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Alysson Neves BessaniView profile

Associate Professor

• Distributed Systems
• Dependability
• Fault Tolerance
• +5 more

Alysson Neves Bessani is an Associate Professor at the Informatics Department of Faculdade de Ciências da Universidade de Lisboa, Portugal, and a member of the LaSIGE research group. His work focuses on distributed systems, Byzantine fault tolerance, and cybersecurity, with significant contributions to blockchain consensus and intrusion-tolerant architectures. Academic Rank: Associate Professor University: Universidade de Lisboa School: Faculdade de Ciências Department: Informatics Department Research Groups: LaSIGE, Navigators Research Interests span distributed systems design, Byzantine fault tolerance, adaptive consensus protocols, and secure multi-cloud storage. His work bridges theoretical foundations with practical implementations like the BFT-SMaRt library and the Vawlt startup. Scientific Awards include multiple Test-of-Time Awards (DSN'24, DSN'21), IBM Faculty Award (2017), and Best Student Paper at Middleware'19. He has advised numerous PhD and Master’s students, contributing to advancements in fault-tolerant systems. Publications (15 most recent) reveal trends in Byzantine consensus optimization, blockchain integration, and AI-driven threat detection. His interdisciplinary work combines distributed computing with genomics and IoT security, reflecting a broad impact across computer science.

• Data Mining
• Bioinformatics
• Machine Learning
• +3 more

Domingo Savio Rodríguez Baena is a Professor at Pablo de Olavide University, affiliated with the Department of Computer Languages and Systems. His research focuses on data mining, bioinformatics, and computational biology, with a particular emphasis on biclustering algorithms, gene co-expression networks, and high-performance computing applications. PhD in Engineering, Data Science, and Bioinformatics (2012) from Pablo de Olavide University His work spans interdisciplinary domains, including recommender systems , livestock behavior analysis , and biological data interpretation . Recent articles highlight his contributions to multi-GPU optimization , ensemble learning , and historical database construction . Key collaborations include the DATAi Intelligent Data Analysis and DASE Data Analytics Science & Engineering research groups. He has developed tools like the CyEnGNet–App for gene network visualization and BIGO for gene enrichment analysis. Contact: dsrodbae@upo.es

• Numerical Methods
• Partial Differential Equations
• Computational Mathematics
• +3 more

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.

Yann PontyView profile

Researcher

• RNA Folding
• RNA Design
• RNA Evolution
• +9 more

Yann Ponty is a tenured CNRS Researcher at the Computer Science Department (LIX) of École Polytechnique (Institut Polytechnique de Paris, France). He leads the AMIBio team and serves as Deputy Director of LIX. His work focuses on developing bioinformatics methods at the intersection of computer science, mathematics, and molecular biology, particularly for RNA structure prediction, design, and evolution. He holds leadership roles in the ISCB Board of Directors (2025-2027) and the HDR referent for the IDIA department (CS&Interactions) at IP Paris. Research Interests: RNA folding/design/evolution, RNA-RNA/RNA-protein interactions, random generation, enumerative combinatorics, discrete algorithms, parameterized complexity, RNA visualization Key Contributions: Developed algorithms for RNA inverse folding, pseudoknot modeling, and dynamic programming optimization Collaborations: Partnerships with institutions like Simon Fraser University, Boston College, and Université Paris-Saclay His recent publications (15 most recent) span RNA structure prediction, pseudoknot partition functions, linear-time inverse folding algorithms, and parameterized sampling techniques. The work emphasizes dynamic programming, combinatorial approaches, and integration of experimental data for improving RNA modeling. Scientific awards include election to the ISCB Board of Directors (2025-2027) and leadership roles in academic networks like GdR BIM. He actively contributes to software development (VARNA, RNANR, SPARCS, IncaRNAtion, RNARedPrint) and serves as Associate Editor for Bioinformatics (OUP). Teaching engagements include graduate-level courses in combinatorial optimization, RNA bioinformatics, and algorithms at Université Paris-Saclay and École Polytechnique.

Sebastian Tornil SinView profile

Associate Professor

• Automatic Control
• Fault Detection and Diagnosis
• Water Distribution Networks
• +6 more

Sebastian Tornil Sin is an Associate Professor in the Department of Automatic Control at Universitat Politècnica de Catalunya (UPC), affiliated with the Institut de Robòtica i Informàtica Industrial (IRI), a joint center of UPC and CSIC. His work focuses on fault detection, diagnosis, and monitoring in industrial and water distribution systems. His research interests lie at the intersection of automatic control , data-driven modeling , and industrial applications . He specializes in leak detection and localization in water networks using sensor data, classifiers, and reasoning frameworks like Dempster-Shafer and Bayesian methods. His work also extends to sensor placement optimization and human-robot task design in academic environments. The recent publications (2017–2022) show a consistent focus on applying machine learning and control theory to real-world infrastructure problems, particularly in water networks. Trends include hybrid data-expert systems, classifier-based fault localization, and incremental sensor deployment strategies. Scientific Awards: No awards mentioned in the provided text. Sebastian Tornil Sin actively contributes to research through collaborations with experts such as V. Puig, J. Blesa, and A. Soldevila. While no formal advising or grant information is available, his extensive publication record in journals like IEEE Transactions on Control Systems Technology and Computers and Chemical Engineering indicates strong research leadership and project involvement. He is part of the research team at the Institut de Robòtica i Informàtica Industrial (IRI) , where he contributes to projects in fault detection, monitoring systems, and robotics applications in industrial and urban infrastructure.

Mercè Roca i PuigvertView profile

Associate Professor

• International Business Management
• Marketing
• Consumer Behavior
• +7 more

Mercè Roca i Puigvert is an Associate Professor and researcher at Universitat Pompeu Fabra (UPF) and ESCI-UPF, with affiliations to the Barcelona School of Management. She holds a PhD in Management from Leeds University Business School (2006), a Master's in Economics and Business (UPF, 2002), and dual bachelor's degrees in Business Administration (UPF, 2000) and Economics (UPF, 1999). Her research focuses on International business and market research Consumer and organizational decision-making Sustainability, CSR, and circular economy Environmental policy and waste systems Data analytics for economic decisions Recent publications analyze complementary currency impacts, sustainable tourism, opera sector eco-design, and packaging waste policies. She leads the UNESCO Chair in Life Cycle and Climate Change projects and participates in EU-funded initiatives like GREENTOUR and LIFE15/ENV/ES/000209. As director of the MSc in International Business and academic coordinator for multiple programs, she integrates research into curriculum design and industry partnerships.

• RFID Technology
• Wireless Sensor Networks
• Internet of Things
• +5 more

Asier Perallos Ruiz is a Professor in the Faculty of Engineering at the University of Deusto, specializing in the Department of Computing, Electronics and Communication Technologies. His research focuses on RFID technology, wireless sensor networks, and computational intelligence applications with significant contributions to intelligent transport systems and antenna design. Dr. Perallos Ruiz's research interests span multiple domains with a focus on RFID technology , Wireless sensor networks , Internet of Things (IoT) , Computational intelligence , Evolutionary algorithms , and Intelligent transport systems . His work bridges theoretical advancements with practical applications, particularly in transportation systems, healthcare, and industrial automation. His research often involves interdisciplinary collaboration across engineering disciplines. His publication portfolio shows a consistent trend toward improving RFID systems, developing efficient anti-collision protocols, and applying computational intelligence to real-world problems. Recent work has focused on polarization-diversity rotation sensing, customizable RFID platforms, and the integration of RFID with IoT applications. His research demonstrates a progression from foundational RFID technology to more complex system integration and application-specific solutions. Dr. Perallos Ruiz has supervised several graduate students including Muralter Florian (2021), Arjona Aguilera Laura (2018), Cmiljanic Nikola (2018), Lopez Garcia Pedro (2016), and Moreno Emborujo Asier (2016). His research has been supported by various projects focusing on RFID technology, intelligent transportation systems, and wireless communication applications. He leads research teams focused on RFID systems development, wireless sensor networks, and computational intelligence applications. Current work appears to be advancing RFID sensing capabilities, energy-efficient protocols, and system integration for practical applications in transportation and industry.

Rafael SebastianView profile

Professor

• Cardiac Computational Modeling
• Artificial Intelligence in Medicine
• Medical Imaging
• +4 more

Rafael Sebastian is a Full Professor at Universitat de Valencia and General Director for Science and Research of the Generalitat Valenciana. He leads the Computational Multiscale Simulation Lab (CoMMLab) and collaborates with institutions like Oxford University and Yale University. Department of Computer Science, Universitat de Valencia CoMMLab Founder Spanish Network of Excellence in Cardiac Modeling His research focuses on multi-scale computational models and artificial intelligence for patient-specific cardiac simulations , aiming to improve arrhythmia risk stratification and therapy planning . Key topics include cardiac conduction system modeling , scar-related ventricular tachycardia , and machine learning pipelines for clinical applications. Recent publications emphasize automata-based simulations for atrial arrhythmias, machine learning in arrhythmia localization, and 3D geometric characterization of aortic diseases. Trends show integration of computational modeling with clinical data and medical imaging . Scientific Awards: Best Poster Award, Functional Imaging and Modeling of the Heart (2021) Cum Laude Award, SPIE Medical Imaging (2009) Student Presentation Award (2011) He has supervised 7 PhD/Master students and led grants exceeding €1 million, including projects like iSARC-GENETICS and iCardioTwins , focusing on digital twin technology and cardiac disease stratification .

• Consumer Behavior
• Consumer Choice Models
• Diffusion Models
• +5 more

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.

• Combinatorics
• Graph Theory
• Algebraic Combinatorics
• +4 more

Lluis Vena Cros is a distinguished researcher in the Department of Mathematics at Universitat Politècnica de Catalunya - BarcelonaTech (UPC-BarcelonaTech), affiliated with the Faculty of Mathematics and Statistics. He is a core member of the GAPCOMB research group, which specializes in Geometric, Algebraic and Probabilistic Combinatorics. His research spans multiple domains within combinatorics, with particular emphasis on graph theory, algebraic combinatorics, geometric combinatorics, and probabilistic combinatorics. Vena Cros has made significant theoretical contributions to the understanding of graph homomorphisms, Tutte polynomials, Ramsey theory, and extremal combinatorial structures. His work often explores the deep connections between combinatorial objects and other mathematical disciplines such as topology, algebra, and discrete geometry. An analysis of his recent publications reveals a consistent focus on combinatorial structures with applications across multiple mathematical domains. His work on Tutte polynomials for various graph structures demonstrates a unifying approach to graph invariants, while his research in Ramsey theory explores structural properties of large combinatorial objects. The recurring theme across his publications is the investigation of extremal properties and computational aspects of combinatorial configurations. Vena Cros actively participates in multiple research projects including 'Structure, Randomness and Computational Methods in Extremal Combinatorics,' 'COntemporary COmbinatorics and Applications (COCOA),' and the 'Grup GAPCOMB de la UPC.' These projects involve collaborations with numerous researchers across Spain and internationally, reflecting his significant standing in the combinatorial mathematics community. His work has been supported by various funding bodies including the Spanish State Research Agency and the European Union's Horizon 2020 program. As a member of the GAPCOMB research group, Vena Cros contributes to a vibrant mathematical community focused on advancing combinatorial theory and its applications. The group maintains strong connections with other research centers and regularly participates in international conferences and collaborative projects, fostering the exchange of ideas across the global combinatorial mathematics community.

• Nonlinear Differential Equations
• Mathematical Analysis
• Optimal Control
• +3 more

Francisco Javier Fernandez Fernandez is a Professor at the University of Seville's Department of Mathematical Analysis. His research focuses on nonlinear differential equations, optimal control, environmental modeling, and mathematical analysis. He teaches courses such as 'Derivation and Integration of Functions of a Real Variable' and 'Professional Software in Environmental Issues' across various mathematics and interdisciplinary programs. His research group, 'Nonlinear Differential Equations,' explores topics like Stieltjes differential equations, population dynamics, and eutrophication control. Recent work emphasizes applications in environmental systems (e.g., Vespa Velutina population modeling, urban heat islands) and digital twin technologies for real-time simulation. Publications from 2025 highlight advancements in Stieltjes derivative theory and functional spaces, while earlier works address water circulation optimization and 3D eutrophication models. His contributions span over two decades, with a strong emphasis on bridging mathematical theory and environmental engineering challenges. No scientific awards are listed, but his extensive publication record reflects sustained academic impact. Advising and grant details are not explicitly mentioned in the provided texts, though his teaching roles suggest involvement in mentoring students through coursework.

Sanjay K DharView profile

Professor

• Strategic Marketing Management
• Brand Management
• New Product Development
• +12 more

Sanjay K. Dhar, the James M. Kilts, Jr. Professor of Marketing at the University of Chicago Booth School of Business, is a leading scholar in strategic marketing management and retail dynamics. His work bridges empirical economic modeling with actionable business insights. Education: B.Tech (IIT), MBA (IIM), PhD (UCLA Anderson School) Affiliation: Faculty member at Chicago Booth since 1992 Research interests span brand management , consumer behavior , and retail strategy , with a focus on how economic factors and marketing mix variables influence household budget allocations and brand performance . His empirical work leverages massive datasets like Nielsen Homescan to uncover geographic patterns and long-term consumer trends . Recent publications examine on-screen cigarette product placement effects, WIC program impacts on cereal consumption, and retail format competition . His 2025 under-review paper extends these insights to multi-category budget reallocation during macroeconomic shifts. Scientific Recognition includes: William O’Dell Award Finalist (2012) Paul Green Award (2008) John D. C. Little Award (1995) McKinsey Teaching Excellence Award (2000) Hillel Einhorn Teaching Awards (2008, 2012) Dhar’s teaching philosophy emphasizes mastering fundamentals to solve complex marketing problems. He advises firms on strategic marketing and new product development while maintaining active research in consumer packaged goods (CPG) industries.

• Partial Differential Equations
• Mathematical Physics
• Harmonic Analysis
• +1 more

Albert Mas Blesa is an Associate Professor in the Department of Mathematics at Universitat Politècnica de Catalunya (Barcelona, Spain). His academic career spans positions at Universidad Autònoma de Barcelona (PhD 2011), Universitat Politècnica de Catalunya, Universitat de Barcelona, and Universitat Autònoma de Barcelona in postdoctoral roles. He specializes in Partial Differential Equations , Mathematical Physics , Harmonic Analysis , and Geometric Measure Theory . Education : PhD in Mathematics (2007-2011), Universitat Autònoma de Barcelona Master's in Advanced Mathematics (2006-2007), Universitat Autònoma de Barcelona Bachelor's in Mathematics (2001-2006), Universitat Autònoma de Barcelona His research focuses on the intersection of quantum mechanics and geometric analysis, particularly Dirac operators, MIT bag models, and nonlocal equations. Recent work explores heat kernel monotonicity, shape optimization, and spectral properties of relativistic systems. Collaborations with leading researchers like Xavier Cabré and Luis Vega highlight his contributions to theoretical and applied PDEs. His 15 most recent publications span topics from quantum dot modeling to fractional calculus, emphasizing variational methods, symmetry analysis, and spectral theory. Key themes include MIT bag models, Dirac operators, nonlocal CMC surfaces, and harmonic analysis on Lipschitz graphs. Albert Mas Blesa has no listed scientific awards in available records and no advising history is provided. His affiliations include UPC's Campus Diagonal Besòs and institutions across Spain's Catalan universities.

• 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.

• Algorithms
• Randomized Data Structures
• Divide-and-Conquer Algorithms
• +5 more

Salvador Roura Ferret is a faculty member at the Universitat Politècnica de Catalunya (UPC), affiliated with the Faculty of Informatics of Barcelona (FIB) and the Department of Computer Sciences. He is an active researcher in the ALBCOM group, focusing on algorithmics, bioinformatics, complexity, and formal methods. His research interests span algorithms , randomized data structures , divide-and-conquer methods , and computational complexity . His work often bridges theoretical computer science with practical applications in voting systems, game theory, and educational technologies. The recent publications (2013–2025) reflect a strong trend in theoretical computer science, particularly in algorithm design, data structures (e.g., K-d trees, binary search trees), and game-theoretic models. There is a notable emphasis on mathematical rigor, complexity analysis, and formal modeling of computational problems. Best student paper award Distinció Jaume Vicenç Vives a la qualitat docent universitària (modalitat individual) 18è Premi UPC a la Qualitat en la Docència Universitària Roura has contributed to teaching innovation through projects like Eines per a la Transformació de la Docència en Programació and the development of Jutge.org , an online programming judge platform. He has participated in numerous competitive R+D+i projects, often in collaboration with researchers such as Conrado Martinez, Xavier Molinero, and Maria Serna. His work has been supported by national and regional funding programs. While no direct mention of grants or student advising is made, his extensive publication and project history suggest significant research leadership.