جستجوی استاد راهنمای دانشگاهی

Danfeng Zhang is a faculty member at Duke University whose research sits at the intersection of programming languages and security. Active across the premier PL conferences since 2015, Zhang has served on more than two-dozen program committees and currently co-chairs the POPL Student Research Competition. Education & Affiliation: Home page: users.cs.duke.edu/~dz132 Affiliation: Duke University, United States Research Interests: Zhang’s work spans programming-language design, static and dynamic analysis, formal verification, and security. A recurring theme is developing language-based techniques that guarantee strong security and privacy properties—ranging from side-channel resistance and constant-time execution to differential-privacy proofs—while preserving performance and usability. His recent projects combine type systems, program logics, and automated reasoning to build practical verification tools for concurrent, speculative, and approximate software. Publication Trends: Across nine representative papers (2015-2024) Zhang has advanced static detection of cache side channels, automated proofs of differential privacy, and relaxed concurrency models. The trajectory shows deepening integration of security concerns into language infrastructure, with tool-building (CtChecker, SpecSafe, LightDP) that bridge formal guarantees and real-world systems. Service & Leadership: 2024 POPL Student Research Competition Co-Chair 2025 POPL Program Committee member Repeated reviewer/PC member: PLDI, SPLASH/OOPSLA, ISSTA, ECOOP, APLAS, PriSC, PASS Zhang regularly mentors student researchers through SRC sessions and workshop panels, fostering diversity and early-career participation in the programming-languages community.

• Programming Languages
• Security
• Differential Privacy
• +۵ مورد دیگر

Angels Colomé is an Associate Professor in the Department of Cognition, Development and Educational Psychology at the University of Barcelona's Faculty of Psychology. She specializes in numerical cognition, math anxiety, and decision-making processes. Her work integrates experimental psychology, cognitive neuroscience, and educational research to understand how cognitive and emotional factors influence mathematical reasoning. Education: Psychology Degree, Universitat de Barcelona (1996) Doctorate in Psychology, Universitat de Barcelona (2000) Research Interests: Dr. Colomé investigates how anxiety impacts numerical processing and mathematical performance. Her studies explore spatial processing deficits in math-anxious individuals, probabilistic reasoning biases, and decision-making under uncertainty in medical contexts. She employs behavioral experiments, electrophysiological measures (ERP), and neuroimaging techniques to uncover cognitive mechanisms. Key Projects: 2014-2017: 'Visió i Control de l'Acció' (AGAUR Grant SGR79) - Investigating visual-motor control mechanisms 2016-2019: 'Ansiedad matemática:el papel de la habilidad de procesamiento espacial' (MINECO Grant PSI2015-69915-R) - Examining spatial skills' role in math anxiety 2017-2021: 'Visió i Control de l'Acció' (AGAUR Grant SGR48) - Ongoing visual action control research Teaching: Recently taught courses include 'Cognitive Numerical Processing', 'Mathematical Processing Disorders', and 'Problem-Solving and Reasoning' at the undergraduate level. Labs/Groups: Member of the VISCA research group (Visual Action Control) and the Aprenentatge i Pensament educational innovation team. Collaborates with researchers like Maria Isabel Núñez-Peña and Joan Lopez Moliner.

• Numerical Cognition
• Math Anxiety
• Probabilistic Reasoning
• +۳ مورد دیگر

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.

• Automatic Control
• Fault Detection and Diagnosis
• Water Distribution Networks
• +۶ مورد دیگر

Cecilio Angulo Bahón is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Industrial Engineering (ETSEIB) and the Department of Systems, Automatics and Industrial Informatics Engineering . He leads research in Artificial Intelligence and Robotics , with significant contributions to healthcare data analytics, digital twins, and human-robot collaboration. His research spans machine learning for medical data harmonization, generative adversarial networks in health informatics, and evolutionary algorithms for control systems. Recent publications focus on synthetic healthcare data generation, climate-resilient agriculture , and UMAP-based data analysis . His work bridges AI theory with practical applications in industrial and healthcare domains. Scientific awards include the Sant Jordi 2023 Digital Polytechnic Initiative Award . He has supervised doctoral candidates like Carlos Flores-Vázquez and N. Raya, with key collaborations at the IDEAI-UPC Intelligent Data Science and AI Research Group and the Institute of Robotics and Industrial Informatics (CSIC-UPC).

• Artificial Intelligence
• Robotics
• Data Science
• +۴ مورد دیگر

Elisabet Tubau Sala is a Full Professor at the Universitat de Barcelona , affiliated with the Department of Cognition, Development and Educational Psychology within the Faculty of Psychology . Her research focuses on probabilistic reasoning, learning processes, and decision-making mechanisms. She has led projects funded by institutions like Spain's Ministry of Science and the Catalan Agency for Management of University and Research Grants. Education: Psychology Degree (1984) - Universitat de Barcelona Doctorate (1987) - Universitat de Barcelona Recent Research Themes: Cognitive mechanisms behind Bayesian problem-solving challenges Role of visual aids in improving risk comprehension Educational interventions targeting causal reasoning biases Perceived severity effects in medical judgments Multi-object tracking models integrating speed/position data Cognitive control in math-anxious individuals Key Projects (2017-2024): 3D Space Updating from Optical Flow (PID2020-114713GB-I00) Vision and Action Control (VISCA) research group (2017-2021) Teaching Activities (Past 5 years): Cognitive Numeracy and Numerical Processing Disorders (Undergraduate) Perception, Action & Consciousness (Master's) Thinking & Problem Solving (Undergraduate) Her work bridges cognitive psychology with educational applications, emphasizing probabilistic reasoning's role in real-world decision contexts.

• Probabilistic Reasoning
• Cognitive Psychology
• Decision Making
• +۳ مورد دیگر

Pedro Cabalar is Full Professor at the Department of Computer Science of the University of Corunna, Galicia, Spain, and current coordinator of the inter-university Master in Artificial Intelligence (Universities of A Coruña, Santiago de Compostela and Vigo). He also serves as Area Editor (Theory Foundations) for Theory and Practice of Logic Programming and as Standard Editor for the Artificial Intelligence journal. Education: PhD in Computer Science, University of Corunna, 2001 Master in Computer Science, Politéchnic University of Madrid, 1993 Bachelor in Computer Science (3-year degree), University of Santiago de Compostela / University of Corunna, 1989 Research interests revolve around Knowledge Representation & Reasoning , especially Answer Set Programming , non-monotonic reasoning , temporal and modal logics , and causal reasoning . He investigates theoretical foundations (equilibrium logic, temporal extensions, deontic operators) and practical systems (telingo, eclingo, aspBEEF), with applications ranging from planning and diagnosis to explainable AI and healthcare decision support. His recent articles (2023-2025) exhibit a clear trend toward temporal and metric extensions of ASP , explainability , and hybrid reasoning systems , often combining logic programming with deontic or probabilistic features. Scientific awards & recognition: University of Corunna Dissertation Award, 2003 Best Paper Award at LPNMR 2019 Best Student Paper at ICLP 2020 Best Student Paper at JELIA 2019 Grants & projects: He currently leads or co-leads nationally funded Spanish projects (GEISER 2024-2028, ARLEKIN 2021-2024) and has coordinated EU COST actions (DigForASP) as well as earlier MINECO projects on temporal ASP and medical reasoning (TARDIS, MERLOT, FEAST, etc.). PhD supervision: He has successfully supervised three PhD theses (Martín Diéguez, Jorge Fandiño, Brais Muñiz) and continues to advise students within the Information Retrieval Laboratory (IRLab) and the Spanish node of Potassco Solutions.

• Knowledge Representation
• Answer Set Programming
• Non-monotonic Reasoning
• +۵ مورد دیگر

Roberto Javier López Sastre is an Associate Professor of Signal Theory and Communications at the University of Alcalá. He holds a Ph.D. from the same institution (2010), focusing on 'Visual vocabularies for category-level object recognition' under Dr. Saturnino Maldonado Bascón's supervision. His research spans machine learning, computer vision, robotics, and astrophysics. Key areas include Bayesian neural networks for stellar dating, semantic navigation in robotics, and AI-driven medical assistive technologies. Affiliation: Department of Signal Theory and Communications, University of Alcalá Research Group: GRAM (Multisensorial Recognition and Analysis Group) His work interfaces computational methods with real-world applications, such as assistive robotics for neurodevelopmental disorder patients and deep learning models for astrophysical parameter estimation. Recent contributions include semantic segmentation-driven navigation systems and Bayesian approaches to black hole solutions. Publications emphasize interdisciplinary applications of AI, including live video processing, continual learning frameworks, and physics-informed neural networks. Ongoing research explores the intersection of robotics, healthcare, and astrophysics through collaborative projects. López Sastre's GRAM group focuses on multisensory data analysis for recognition and navigation challenges. His technical expertise spans signal processing, probabilistic modeling, and embedded AI systems.

• Machine Learning
• Computer Vision
• Robotics
• +۵ مورد دیگر

Alejandro Aguirre is a Research Fellow at Aarhus University, Department of Computer Science. Previously, he was a PhD student at Universidad Politécnica de Madrid and Imdea Software Institute under Gilles Barthe's supervision. Current Role: Postdoctoral Research Fellow at Aarhus University PhD Supervisors: Gilles Barthe, Lars Birkedal Education: PhD (2021), MRes (2016), Double Degree in Mathematics and Computer Science (2015) His research focuses on Formal Verification , Probabilistic Programming , and Programming Language Semantics . He develops logical frameworks for verifying probabilistic and concurrent programs, including Separation Logic extensions, Guarded Type Theory, and Relational Reasoning. His work addresses challenges in probabilistic coupling, termination analysis, error bounds, and expected costs in higher-order programs. The most recent articles highlight his contributions to asynchronous probabilistic couplings , error credits for resourceful reasoning , and guarded refinement for almost-sure termination . These works span Computer Science , Formal Methods , and Concurrency , with subfields like Program Logics , Probabilistic Reasoning , and Logical Relations . Scientific Recognition: Distinguished Paper Award, ICFP '24 Distinguished Paper Award, POPL '21 He has served on the Program Committee for POPL 2024 and OOPSLA Review Committee (SPLASH 2024). His work intersects Probabilistic Programming and Formal Verification , with applications to security, concurrency, and program logics.

• Formal Verification
• Probabilistic Programming
• Programming Language Semantics

Ankush Das is a tenure-track assistant professor in the Computer Science Department at Boston University. His research focuses on programming languages with applications in cryptographic protocols, distributed systems, and probabilistic and machine learning models. Prior to joining Boston University, he worked as an applied scientist at Amazon in the Automated Reasoning Group until December 2023. Dr. Das received his PhD from Carnegie Mellon University in 2021, where he was advised by Prof. Jan Hoffmann and worked closely with Prof. Frank Pfenning. He completed his undergraduate studies at IIT Bombay, India in 2015. His research interests span a wide range of topics within programming languages, with specific focus on resource analysis, session types, distributed protocols, and language design for smart contracts on the blockchain. He is particularly interested in developing type systems that can ensure safety and efficiency properties in concurrent and distributed systems. His work has led to the development of domain-specific languages like Nomos for implementing smart contracts and Rast for resource-aware session types with arithmetic refinements. Dr. Das's publication record demonstrates a consistent focus on advancing type theory and its applications to practical systems. His work frequently appears in top-tier programming languages conferences such as POPL, PLDI, and ICFP. A notable trend in his recent work is the extension of session types to handle probabilistic computations and resource-aware programming, reflecting the growing importance of these areas in modern distributed systems. His scientific achievements have been recognized with several prestigious awards: Distinguished paper award at POPL 2024 for "Parametric Subtyping for Structural Parametric Polymorphism" Best system description paper award by a junior researcher at FSCD 2020 for "Rast: Resource-Aware Session Types with Arithmetic Refinements" Dr. Das is actively mentoring PhD and undergraduate students at Boston University. His current advisees include Anthony DeRossi, Toby Ueno, Brendan Coyne, Qiancheng Fu, June Wunder, Sam Buxbaum, and Sakshi Sharma. He is looking for motivated PhD students to join his research group, with opportunities to work on cutting-edge problems in programming languages and their applications to distributed systems and security. At Boston University, Dr. Das leads research efforts in programming language theory and its applications. His work bridges theoretical foundations with practical implementations, particularly in the areas of smart contracts and distributed protocols. He has collaborated extensively with researchers from Carnegie Mellon University, including his former advisors Jan Hoffmann and Frank Pfenning.

• Programming Languages
• Cryptographic Protocols
• Distributed Systems
• +۶ مورد دیگر

Diego Martín Papayannis is a full-time Associate Professor in the Department of Private Law at the Faculty of Law, University of Girona, where he also serves as Vice-Dean. He holds a PhD in Law from Pompeu Fabra University and has held visiting positions at Yale Law School and Bocconi University. He is an active researcher in legal philosophy, particularly in the philosophy of private law, tort law, and law and economics. His educational background includes: Law Degree, University of Buenos Aires (2001) Master in Law and Economics, University of Buenos Aires (2007) PhD in Law, Pompeu Fabra University (2010) Visiting Research Scholar, Yale Law School (2013) His research centers on the philosophical foundations of private law, causality, legal theory, and the economic analysis of law. Recently, he has been exploring how private law contributes to public goals such as wealth redistribution, gender equality, and social justice. His work bridges doctrinal analysis with normative and economic perspectives, making significant contributions to both Spanish and international legal scholarship. The articles and books authored and edited by Diego Martín reflect a consistent focus on the philosophical and ethical dimensions of tort law, causality, and legal justification. His publications span leading journals such as Legal Theory , Ratio Juris , and Journal of European Tort Law , and major publishers like Cambridge University Press and Springer. The recurring themes include corrective justice, moral responsibility, legal neutrality, and the social function of private law. He has supervised 7 PhD theses and 2 postdoctoral researchers and is currently advising 5 doctoral students. He has led curriculum development initiatives, including the creation of a 30-ECTS English-language program at the Faculty of Law to enhance internationalization. His research is supported by participation in funded projects and editorial roles in significant academic publications. Diego Martín is a key member of the Research Group in Legal Philosophy at the University of Girona. His leadership as Vice-Dean has contributed to institutional innovation, particularly in promoting multilingual legal education and attracting international students. He continues to shape legal scholarship through his editorial work, publications, and supervision of emerging legal theorists.

• Legal Philosophy
• Philosophy of Private Law
• Law and Economics
• +۷ مورد دیگر

María Amparo Alonso Betanzos is a Professor in the Department of Computer Science and Information Technology at the Faculty of Informatics, Universidade da Coruña (UDC), Spain. She is an active researcher and educator specializing in Artificial Intelligence and Machine Learning, with a focus on scalable and explainable approaches. She is a member of the Laboratory for Research and Development in Artificial Intelligence at UDC. Dr. Alonso Betanzos has extensive teaching experience across multiple degree programs including the Degree in Artificial Intelligence and the Degree in Computer Engineering. Her current teaching portfolio includes courses such as Deep Learning, Development of Intelligent Systems, Knowledge-based Systems, and Intelligent Systems, covering both mandatory and optional subjects across undergraduate and master's programs. Her primary research interests span Scalable Machine Learning, Explainable Machine Learning, Sustainable Artificial Intelligence, and Agent-Based Modeling. Her work demonstrates a strong commitment to developing AI systems that are not only powerful but also interpretable and environmentally conscious. She has made significant contributions to methods for feature selection, classification algorithms, and knowledge representation in complex domains. Analysis of her recent publications reveals a consistent focus on advancing explainable AI techniques, particularly in medical and social applications. Her work frequently appears in top-tier journals including IEEE Transactions on Neural Networks and Learning Systems, Information Fusion, and Expert Systems with Applications. A notable trend in her recent work is the application of AI to healthcare challenges, with several papers published in biomedical computing journals. Dr. Alonso Betanzos has been actively involved in research funding, serving as Principal Investigator on multiple projects funded by the European Regional Development Fund, the Ministry of Science, Innovation and Universities, and regional Galician agencies. Her research group has secured continuous funding since at least 2003, demonstrating sustained excellence in research. She has directed numerous final degree and master's theses since 2013, with topics ranging from virus spread simulation using intelligent models to anomaly detection in mixed categorical-continuous spaces. Her students' work often focuses on practical applications of machine learning in healthcare, social systems, and recommendation systems. Dr. Alonso Betanzos is a core member of the Laboratory for Research and Development in Artificial Intelligence at UDC, which focuses on advancing fundamental AI research while addressing real-world challenges. The lab maintains strong collaborations with both national and international research groups, particularly in the areas of explainable AI and sustainable computing.

• Machine Learning
• Artificial Intelligence
• Explainable AI
• +۵ مورد دیگر

Juan José Rué Perna is an Associate Professor in the Department of Mathematics at Universitat Politècnica de Catalunya (UPC), where he serves in the Faculty of Mathematics and Statistics. He also holds the position of Director of CFIS (Centro de Formación Interdisciplinaria Superior) and maintains strong affiliation with the Centre de Recerca Matemàtica (CRM). His academic career spans prestigious institutions across Europe, including Freie Universität Berlin, CSIC-ICMAT in Madrid, and École Polytechnique in Paris. Licenciado en Matemáticas (5-year degree) Engineering degree in Telecommunications (5-year program) PhD in Applied Mathematics (2009), supervised by Professor Marc Noy Rué's research focuses on combinatorics and discrete mathematics, with expertise in combinatorial structures, random graphs, and enumerative problems. His work bridges theoretical mathematics with applications in computer science, particularly in structural graph theory and probabilistic methods. He has made significant contributions to the understanding of planar graphs, random discrete structures, and additive combinatorics problems. His research combines analytic techniques with combinatorial reasoning to solve challenging enumeration and structural problems. His recent publications demonstrate a consistent trajectory in combinatorial mathematics, with emphasis on planar structures, random discrete objects, and additive problems. The works span theoretical investigations of graph structures, enumeration techniques, and probabilistic approaches to combinatorial problems. His research group GAPCOMB (Geometric, Algebraic and Probabilistic Combinatorics) at UPC continues to produce influential work in these areas. Premi Albert Dou de la SCM Rué has successfully supervised multiple PhD students to completion, including Clément Requilé, Christoph Spiegel, Vasiliki Velona, and Maximilian Wötzel. His research has been supported through numerous competitive grants, including ERC projects, ExploreMaps, and participation in the Berlin Mathematical School. He has organized significant academic events such as EUROCOMB 2021 and various workshops on combinatorics and discrete mathematics. As leader of the GAPCOMB research group at UPC, Rué fosters collaboration between geometric, algebraic, and probabilistic approaches to combinatorial problems. The group maintains strong connections with international research centers including ICMAT in Madrid and institutions across Europe, contributing to the vibrant combinatorial research community in Spain and internationally.

• Combinatorics
• Discrete Mathematics
• Random Graphs
• +۴ مورد دیگر

Paulo Félix Lamas is a Full Professor at the University of Santiago de Compostela (USC), specializing in Computer Science and Artificial Intelligence. He obtained his PhD in Physics from USC in 1999 and became an Associate Professor in 2002. As a foundational leader of CiTIUS (Research Centre in Intelligent Technologies), he served as Head (2010–2019) and Deputy Director (2019–2020). His research focuses on probabilistic learning , temporal abductive reasoning , and biomedical signal interpretation . Key applications include ECG analysis, glucose monitoring, and AI-driven healthcare solutions. His work bridges machine learning with clinical diagnostics, emphasizing interpretability and real-time systems. Recent publications (2015–2024) demonstrate interdisciplinary innovation, spanning: Healthcare AI : Personalized drug dosing, arrhythmia detection, and continuous glucose monitoring. Computational methods : Stochastic embeddings, kernel-based missing data handling, and adaptive clustering. Theoretical advances : Abductive reasoning frameworks for time-series interpretation. He leads major projects like: SOSFood (2024–2028): AI for sustainable food systems. XAI4SOC (2022–2025): Explainable AI for healthy aging. INSIDE (2022–2024): Predictive cardiac rehabilitation. At CiTIUS, he directs research on intelligent healthcare technologies, integrating sensor data with machine learning for chronic disease management.

• Machine Learning
• Biomedical Signal Processing
• Probabilistic Reasoning
• +۳ مورد دیگر

Roberto Iglesias Rodríguez is an Associate Professor at the University of Santiago de Compostela, Spain, with a focus on robotics and machine learning. He holds a B.S. and Ph.D. in Physics from the same institution (1996, 2003). His work addresses lifelong robot learning, federated learning, and deployment of intelligent systems in heterogeneous environments. Current affiliation: University of Santiago de Compostela Academic rank: Associate Professor Education: B.S. and Ph.D. in Physics (1996, 2003) His research spans robotics, machine learning, and sensor fusion , emphasizing adaptive algorithms for non-IID data, concept drift, and real-time environmental interaction. Projects include service robots learning from humans, distributed control architectures, and federated learning strategies. Recent publications analyze continual learning , scene recognition , and human-robot collaboration . Key themes: robust navigation, multi-sensor systems, and explainable AI.

• Machine Learning
• Robotics
• Continual Learning
• +۶ مورد دیگر

Luca Lorenzo Bonatti is an ICREA Research Professor at the Universitat Pompeu Fabra in the Department of Information and Communication Technologies, leading the Reasoning and Infant Cognition group. Previously, he held roles as Full Professor at the University of Nantes, Associate Professor at the University of Paris 8, and Research Associate at SISSA/ISAS. He has also been a Visiting Professor at institutions including the University of Budapest, the University of the Balearic Islands, and New York University. He earned his PhD in Philosophy of Mind from Rutgers University under Jerry Fodor and a Laurea in Philosophy from the University of Milan under Andrea Bonomi. His research focuses on reasoning mechanisms, language learning, infant cognition, and probabilistic intuition. Key areas include how infants predict future events, process causal information, and form logical concepts. His publications span developmental psychology, cognitive neuroscience, and philosophy of mind, emphasizing logical reasoning in infants and adults. Notable works explore entailment in language, non-verbal deduction, and the neural bases of deductive reasoning. His work bridges disciplines like linguistics, neuroscience, and education, with applied studies on improving mathematical skills in children. Bonatti’s research has been supported by grants and collaborations with international teams. He leads a lab investigating infant cognition and runs projects on logical primitives and probabilistic reasoning. No specific awards are listed, but his extensive academic roles and publications highlight his contributions to cognitive science.

• Reasoning
• Language Learning
• Infant Cognition
• +۳ مورد دیگر