جست‌وجوی استاد و پژوهشگر

• Algorithms
• Data Structures
• Combinatorics
• +۹ مورد دیگر

Conrado Martinez Parra is a Professor in the Department of Computer Science at the Faculty of Computer Science, Universitat Politècnica de Catalunya (UPC). He is a core member of the ALBCOM research group, which focuses on Algorithmics, Bioinformatics, Complexity, and Formal Methods. Affiliation : Department of Computer Science, Faculty of Computer Science (FIB), UPC Research Group : ALBCOM - Algorísmia, Bioinformàtica, Complexitat i Mètodes Formals Email : conrado@cs.upc.edu ORCID : 0000-0003-1302-9067 Researcher ID : G-4629-2015 His research spans theoretical computer science with a strong emphasis on the design and analysis of algorithms and data structures. His work includes average-case analysis of algorithms, combinatorial generation, probabilistic methods in algorithmics, and applications in information retrieval and data stream processing. He has extensively studied multidimensional data structures such as quadtrees, K-d trees, and skip lists, analyzing their performance under various query models including partial match and orthogonal range searches. His recent publications reveal a sustained focus on algorithmic efficiency, sampling techniques, and probabilistic modeling in data structures. Trends indicate a deep engagement with randomized algorithms, unbiased estimation, and cache-efficient selection methods, reflecting both theoretical rigor and practical applicability in modern computing environments. Scientific Contributions Extensive publication record spanning over three decades, from 1989 to 2024. Active in major algorithmic conferences such as ANALCO, AofA, and AAAI. Contributions to foundational algorithm analysis including Hoare’s FIND, Quickselect variants, and deletion in binary search trees. Collaborative research with prominent figures in theoretical computer science across Europe. Professor Martinez Parra has advised or collaborated with several doctoral students, including Gustavo Lau, whose thesis on partial match queries he supervised. He has participated in numerous competitive R&D projects funded by national and regional programs, focusing on large-scale information processing and graph-based computing models. His work is supported by long-standing grants from Spanish and Catalan research councils. He is affiliated with the ALBCOM research group, a leading team in algorithmic research at UPC, contributing to both theoretical advances and practical implementations in combinatorics and data structure optimization.

• Theoretical Computer Science
• Algorithms
• Computational Complexity
• +۶ مورد دیگر

Maria Jose Serna Iglesias is a Full Professor at the Faculty of Informatics of Barcelona (FIB), Universitat Politècnica de Catalunya (UPC)-BarcelonaTech, where she is affiliated with the Department of Computer Sciences. She is a leading member of the ALBCOM research group, focusing on Algorithmics, Bioinformatics, Complexity, and Formal Methods, and serves as the coordinator of the PhD program in Computing. Her academic leadership and research excellence are central to UPC's contributions in theoretical computer science. Licenciado en Ciencias Matemáticas Licenciado en Informática Doctorat en Informàtica (Doctorate in Computing) Her research interests lie at the intersection of theoretical computer science and game theory, with a strong focus on algorithmic game theory , social network analysis , and computational complexity . She investigates influence propagation models, cooperative games, weighted voting systems, and graph algorithms. Her work often involves the design and analysis of algorithms for discrete structures, with applications in network science and decision-making systems. The analysis of her recent publications reveals a consistent trend in studying strategic interactions in networks, particularly through influence models and cooperative game theory . Her work spans both theoretical foundations—such as complexity and dimensionality of games—and practical applications in social networks, education, and synthetic data validation. The keywords across her articles highlight a deep engagement with discrete mathematics, optimization, and algorithmic decision theory. She has received scientific recognition, including competitive awards and active participation in scientific committees of major international conferences such as the International Conference on Algorithmic Decision Theory and the Discrete Mathematics Days. Premiada (Awarded) Scientific committee member for multiple international conferences Maria Jose Serna has led and participated in numerous competitive R+D+i projects, often in collaboration with other prominent researchers in the ALBCOM group. She has advised multiple students and researchers, contributing to the training of the next generation of computer scientists. Her collaborations span institutions in Spain and internationally, particularly in the domains of algorithms and game theory. She is a core member of the ALBCOM research group (Algorísmia, Bioinformàtica, Complexitat i Mètodes Formals) at UPC, which is a leading force in theoretical computer science in Spain. The group fosters interdisciplinary research in algorithms, complexity, and formal methods, with strong ties to mathematical and computational sciences.

• Computational Complexity
• SAT Solvers
• MaxSAT Algorithms
• +۳ مورد دیگر

M. Luisa Bonet Carbonell is a researcher in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona School of Informatics (FIB). Her work focuses on computational complexity, SAT and MaxSAT solvers, proof systems, and algorithmic optimization. She has extensive collaborations within the LOGPROG and ALBCOM research groups, contributing to projects like TASSAT3 and MULOG-2. Her research spans theoretical computer science, with emphases on proof complexity, polynomial calculus, and the analysis of industrial SAT instances. Notable contributions include studies on Sherali-Adams and Nullstellensatz proof systems, as well as the fractal dimension of SAT formulas. Over 90 publications include articles in Artificial Intelligence , Journal of Computer and System Sciences , and conferences like SAT and IJCAI. Her work bridges theoretical foundations with practical applications, such as improving MaxSAT algorithms and analyzing community structures in problem instances.

Alexandra Silvaمشاهده پروفایل

استاد

• Programming Languages
• Formal Verification
• Kleene Algebra with Tests
• +۶ مورد دیگر

Alexandra Silva is a Professor of Computer Science in the Department of Computer Science at Cornell University's College of Engineering. She joined Cornell as faculty in 2021 after previously serving as a Royal Society Wolfson Fellow and Professor of Algebra, Semantics, and Computation at University College London. Her research spans programming languages, formal verification, and theoretical computer science, with particular focus on Kleene Algebra with Tests (KAT), probabilistic programming, and automata theory. She has held numerous leadership roles in major programming languages conferences including POPL, PLDI, and ICFP. Dr. Silva completed her PhD at Centrum Wiskunde & Informatica (CWI) in Amsterdam under the supervision of Jan Rutten and Marcello Bonsangue, with her thesis entitled "Kleene coalgebra" defended in December 2010. Prior to her PhD, she was an undergraduate student at University of Minho in Portugal, where she completed a 5-year Mathematics and Computer Science degree in May 2006. Her research focuses on the modular development of specification languages and algorithms for models of computations, often from the unifying perspective offered by coalgebra. She has made significant contributions to Kleene Algebra with Tests, probabilistic programming semantics, network verification, and automata learning. Her work bridges theoretical foundations with practical verification tools, particularly in the domain of Software-Defined Networking where her NetKAT framework has gained significant attention. Analysis of her recent publications reveals a strong trend toward unifying frameworks for program verification, particularly through her development of Outcome Logic which provides foundations for both correctness and incorrectness reasoning. Her work increasingly integrates probabilistic and concurrent aspects of programming languages, with applications to network verification and security. The NetKAT ecosystem remains a central theme, with extensions to infinite state verification, symbolic execution, and learning-based approaches. Distinguished paper award for Guarded Kleene algebra with tests: verification of uninterpreted programs in nearly linear time (POPL 2020) Dr. Silva advises a large research group with numerous PhD students, postdocs, and undergraduate researchers. Her group has produced significant work in programming languages theory, verification, and applications to networking. She has secured substantial research funding through various grants that support her work on formal methods for network verification and probabilistic programming. Her mentoring approach emphasizes both theoretical depth and practical impact, with many of her students moving to prestigious academic and industry positions. Her research group, spanning both Cornell University and University College London, focuses on developing theoretical foundations for programming languages with practical applications in network verification, probabilistic systems, and program analysis. The group maintains active collaborations with researchers at CWI, University of Oxford, and other leading institutions in programming languages and formal methods.