برای مسیر پژوهشیتان، استاد راهنما، استاد دانشگاه و پژوهشگر مناسب را پیدا کنید و با آنها ارتباط بگیرید.
نمایش ۱-۱۵ از ۲۱ استاد راهنما
اطلاعات پروفایلها از صفحات عمومی دانشگاهها گرفته شده و ممکن است بهروز نباشد.
دانشیار
Ondřej Bojar is an Associate Professor at the Institute of Formal and Applied Linguistics (UFAL), part of the Faculty of Mathematics and Physics at Charles University in Prague . He actively engages in research and teaching, with a focus on machine translation and computational linguistics. His work spans both theoretical and applied domains, involving collaborations with industry and academia.
دانشیار
Assoc. Prof. Ondřej Pejcha is an active researcher at the Institute of Theoretical Physics, Faculty of Mathematics and Physics, Charles University in Prague. His work focuses on connecting theoretical modeling, observational astronomy, and data science to understand time-domain phenomena in stellar systems, particularly binary stars and their evolution. Dr. Pejcha's research spans computational astrophysics, with emphasis on (radiation)(magneto)hydrodynamics simulations of binary star systems, common envelope evolution, and stellar mergers. His group develops advanced numerical methods to study transients such as stellar mergers and core-collapse supernovae, persistent variable sources including eclipsing binaries and pulsating stars, and stellar dynamics. They combine supercomputer simulations with semi-analytic models and machine learning techniques applied to astronomical data from surveys like ASAS-SN. The analysis of Dr. Pejcha's recent publications reveals a strong focus on computational approaches to binary star evolution, with increasing integration of machine learning methods in the latest works. His research addresses fundamental questions about common envelope evolution, mass transfer processes, and the connection between theoretical models and observational signatures in time-domain astronomy. ERC Consolidator grant for ROGALLO project (developing new simulation methods for binary stars) ERC Starting grant for Cat-In-hAT project (computational methods for binary star mergers) Czech Science Foundation grant for studying mass transfer in binaries Czech-American collaboration grant for ASAS-SN survey participation Primus award PRIMUS/SCI/17 from Charles University Dr. Pejcha actively mentors PhD students and postdocs, with recent advisees including Jakub Cehula and Milan Pešta. His group has secured substantial funding that supports internationally competitive salaries, dedicated computing resources including a specialized cluster with upcoming GPU enhancements, and travel funds. Alumni from his group have successfully obtained competitive postdoctoral positions and national/international fellowships. The group maintains strong international connections, regularly collaborating with institutions including Princeton University, Brown University, MPA Garching, and Warsaw University Observatory.
دانشیار
Ondřej Čepek is an Associate Professor at the Department of Theoretical Computer Science and Mathematical Logic, Faculty of Mathematics and Physics, Charles University in Prague. His academic career spans several decades with numerous publications demonstrating his expertise in theoretical computer science, particularly in Boolean logic, computational complexity, and operations research. Čepek's research primarily focuses on Boolean functions, Horn formulas, and computational complexity. His work explores structural properties of logical constructs, minimization techniques, and applications in knowledge representation. He has made significant contributions to understanding satisfiability testing complexity, CNF minimization, and Boolean function representations using interval structures. His research also extends to scheduling problems, particularly just-in-time scheduling with periodic time slots, where he has developed efficient algorithms for multislot scheduling on identical parallel machines and nonpreemptive flowshop scheduling with machine dominance. Analysis of his recent publications reveals a consistent research trajectory from theoretical foundations to practical applications. His work demonstrates expertise in tractable classes of Boolean formulas, knowledge compilation techniques, and the relationship between computational complexity and logical representations. The recurring themes include efficient representations for logical formulas, characterization of tractable problem classes, and development of optimization algorithms for discrete structures. His collaborations with researchers like Petr Kučera, Roman Barták, and Endre Boros have produced influential work in constraint programming and artificial intelligence. Distinguished Paper Award at CP2004 for 'Unary resource constraint with optional activities' While specific details about his advising activities are not provided in available sources, his extensive publication record spanning from 1989 to 2017 suggests substantial involvement in academic mentoring. His numerous collaborations both within Charles University and internationally indicate an active role in the academic community. His research has practical applications in knowledge-based systems, constraint satisfaction problems, and artificial intelligence. Čepek maintains an active research profile with publications continuing through 2017. His recent work has focused on knowledge compilation techniques, recognition of tractable DNFs, and the complexity of CNF minimization. He has also explored applications of Boolean techniques to DNA microarray data analysis, demonstrating the interdisciplinary nature of his research.
استادیار
Michal Outrata is an Assistant Professor in the Department of Numerical Mathematics at Charles University's Faculty of Mathematics and Physics in Prague, Czech Republic. He began his position in fall 2024 after completing a postdoctoral fellowship at Virginia Tech with Prof. Eric de Sturler and earning his PhD under Prof. Martin Gander at the University of Geneva, where his thesis was awarded the Henri Fehr Prize in 2023. His academic journey started with undergraduate studies in Prague under Prof. Zdeněk Strakoš (bachelor) and Prof. Miroslav Tůma (master). Dr. Outrata's research focuses on understanding why certain numerical methods work for specific problem classes, with emphasis on numerical linear algebra , Krylov subspace methods , and domain decomposition techniques . His work bridges theoretical analysis with practical algorithm development, particularly in preconditioning strategies for iterative solvers. Current projects include the Primus Research Programme (2025-2028) titled 'Divide, Conquer and Optimize: Domain Decomposition Methods in Scientific Computing' which explores hierarchical matrix formats and mixed precision computations for optimizing domain decomposition methods. His publication record demonstrates consistent contributions to top journals including SIAM Journal on Scientific Computing and Linear Algebra with Applications. His research shows progression from foundational work on GMRES convergence to sophisticated analyses of block Runge-Kutta preconditioners and optimized Schwarz methods with data-sparse transmission conditions. His recent work increasingly integrates hierarchical matrix formats and explores mixed precision computing approaches. Swiss Government Excellence Scholarship (3-year award) Henri Fehr Prize for best PhD thesis in mathematics (2023) Primus Research Programme grant (2025-2028) Dr. Outrata actively mentors students and postdocs, currently supervising Marouan Handa and Lenka Ptáčková (PostDocs) along with undergraduate researchers. He teaches courses including Numerical Analysis and Introduction to Numerical Mathematics at Charles University. His collaborative network spans international institutions including University of Geneva, Virginia Tech, and various European research centers. He is also involved in organizing major conferences including DD29 and GAMM95.
Vit Dolejsi is a Professor at the Department of Numerical Mathematics , Faculty of Mathematics and Physics , Charles University in Prague . He holds a PhD in Mathematical Modeling and Mechanics from Charles University and Universite Mediterranee. His research focuses on Numerical methods for partial differential equations with applications in Fluid dynamics , particularly using Discontinuous Galerkin methods and Anisotropic mesh adaptation . Phone: [+420] 95155 3373 Email: vit.dolejsi@matfyz.cuni.cz Office: Sokolovska 83, 186 75 Praha 8 - Karlin, Czech Republic Research Interests : Numerical methods for nonlinear PDEs High-order adaptive DG schemes Error estimation and adaptivity Compressible and incompressible flow simulations Applications in porous media and atmospheric modeling Algebraic and discretization error control Publications & Contributions : Authored monographs on Anisotropic hp-Mesh Adaptation (2022) and Discontinuous Galerkin Method (2015) Published 15+ journal papers (2015-2025) on DG methods, mesh adaptation, and error analysis Developed freely available CFD software implementations Contributed to hp-adaptive algorithms and space-time DG for nonlinear problems
استادیار
Erin Claire Carson is an Assistant Professor at the Department of Numerical Mathematics, Faculty of Mathematics and Physics, Charles University, Prague. A specialist in numerical linear algebra and high-performance computing, she leads the ERC Starting Grant project InEXASCALE focused on exascale algorithms. Her research explores mixed precision arithmetic, communication-avoiding Krylov subspace methods, and stability analysis in finite precision. Ph.D., University of California, Berkeley (2015) Courant Instructor, New York University (2015-2018) Postdoctoral Researcher and PRIMUS Fellow, Charles University (2018-2022) Dr. Carson's work bridges theoretical analysis with practical implementations for supercomputers. Her recent publications include advancements in low-synchronization orthogonalization, silent error detection, and multilevel sampling techniques. She received the 2025 Wilkinson Prize from SIAM for outstanding contributions to numerical analysis. Current trends in her research involve: Exploiting mixed precision arithmetic for algorithm acceleration Developing stable communication-avoiding Krylov methods Optimizing numerical stability in GPU-based solvers Understanding error propagation in multistage refinements Scientific honors: 2025 SIAM Wilkinson Prize in Numerical Analysis and Scientific Computing 2023 ERC Starting Grant recipient 2019-2022 PRIMUS Research Fellow She supervises PhD and Master’s students while teaching advanced courses in numerical linear algebra and high-performance computing. Her work has been featured in WIRED and Forbes Czech Republic for improving supercomputer algorithms.
Petr Jancar is a Professor at the Department of Informatics, Faculty of Science, Palacký University in Olomouc. He has previously held academic positions at VŠB-Technical University of Ostrava and the University of Ostrava. His research is centered in theoretical computer science, with deep contributions to automata theory, Petri nets, system verification, and computational complexity. Education RNDr, Theoretical Cybernetics and Mathematical Informatics, Faculty of Mathematics and Physics, Charles University, Prague (1982) CSc. (PhD equivalent), Dissertation: "Questions of Decidability of Dynamic Properties of Petri Nets", Charles University (1989) Appointed Associate Professor in Informatics, Faculty of Informatics, Masaryk University (1996) Appointed Professor in Informatics, VŠB-TU Ostrava (2008) His primary research interests include theoretical computer science , focusing on language and automata theory, computability and complexity, algorithm theory, and mathematical logic. A significant portion of his work addresses system verification , particularly using Petri nets and infinite-state systems. He investigates fundamental questions of bisimilarity, equivalence checking, decidability, and complexity in models like pushdown and one-counter automata. Jancar's recent publications (2020–2025) show a strong trend in advancing the theory of Petri nets, especially structural liveness, reachability, and home-space problems, often establishing high complexity bounds (e.g., Ackermann-complete). His work combines deep theoretical insight with formal rigor, frequently published in top venues like LICS, CONCUR, and LogMethCS. He has long-standing collaborations with researchers such as Jérôme Leroux, Zdeněk Sawa, and Antonín Kučera. Scientific Service and Recognition Member, Editorial Board, Information and Computation (since 2015) Member, Scientific Councils at Masaryk University, VŠB-TU Ostrava, Palacký University, and Brno University of Technology Chairman, GAČR Panel P202 Informatics (2015–2017) Member, Program Committees of major international conferences He has been a co-investigator and researcher on multiple GAČR projects, including those on algorithms for infinite-state systems, computational complexity of verification, and modeling of parallel systems. He has also participated in the Center for Applied Cybernetics. He has held research stays supported by grants in Germany, France, Sweden, and the UK. Laboratories and Research Groups His work is closely associated with formal methods and verification research groups at Palacký University and former affiliations. He has contributed to collaborative projects involving MPI verification and infinite-state system analysis.
دانشیار
Daniel Zeman is an Associate Professor at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics, Charles University in Prague. His work focuses on computational linguistics, particularly morphological analysis and dependency syntax of natural languages. He co-leads the Universal Dependencies project, a major international effort to create cross-linguistically consistent treebank annotation that has become a de-facto standard in the field, currently covering 148 languages with biannual releases. Dr. Zeman's research interests include: Computational models of morphology and syntax Multilingual approaches working across typologically different languages Cross-lingual techniques supporting disadvantaged languages with limited resources Harmonized data resources for multilingual processing Deep syntactic relations, semantic roles, and coreference His publication record shows a consistent focus on universal frameworks for linguistic annotation. The Universal Dependencies project, which he co-leads, represents a paradigm shift in how linguistic resources are created and shared across languages. His work bridges theoretical linguistics with practical language technology applications, with particular emphasis on making NLP accessible for resource-poor languages through cross-lingual transfer techniques. Scientific recognition includes: Fulbright-Masaryk Fellowship (2006-2007) at University of Maryland Dean's award for best monograph at the Faculty of Mathematics and Physics (2018) Senior area chair for LREC-COLING 2024 (CORE B conference) Area chair for ACL 2020 (CORE A* conference) Dr. Zeman has supervised 19 graduate students to completion (1 PhD, 13 Master's, 5 Bachelor's) as of March 2024. He leads several major research initiatives including Universal Dependencies (since 2014), CorefUD (since 2021), and is Vice-Chair of COST Action UniDive (2022-2026). His current projects span historical linguistics (HiČKoK, 2023-2026) to language understanding from syntax to discourse (LUSyD, 2020-2024). He has developed key linguistic resources including Interset (tagset conversion framework), HamleDT (harmonized treebanks), and Universal Dependencies. With over 5,468 citations and an h-index of 28, his work has significantly shaped modern computational linguistics methodology.
دانشیار
Assoc. Prof. Milan Předota, Ph.D., is a faculty member at the Department of Physics, Faculty of Science, University of South Bohemia in České Budějovice, Czech Republic. He holds a habilitation in Physics from Charles University in Prague and has been affiliated with the University of South Bohemia since 2003. Education MSc. in Theoretical Physics (1995), Charles University, Prague (with honors) Ph.D. in Physical Chemistry (1998), Charles University, Prague Habilitation (2013), Faculty of Mathematics and Physics, Charles University Professional Roles Post-doctoral Research Associate (University of Tennessee, USA, 1999-2002) Scientific Staff (Institute of Chemical Process Fundamentals, Czech Academy of Sciences, 1995-2013) Assistant Professor (Faculty of Health and Social Studies, 2003-2007; Faculty of Science, 2008-2013) Vice-Dean for Science (Faculty of Science, 2012-) Associate Professor (Faculty of Science, 2013-) Research Interests : Milan Předota specializes in statistical mechanics of molecular fluids , computer simulations of solid-liquid interfaces , and electronic continuum corrections . His work bridges molecular dynamics with experimental validation in areas like mineral-water interactions , biomolecular modeling , and nonlinear optics . He has pioneered pair approximation methods for polarizable fluids and dielectric property analysis at interfaces. Grant Leadership : He led projects such as "Theory and molecular simulation of electric double-layer at solid-liquid interface" (GAČR, 2003-2005), "Computational Study of Interactions of Organic Matter and Biomolecules with Mineral Surfaces" (GAČR, 2013-2016), and "Molecular description of phenomena in electrical double layer" (GAČR, 2017-2019). His collaborative projects include "Molecular simulations of processes at solid-liquid interfaces" (INTER-EXCELLENCE, 2017-2021). Scientific Impact : His publications span Journal of Physical Chemistry , Molecular Physics , and Langmuir , focusing on mineral-water interactions , electrochemistry , and nanofluidics . He supervised doctoral theses on solid/liquid interfaces and biomolecule-surface interactions , with three ongoing projects as of 2022.
پژوهشگر
Dr. Jakub Yaghob is a researcher at the Faculty of Mathematics and Physics , Charles University , specializing in computer science and parallel computing. He teaches advanced programming topics including Compiler Principles , Parallel Programming , and Cloud Computing . Research Interests : Parallel data stream processing, virtualization technologies, semantic web infrastructures, and performance optimization Teaching : Advanced C++ programming, virtualization administration, and computer systems architecture Technical Expertise : Design of parallelization frameworks, astrophysical data analysis, and hybrid CPU-GPU systems His publications focus on: Optimizing stream data processing across distributed architectures Developing domain-specific languages like Bobolang Performance evaluation in educational programming contexts Applications of parallel computing in astrophysics
Jiří Barnat serves as Dean of the Faculty of Informatics at Masaryk University in Brno and holds a professorship in the Department of Programming Theory. He concurrently directs the Center for Education, Research and Innovation in Information and Communication Technologies and maintains active membership in key university governance bodies including the Rector's Board, Scientific Council of the Faculty of Informatics, and Program Board for Informatics bachelor's degree programs. His research centers on formal verification methodologies and parallel system architectures , with significant contributions to automata-based validation techniques. Teaching records spanning 2000-2026 reveal deep expertise in distributed systems implementation, non-imperative programming paradigms, and hybrid system modeling. His course development consistently integrates theoretical foundations with practical laboratory applications in parallel computing environments. Professor Barnat leads the Laboratory of Parallel and Distributed Systems and collaborates with AVELAB research group, where he supervises project-based coursework in advanced parallel programming. His administrative leadership extends to campus infrastructure development through the Construction Council and academic policy formulation via the Extended Rector's Board.
پژوهشگر
Vojtěch Kovář is a researcher at Masaryk University with dual appointments at the Institute of the Czech Language (Faculty of Arts) and the Center for Natural Language Processing (Faculty of Informatics). He has been affiliated with the university since 2006, holding positions as researcher and lecturer while also working as a software analyst at Lexical Computing CZ since 2012. His research focuses on automatic syntactic analysis of natural languages , particularly Czech and related languages, evaluation of syntactic analysis quality , integration of syntactic tools into downstream applications , and corpus linguistics . His work bridges theoretical linguistics with practical language technology applications. Recent publications reveal a strong trend toward dictionary creation methodologies , lexicographic infrastructure development , and corpus-based language resource compilation . His research increasingly addresses rapid dictionary development for both European and Asian languages, as well as bilingual resource creation in response to emerging language needs. PACLIC 2010 best student paper award Member of eLex conference program committee (2017-present) Kovář supervises bachelor's and master's theses at both the Faculty of Arts and Faculty of Informatics, with recent topics including semi-automatic dictionary creation, web-based proofreading systems, and automatic punctuation correction. He teaches multiple courses including Fundamentals of Mathematics and Statistics for Humanities, Algorithmic Description of Syntax, and Programming Basics for Humanities. His research is supported by projects including LINDAT/CLARIAH-CZ (Digital Research Infrastructure for Language Technologies) and the Web-based spelling, grammar and typographical corrector for Czech language initiative.
Prof. Zdeněk Žabokrtský is a Professor at the Institute of Formal and Applied Linguistics (ÚFAL) within the Faculty of Mathematics and Physics at Charles University in Prague. He serves as the head of the PhD study program in Computational Linguistics and teaches several courses including Language Data Resources, Variability of Languages in Time and Space, Natural Language Processing, and Introduction to Language Technologies. His office is located in room S 409 on the 4th floor in the Lesser Town area of Prague. Prof. Žabokrtský's research spans multiple areas of Natural Language Processing and Computational Linguistics. His primary interests include building multilingual morphological resources, developing NLP applications that utilize parallel corpora, studying dependency syntax and valency frameworks, coreference resolution, theoretical studies on formal representations of natural languages, and applying Machine Learning techniques to linguistic problems. His work bridges theoretical linguistics with practical applications in language technology. Analysis of Prof. Žabokrtský's recent publications reveals a strong focus on morphological analysis, coreference resolution across multiple languages, and cross-lingual NLP. His research spans diverse languages including Czech, Turkish, Russian, and various Indic languages. He has made significant contributions to morphological resources, word-formation networks, and multilingual coreference systems, often creating and utilizing linguistic resources while developing novel computational approaches to linguistic phenomena. As an academic leader, Prof. Žabokrtský has supervised numerous PhD students and contributed to major research projects at the Institute of Formal and Applied Linguistics. His work has been supported by various grants that have enabled the development of important linguistic resources and NLP tools. He has been instrumental in establishing the PhD study program in Computational Linguistics at Charles University. Prof. Žabokrtský is a key member of the Institute of Formal and Applied Linguistics research teams, contributing to projects focused on developing language technologies, creating linguistic resources, and advancing theoretical understanding of natural language processing. His work is closely integrated with the Prague Dependency Treebank project and other major linguistic resources developed at Charles University.
دانشیار
Martin Kruliš is an associate professor in the Department of Distributed and Dependable Systems at the Faculty of Mathematics and Physics, Charles University , Prague, Czech Republic. His primary roles include research, teaching, advising, and leading projects that bridge high-performance computing, GPU programming, and self-adaptive systems. Education: While exact details of his own degrees are not provided, Dr. Kruliš’s extensive publication record and faculty position at Charles University indicate advanced training in computer science with specialization in parallel and distributed computing. Research Interests: High-Performance GPU Computing: Deep investigation into CUDA kernel optimization, memory bandwidth utilization, and workload dispatching for massively parallel accelerators. Self-Adaptive & Self-Optimizing Systems: Designing ensemble-based abstractions that integrate machine-learning estimators to enable runtime adaptation in component architectures. Parallel Algorithms & Data Structures: Development of cache-friendly, SIMD-aware, and GPU-accelerated algorithms for clustering, dimensionality reduction, and similarity search. Software Engineering for Parallelism: Creation of C++ libraries, DSLs (e.g., Bobolang), and educational tools (ReCodEx) that simplify parallel programming and automated evaluation. Publication Trends: Across 2011–2025, Kruliš’s articles reveal a clear trajectory from foundational GPU-accelerated indexing and multimedia retrieval toward sophisticated self-adaptive systems that leverage machine learning. Recent works (2023–2025) increasingly focus on integrating LLMs and neural networks into compiler and runtime optimization loops, reflecting a convergence of AI and systems research. Scientific Awards & Recognition: No specific awards or fellowships are mentioned in the provided text; however, sustained publication in top-tier venues (JPDC, IPDPS, Euro-Par, SEAMS) and active involvement in program committees and tool development indicate strong peer recognition. Teaching & Student Supervision: Teaches Programming in Parallel Environment (NPRG042) , Advanced Programming in Parallel Environment (NPRG058) , Computer Systems (NSWI170) , and Software Projects . Supervises numerous bachelor’s and master’s theses; exact student names are not listed in the text. Labs, Projects & Tools: ReCodEx: A widely used platform for semi-automated evaluation of programming assignments at Charles University. Simdex: A modular simulator of the ReCodEx backend that enables realistic experimentation with self-adaptive job dispatching and machine-learning controllers. Active contributor to open-source repositories on GitHub, focusing on GPU kernels, benchmarking frameworks, and educational tooling.
دانشیار
Assoc. Prof. Pavel Pecina, Ph.D., is a faculty member at the Institute of Formal and Applied Linguistics, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic. His primary academic role as an Associate Professor focuses on Natural Language Processing , Artificial Intelligence , and related areas. Research Interests: Information extraction, information retrieval, machine translation, multimodal data interpretation, optical music recognition Teaching: Courses since 2012-2022 including Natural Language Processing , Information Retrieval , and Statistical Methods in NLP Key Research Projects include GI-Insight (AI for healthcare), RES-Q+ (global stroke care registry), and MEMORISE (heritage digitization). His recent publications (2023-2025) demonstrate expertise across clinical NLP , historical document analysis , and music technology domains. Advising: Supervised 10+ graduate students in areas ranging from semantic search to optical music recognition. Collaborates with international institutions on multilingual translation and medical informatics challenges through initiatives like IWSLT and CLEF eHealth.
