جست‌وجوی استاد و پژوهشگر

• Constraint Satisfaction Problems
• Computational Complexity
• Theoretical Computer Science
• +۴ مورد دیگر

Victor Dalmau is an Associate Professor at the Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF). He holds a Ph.D. and a degree in Computer Science from Universitat Politècnica de Catalunya. His career includes post-doctoral roles at institutions such as the University of Zaragoza and University of California, Santa Cruz, before joining UPF in 2000. He has held visiting positions at prestigious universities including Oxford, Cambridge, and Simon Fraser University. His research focuses on theoretical computer science, particularly constraint satisfaction problems (CSPs), exploring their complexity, combinatorial structures, and applications in areas like artificial intelligence and database theory. His work integrates concepts from universal algebra, logic, and computational learning theory. Notably, he investigates algorithmic techniques like Sherali-Adams hierarchies and Weisfeiler-Leman invariance for solving CSPs efficiently. Recent publications emphasize advancements in constraint satisfaction frameworks, homomorphism dualities, and the interplay between logic and database query optimization. His research bridges foundational theory with practical challenges in distributed computing and algorithm design. Victor Dalmau’s contributions span over 50 peer-reviewed articles, with a focus on computational complexity classifications, constraint programming, and the theoretical underpinnings of database systems. His work often addresses the boundaries between tractability and intractability in combinatorial problems.

• Theoretical Computer Science
• Constraint Satisfaction Problems
• Algebraic Methods
• +۳ مورد دیگر

Silvia Butti is a Senior Research Associate in the Department of Computer Science at the University of Oxford, where she also holds a Junior Research Fellowship at Lady Margaret Hall. She specializes in theoretical computer science, focusing on constraint satisfaction problems (CSPs), algebraic methods, approximation algorithms, and computational complexity. Her research bridges theoretical foundations with applications in distributed computing and combinatorial optimization. She earned her PhD from Universitat Pompeu Fabra (Barcelona, Spain) in 2022, supervised by Victor Dalmau, and holds an MSc in Mathematics and Foundations of Computer Science from the University of Oxford (2018) and a BSc in Mathematics from University College London (2017). Her academic journey is supported by prestigious fellowships, including the INPhINIT “la Caixa” and Marie Skłodowska-Curie Actions. Her research interests include the algebraic analysis of CSPs, inapproximability, and the interplay between hierarchies like Sherali-Adams and Weisfeiler-Leman invariants. She actively contributes to conferences such as LICS, MFCS, and CP, and has published extensively on topics ranging from promise problems to distributed algorithms. Dr. Butti teaches courses on computational complexity, combinatorial optimization, and probability and computing at the University of Oxford. She is committed to science communication, engaging with outreach initiatives like Maths Fest, the Royal Institution Masterclasses, and the UNIQ Summer School. Her work is funded by the UKRI-ERC grant NAASP, focusing on new approaches to approximability of satisfiable problems.

• Operations Research
• Mathematical Programming
• Fuzzy Optimization
• +۸ مورد دیگر

Maria Teresa León Mendoza is an Associate Professor in the Department of Statistics and Operations Research at the Faculty of Mathematics, Universitat de València. She is affiliated with the IARM (Image Analysis, Modelling and Retrieval) research group, reflecting her interdisciplinary work in data analysis and image processing. Doctorate: Universitat de València, 1992 Thesis: Un algoritmo primal para el problema continuo de programación semi-infinita lineal Supervisor: Dr. Enriqueta Vercher González Her research focuses on Operations Research , Mathematical Programming , and Fuzzy Optimization , with significant contributions to semi-infinite programming, data envelopment analysis (DEA), and portfolio selection under uncertainty. She has also applied mathematical methods to diverse areas such as image retrieval and musical tuning systems, demonstrating a broad interdisciplinary reach. Her publication record since 1992 shows a consistent focus on optimization under uncertainty, fuzzy methods for decision-making, and numerical algorithms. She frequently collaborates with researchers like Vicente Liern and Enriqueta Vercher, and her work is published in top journals such as European Journal of Operational Research and Fuzzy Sets and Systems . There is no mention of scientific awards in the provided sources. Maria Teresa León Mendoza has supervised at least one PhD student (Dr. Enriqueta Vercher González, who later became her supervisor, suggesting a long-standing academic collaboration), and she has been involved in multiple research projects, though specific grant details are not listed. Her work bridges theoretical optimization and practical applications in economics, finance, and engineering. She is actively involved in the IARM research group, which specializes in image analysis and retrieval, indicating ongoing research in machine learning and pattern recognition applications.

• Program Analysis
• Software Verification
• Debugging
• +۱۳ مورد دیگر

Manuel V. Hermenegildo is a Distinguished Professor at the IMDEA Software Institute and a Full Professor in the Department of Artificial Intelligence at the Technical University of Madrid (UPM). He is the founding Scientific Director of IMDEA Software and leads the CLIP Lab, a joint research unit between UPM and IMDEA Software focused on computational logic, programming languages, and parallelism. His career spans leadership in national research policy, academic positions in Spain and the U.S., and extensive international collaboration. PhD in Electrical and Computer Engineering, University of Texas at Austin (1986) M.S. in Electrical and Computer Engineering, University of Texas at Austin (1984) M.S. in Electrical Engineering, Technical University of Madrid (1981) His research centers on global program analysis, verification, debugging, and optimization for functional and non-functional properties such as time, memory, and energy. He has pioneered work in abstract interpretation, partial evaluation, constraint and logic programming, parallelizing compilers, and computational logic. His methodologies support the development of safe, efficient, and reliable software systems. The integration of static and dynamic analysis, resource-aware compilation, and assertion-based debugging are recurring themes in his work. His recent publications emphasize incremental and modular analysis, assertion checking, energy-aware computing, and verification via Horn clauses. Trends show a strong focus on making static analysis more practical, scalable, and integrated into real-world development workflows, particularly for logic and declarative languages. He frequently publishes in top venues such as TPLP, SCP, TOPLAS, and POPL. ACM Fellow Julio Rey Pastor Prize (2006) Aritmel Prize (2005) Elected member, Academia Europaea (2010) Test of Time Award, ICLP 2017 Best Paper Awards at ICSOC 2011 and ICLP 2005 Fulbright-Hays Scholarship Hermenegildo has supervised numerous PhD students and postdocs, many of whom are now leading researchers. He has been principal investigator in over 50 research projects funded by the EU, Spanish government, NSF, and industry partners. His leadership extends to national research policy, where he directed Spain’s National Research Directorate and launched the Ramón y Cajal fellowship program. He has served on tenure and evaluation committees for institutions worldwide and is active in shaping research agendas through roles in Informatics Europe and EIT Digital. He leads the CLIP Lab, which develops advanced program analysis tools and systems such as the Ciao programming environment, CiaoPP static analyzer, and LPdoc documentation generator. The lab fosters collaboration across academia and industry, focusing on next-generation program development tools, verification, and resource-aware computing.

María Beatriz Hernández Jiménezمشاهده پروفایل

استاد

• Operations Research
• Mathematical Programming
• Optimization Theory
• +۶ مورد دیگر

María Beatriz Hernández Jiménez is a Full Professor at Pablo de Olavide University, affiliated with the Department of Economics, Quantitative Methods and Economic History. She earned her PhD from the University of Seville in 2007, supervised by Dr. Marko Antonio Rojas-Medar and Dr. Rafaela Osuna Gómez, with a thesis titled 'Generalized Convexity in Non-Regular Optimization Problems'. Research Focus Her work centers on mathematical optimization under uncertainty , specializing in generalized convexity, interval-valued functions, fuzzy programming, and multiobjective decision-making. Key areas include: Development of optimality conditions for non-differentiable and interval-valued systems Duality theory in Riemannian manifolds and conic-constrained problems Efficiency analysis in multiobjective optimization Publication Trends Her 15 most recent articles (2013–2023) reveal a strong emphasis on generalizing differentiability concepts (e.g., Hukuhara derivatives for interval-valued functions) and extending optimality frameworks to fuzzy/interval contexts. Over 60% of these works address multiobjective or non-regular problems, often incorporating variational inequalities, conic constraints, or Riemannian geometry. Collaborations She frequently collaborates with researchers at the intersection of optimization and applied mathematics, including Rafaela Osuna-Gómez and Gabriel Ruiz-Garzón.

• Fuzzy Logic Programming
• Fuzzy Deductive Databases
• Automatic Program Transformation
• +۴ مورد دیگر

Pascual Julián-Iranzo is an Associate Professor in the Information Technologies and Systems Department at the Higher School of Computer Science, University of Castilla-La Mancha (UCLM), where he has served since April 2003. He is a founding member and current co-director of the DEC-tau research group focused on Declarative Programming and Automatic Program Transformation. His academic career includes over 27 years of university teaching experience across various positions, with significant contributions to curriculum development including the Degree Curriculum in Computer Engineering (2008/09 and 2009/10). Education Background: Doctor in Computer Science (1994-2000) from Universitat Politècnica de València, Department of Computer Systems and Computation His research centers on declarative programming languages with emphasis on fuzzy logic programming, functional-logic paradigm integration, and automatic program transformation. He pioneered work in proximity-based reasoning systems like Bousi-Prolog and FASILL, developing novel approaches for similarity-based unification, thresholded tabulation, and fuzzy deductive databases. His publications demonstrate consistent innovation in fuzzy logic semantics, particularly in handling truth degrees and semantic similarity measures for knowledge representation. Analysis of his 15 most recent publications reveals a strong trajectory in formalizing fuzzy logic programming frameworks, with increasing focus on practical implementations (2018-2023) after establishing theoretical foundations (2015-2017). Key thematic clusters include proximity-based unification algorithms (2018-2021), semantic frameworks for truth degree management (2016-2017), and real-world applications in natural language processing (2021) and security systems (2017). Research Recognition: Positive evaluation by CENAI for three consecutive research periods: [1997-2002], [2003-2008], and [2009-2014] Consistent publication record with 24 scientific journal articles (16 JCR-indexed) As an academic leader, Julián-Iranzo has supervised 2 doctoral theses and chaired the PROLE 2021 Conference Program Committee. His grant portfolio includes significant European funding, notably the MERINET project (2016-2019) supported by ERDF and MINECO. He has served on 12 conference program committees and reviewed for top journals including Journal of Theory and Practice of Logic Programming. His DEC-tau research group maintains active international collaborations, evidenced by coordination of the UCLM node in the ALFA Lernet Project (2005-2009) and partnership with Argentina's National University of San Luis (2009-2013).

Alessio Mansuttiمشاهده پروفایل

استاد پژوهشی

• Computer Science
• Automated Verification
• Arithmetic Theories
• +۳ مورد دیگر

Alessio Mansutti is an Assistant Research Professor at the IMDEA Software Institute. He received his PhD in Computer Science from École Normale Supérieure Paris-Saclay and previously held a Research Associate position at the University of Oxford's Automated Verification Group. Research focuses on algorithms for arithmetic theories and automated software verification. Key areas include computational logic, proof systems, finite model theory, and SMT solvers. Current projects investigate non-linear existential arithmetic theories, developing novel algorithms for systems featuring exponentiation and divisibility operations. Articles primarily explore complexity boundaries in arithmetic theories, including Presburger arithmetic extensions and integer programming with non-linear constraints. Recent work establishes complexity results for integer programming with GCD constraints and linear-exponential programming.

José Francisco Moralesمشاهده پروفایل

پژوهشگر

• Constraint logic programming
• Assertion languages
• Abstract interpretation
• +۵ مورد دیگر

Jose Francisco Morales is a Researcher at IMDEA Software Institute, a position he has held since November 2010 after completing his PhD at the Technical University of Madrid (UPM). Prior to this, he served as a teaching assistant at Universidad Complutense de Madrid starting in 2005. His academic background includes: PhD in Computer Science from the Technical University of Madrid (UPM), Spain His research focuses on efficient logic program execution through abstract interpretation for property inference, highly-optimizing native code translation , and abstract machine specification . Key areas include constraint logic programming, assertion languages, program analysis, compiler optimizations, and multiparadigm language implementation, with emphasis on developing formal abstractions for automated system construction. No scientific awards, student advisees, grants, or laboratory affiliations were documented in the source material.

• Optimization
• Soft Computing
• Logistics and Supply Chain
• +۳ مورد دیگر

Airam Expósito Márquez is a Researcher at the University of La Laguna, affiliated with the Department of Computer Science and Systems Engineering and the GA2 Grupo de Algoritmia Avanzada research group. They hold a PhD in Computer Science from the University of La Laguna (2020), supervised by Dr. Julio Antonio Brito Santana and Dr. José Andrés Moreno Pérez. Research focuses on optimization techniques, soft computing, logistics, and transportation systems. Key areas include production planning in industries, maritime logistics, waste collection route design, and smart mobility solutions. They have explored fuzzy logic, GRASP algorithms, and simulation models to address complex routing and scheduling problems. Recent work emphasizes real-world applications in seaport truck management, greenhouse gas reduction in freight distribution, and intelligent tourism routing. Their contributions span conference proceedings, peer-reviewed journals, and collaborative projects with industry partners. No scientific awards are explicitly mentioned, but their active publication record indicates sustained academic engagement. They are involved in teaching and curriculum development, as seen in their 2024 publication on secondary education technology programming. Labs/Teams: Active member of the GA2 Advanced Algorithmics Group, focusing on algorithm design and optimization for real-world challenges.

• (Concurrent) (Constraint) Logic Programming
• Program Analysis
• Program Transformation
• +۳ مورد دیگر

Francisco José Bueno Carrillo is an Associate Professor affiliated with the Department of Artificial Intelligence at the College of Computer Science, Technical University of Madrid. He is a member of the CLIP group and actively teaches courses in computational logic, formal logic, and logic programming.

Daniel Vázquez Vázquezمشاهده پروفایل

استادیار

• Inherent Safety Engineering
• Safety Index Engineering
• Multiobjective Optimization
• +۶ مورد دیگر

Daniel Vázquez Vázquez is an Assistant Professor in the Chemical Engineering and Materials Science Department at IQS School of Engineering (Universitat Ramon Llull). He is an active member of the Grup d'Enginyeria i Simulació de Processos Ambientals (GESPA), where he contributes to research in process engineering and environmental systems. His work spans multiple areas of chemical engineering with a particular focus on sustainable process design and optimization. Research Interests Daniel's research primarily centers on Inherent Safety Engineering and Safety Index development, with significant contributions to Multiobjective Optimization methodologies for chemical process design. His work bridges theoretical developments in optimization techniques with practical applications in environmental engineering and sustainable chemical processes. He has developed novel approaches like the OFISI (Optimizable Fuzzy Inherent Safety Index) that integrate fuzzy logic with process safety assessment. His research portfolio demonstrates a strong trajectory toward addressing complex sustainability challenges, particularly in the areas of carbon management, renewable energy integration, and circular economy principles. Recent work shows an increasing focus on planetary boundaries and the development of methodologies that ensure chemical processes operate within environmental limits while maintaining economic viability. Publication Trends Analysis of Daniel's recent publications reveals a clear evolution in research focus from traditional chemical process optimization toward more comprehensive sustainability frameworks. Early work concentrated on inherent safety metrics and distillation sequence design, while more recent publications integrate machine learning techniques (particularly Bayesian symbolic regression) with process engineering to develop hybrid modeling approaches. There's a marked emphasis on carbon management, with multiple publications addressing carbon dioxide removal technologies, methanol production from renewable sources, and the integration of carbon capture with energy systems. Collaborations and Projects M-AD-NESS Project (2024-2027): As Principal Investigator, Daniel is leading research on Dual Anaerobic Bioelectrochemical Digesters for in-situ biomethane production from wastewater sludge. GESPA Project (2022-2025): As a researcher, he contributed to this group focused on Environmental Process Engineering and Simulation, funded by the Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR). Daniel's research has gained significant attention, with his 2021 Nature Communications paper 'Delaying carbon dioxide removal in the European Union puts climate targets at risk' receiving 61 citations, policy references, and coverage in multiple news outlets. His work has been highlighted by 4 news outlets, blogged about, referenced in policy sources, and shared widely on social media platforms. Laboratory and Research Group Daniel is an active member of the Grup d'Enginyeria i Simulació de Processos Ambientals (GESPA), a research group dedicated to environmental process engineering and simulation. This group brings together multiple researchers from IQS to address challenges in sustainable chemical processes, waste management, and environmental protection through advanced modeling and optimization techniques.

Maria Garcia de la Bandaمشاهده پروفایل

استاد

• Constraint Programming
• Combinatorial Optimization
• Program Analysis
• +۵ مورد دیگر

Maria Garcia de la Banda is a distinguished Professor at Monash University's Faculty of Information Technology, where she serves in the Department of Data Science and Artificial Intelligence (DSAI). With over 25 years of academic experience, she has held significant leadership roles including Deputy Dean (Research) until July 2022, overall Deputy Dean of the Faculty (2013-2016), and Head of the Caulfield School of Information Technology (2009-2011). She is currently a member of the ARC College of Experts and Co-Chair of the Monash-Woodside FutureLab. Her educational background includes a Doctor of Philosophy in Computer Science from the Universidad Politecnica de Madrid (awarded July 7, 1994) and an Ingeniero Informatico degree from the same institution (awarded March 1, 1992). Her PhD received the university's Best PhD Award. Garcia de la Banda's research spans multiple disciplines with a strong focus on constraint programming, combinatorial optimization, program analysis, and bioinformatics. She leads the Optimization research group within DSAI and has made significant contributions to declarative programming languages, parallelism, and automatic parallelization. Her interdisciplinary work bridges computer science with biological applications, particularly in protein structure analysis and computational drug design. Her publication record shows consistent contributions across constraint programming, optimization, and bioinformatics. Recent work demonstrates increasing interdisciplinary collaboration, with a notable expansion into bioinformatics applications alongside her core constraint programming research. She has maintained a strong presence at major conferences like CP (International Conference on Principles and Practice of Constraint Programming) while also building impactful industry collaborations. Her scientific recognition includes: Logan Fellowship (1997) - the first and only prestigious award of its kind in the Faculty of IT International Constraint Modelling Challenge winner (2005, with Peter Stuckey) Universidad Politecnica de Madrid's Best PhD Award (1994) Induction into the Monash Honour Roll (2021) Vice-Chancellor's Diversity and Inclusion Award (2020) As a research leader, Garcia de la Banda has secured over $20M in industry funding and $14M in nationally competitive funding, including $8M as Chief Investigator in 11 ARC grants (5 as lead). She has served as Area Editor of the Journal of Theory and Practice of Logic Programming since 2010 and on the Editorial Board of the Constraints journal since 2019. Her leadership extends to professional organizations, having served on the Executive Committees of both the Association of Logic Programming (2005-2008) and the Association of Constraint Programming (2017-2020), where she was President (2019-2020). She leads the Optimization research group within DSAI and collaborates extensively across Monash University and with industry partners. Her current major projects include HARNESS (Hierarchical Abstractions and Reasoning for Neuro-Symbolic Systems), the ARC Training Centre in Optimisation Technologies, and the Building 4.0 CRC project focused on better buildings through technology. These initiatives demonstrate her commitment to translating theoretical research into practical applications with real-world impact.

• Constraint Logic Programming
• Answer Set Programming (ASP)
• Stream Data Analysis
• +۳ مورد دیگر

Joaquín Arias is an Associate Professor at the Universidad Rey Juan Carlos (URJC) in Madrid, Spain, since 2025. He previously served as an Assistant Professor at URJC (2020–2025) and as a Pre-Doctoral Researcher at the IMDEA Software Institute (2013–2020). He holds a Ph.D. in Computer Science (2020), a Master of Science in Computer Science (2015), a Bachelor of Science in Computer Science (2014), and a Master of Architecture (2002), all from the Universidad Politécnica de Madrid (UPM). His research focuses on constraint logic programming, answer set programming (ASP), and their applications in stream data analysis, spatial reasoning, and legal reasoning systems. His main research interests include (Constraint) Logic Programming, TCLP, s(CASP), and value-aware systems. He has developed frameworks like Modular TCLP and ATCLP for constraint integration and aggregate computation. Notable projects include applying s(CASP) to legal reasoning (s(LAW)), BIM modeling, and automated conversational agents using LLMs and ASP. His work emphasizes explainable AI and ethical alignment in automated decision-making. Key contributions include the Automated Legal Reasoning with Discretion framework (2024), a socialbot leveraging LLMs and ASP (2024), and a legal reasoning system for administrative processes (2024). He has contributed to proceedings of the ICLP workshops and edited volumes for conferences like AAAI and CAEPIA. His academic awards include the Best Paper Prize at CAEPIA 2021. Collaborations include the University of Texas at Dallas (2017), Aalto University (2019), and IMDEA Software Institute. His teaching includes promoting logic programming in computer science curricula, as highlighted in his 2023 SIIE conference paper.

Nata Stulovaمشاهده پروفایل

پژوهشگر

• Software Engineering
• Formal Methods
• Natural Language Processing
• +۳ مورد دیگر

Nata Stulova is a Researcher currently working as a staff research scientist at MacPaw's Technological R&D Center, focusing on software engineering research involving formal and informal program specifications. Formerly, she held academic roles including senior postdoctoral researcher at the University of Bern (SCG), researcher at EPFL's LARA Lab, and PhD work at the Technical University of Madrid (UPM). Her research spans software documentation consistency, NLP applications, runtime verification, and low-code tools. She has led multiple projects addressing code comment quality, empirical studies on documentation practices, and tool development for requirements engineering. Despite transitioning to industry in 2022, she maintains active collaboration with academia, publishing in top conferences like ICSE and IEEE Transactions. She holds a PhD in Computer Science from UPM and has authored numerous peer-reviewed articles and conference papers. Her work emphasizes bridging academic research with industry applications, particularly in software analysis and developer productivity. Education: PhD in Computer Science, Technical University of Madrid (2018) MSc in Artificial Intelligence, Technical University of Madrid (2013) BSc in Applied System Analysis, NTUU "KPI" (2012) Research Interests: Her work focuses on improving software quality through automated documentation tools, runtime verification techniques, and low-code solutions for requirements engineering. She explores NLP methods for detecting inconsistent or outdated comments and optimizing static analysis efficiency. Recent projects include SwiftEval (LLM-generated code evaluation) and RepliComment (cloned comment detection). She also emphasizes practical applications of formal methods in dynamic languages like Prolog and Python. Grants & Funding: ASA: Agile Software Assistance TRACES: Resource-Aware Software Tools N-GREENS: Energy-Efficient Software Labs/Teams: Core member of the Ciao system development team at IMDEA Software Institute, contributor to the Software Composition Group (SCG) at UniBe, and collaborator with MacPaw's TR&D team on industry-focused R&D.

Miki Hermannمشاهده پروفایل

پژوهشگر

• Computational Complexity
• Constraint Satisfaction Problems
• Satisfiability
• +۴ مورد دیگر

Miki Hermann is a CNRS Researcher at the Laboratory of Computer Science (LIX) at École Polytechnique, France. He is affiliated with the Algorithms and Complexity research group and maintains an active research program in theoretical computer science and computational logic. His research interests span computational complexity, constraint satisfaction problems, satisfiability, and logic in computer science. Hermann's work focuses on the theoretical foundations of computational problems, particularly examining complexity classifications, counting problems, and algorithmic solutions for logical and combinatorial structures. His research bridges theoretical computer science with practical applications in artificial intelligence and data analysis. The analysis of his recent publications reveals a consistent focus on computational complexity across various logical frameworks. His work demonstrates expertise in classifying the complexity of constraint satisfaction problems, propositional logic systems, and graph-theoretic problems. Notable research directions include minimal inference problems, counting complexity, and applications of satisfiability to big data transformation through his MCP project. Hermann is part of the Algorithms and Complexity research group at LIX (CNRS, UMR 7161), where he contributes to theoretical computer science research. He has developed significant software projects including MCP (Multi-Classification Project) for transforming datasets into propositional formulas and GYT (Generalized Young Tableaux) for solving variadic polynomial equations over non-negative integers.