms, multiphysics simulations, and software scalability for exascale computing.