Find Academic Supervisors

Daniel ŘíhaView profile

Assistant Professor

• Interactive Media
• Videogame Studies
• Serious Games
• +1 more

Daniel Říha serves as Assistant Professor at the Department of Theory of Art and Artworks within the Faculty of Humanities, Charles University Prague, holding this position continuously since 2005. His academic foundation includes a Ph.D. (2002) and M.A. (1998) from Charles University's Institute of Information Studies and Librarianship, with doctoral research focusing on collaborative hypermedia environments for scientific communication. His research program integrates Interactive Media, Videogame Studies, Serious Games, and Virtual Reality through interdisciplinary lenses spanning computer science, art theory, and education. Current investigations examine cutscene functionality in game information systems, VR applications in sexuality research, and multi-touch exhibition design, reflecting sustained engagement with digital knowledge representation since his early work on 3D virtual libraries. Analysis of his 15 most recent publications (2009-2016) reveals consistent thematic evolution toward applied interactive systems, with growing emphasis on therapeutic and educational implementations of virtual environments. His editorial leadership across 12 interdisciplinary volumes demonstrates significant influence in cyberculture and game studies discourse. 2003 Winner of Kunst am Bau International Art Competition for Virtual 3-D Library project As Principal Investigator for Czech Ministry of Education grants (2004-2005) and team member for Czech Grant Agency (2016-2018) and Ministry of Culture projects (2012-2015), he has secured substantial research funding. His academic leadership extends to founding Charles University's New Media Studies discipline and MED Comparative Media Research Group, plus international roles including Director of Publications at Inter-Disciplinary Press (2010-2012) and Cyber Hub Leader (2008-2016). Through projects like the Virtual Museum of Phototelegraphy and INVIPO distance education infrastructure, he has established collaborative networks connecting Czech academic institutions with German, Dutch, Swedish, and Polish universities, operationalizing his theoretical work in international educational contexts.

• Linked Data
• Open Data
• Semantic Web
• +6 more

Jakub Klímek is an Associate Professor at the Department of Software Engineering, Charles University. He is a leading researcher in Linked Data and Open Data technologies, with a focus on semantic interoperability, XML schema evolution, and data integration frameworks. Education: Habilitation Thesis: Improving data accessibility and interoperability using linked data Doctoral Thesis: XML Formats Evolution and Integration Master Thesis: XML Schema Evolution Bachelor Thesis: Linear Algebra His research spans semantic web technologies, dataset discovery, knowledge graph applications, and model-driven data engineering. Recent publications address technical and legal interoperability of European open data, context-enhanced similarity search, and data specification tools. Scientific Awards: BEST DEMO PAPER AWARD (ISWC 2024) BEST PAPER AWARD (iiWAS 2017) BEST STUDENT PAPER AWARD (APCCM 2013) BEST PAPER AWARD (EGOV 2013) Klímek contributes to practical applications through tools like UnifiedViews, LinkedPipes, and DataSpecer, collaborating with researchers including Petr Škoda, Martin Nečaský, and Jan Helmich. His work emphasizes real-world implementation of semantic data standards in public administration and enterprise systems.

• Adaptive Software Architectures
• Smart Cyber-Physical Systems (CPS)
• Internet of Things (IoT)
• +5 more

Tomáš Bureš is a Professor at the Department of Distributed and Dependable Systems , Faculty of Mathematics and Physics , Charles University . His work focuses on adaptive software architectures for smart cyber-physical systems (CPS) and IoT, leveraging machine learning (neural networks) for self-adaptation, edge-cloud systems, and model-driven development. Research Groups: Leader of the SmartArch research group. Projects: Involved in ExtremeXP , ESTABLISH , AFarCloud , FitOptiVis , Trust 4.0 , ASCENS , RELATE ITN , Q-ImPrESS . Publications span topics like performance regression testing, ML workflow optimization, confidentiality analysis under uncertainty, and edge-cloud continuum modeling. Key subfields include self-adaptive architectures, adaptation rules, component ensembles, and statistical methods in software engineering. His work bridges theoretical models (e.g., DEECo, SOFA) with practical tools (e.g., ExpEngine, Robin) for CPS and cloud applications. Co-Authors include P. Hnětynka, M. Abdullah, R. Heinrich, and others. Publications appear in venues like IEEE Transactions on Autonomic Computing , ACM/SPEC ICPE , and ECSA Workshops .

• Unified Processing of Multi-Model Data
• Influence Maximization in Social Networks
• Efficient Graph Data Processing
• +3 more

Martin Svoboda is a Lecturer at the Department of Software Engineering , Faculty of Mathematics and Physics, Charles University, Prague. His work focuses on multi-model data management, social network analysis, and XML/linked data processing. University: Charles University School: Faculty of Mathematics and Physics Department: Department of Software Engineering Role: Lecturer Education: Doctoral Thesis: Correction of Invalid Trees with Respect to Regular Tree Grammars (2015) Master's Thesis: Processing of Incorrect XML Data (2010) Bachelor's Thesis: Information System for Small User Group Collaboration (2007) Research Interests encompass: Unified multi-model data processing Influence maximization in social networks Graph data efficiency Big Data and NoSQL systems Querying/indexing linked data XML document correction Publications highlight trends in multi-model data unification, XML correction techniques, and social network analysis, with a strong emphasis on category theory and graph-based approaches. Scientific Recognition: Dean’s Award for Best Master Thesis (2010) Best Poster Award at Reasoning Web Summer School (2012) Projects include grants from the Czech Science Foundation (20-22276S, 2010–2012), Technology Agency of the Czech Republic (TH03010276, 2018–2020), and international collaborations like NoSQL-Net (Germany, 2014).

• Computer Science
• Parallel Computing
• Data Stream Processing
• +3 more

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

• Static Analysis of Programs
• Formal Verification
• Concurrency
• +12 more

Tomáš Vojnar is a Professor at the Department of Intelligent Systems, Faculty of Information Technology, Brno University of Technology (FIT BUT), Czech Republic. He has been a faculty member since 1999, promoted to Associate Professor in 2007 and full Professor in 2012. He leads the VeriFIT research group and has extensive experience in academic leadership, including candidacy for Dean of FIT BUT in 2023 and chairing major conferences such as TACAS'19 and SV-COMP 2018. Research Interests: Static and dynamic analysis of programs, especially those with pointers and dynamic data structures Formal verification of concurrent and infinite-state systems Automata-theoretic and logical methods in verification Binary code analysis and performance analysis His recent publications show a strong trend in developing and applying static analysis tools for verifying memory safety, concurrency, and semantic equivalence in C programs. He has made significant contributions to tools like Predator, 2LS, and DiffKemp, which are widely used in the verification community and have achieved top rankings in international competitions such as SV-COMP. His work bridges theoretical foundations in automata and logic with practical software verification applications. Scientific Awards: Best theory paper award of ETAPS'10 (EATCS) Best paper awards at CADE'19 and CIAA'08 Best tool paper awards at ISSTA'18 and RV'12 Multiple gold, silver, and bronze medals in SV-COMP (Predator, 2LS, Symbiotic) Bronze Humies award for automated design of approximate circuits Gödel prize from FLoC 2014 Olympic Games 1 gold and 3 silver medals at SL-COMP'14 Siemens prize for outstanding PhD thesis (2001) Advising and Grants: He has supervised numerous PhD and Master's students who have contributed to major verification tools and publications. He has been actively involved in national and international research projects, including the Czech Science Foundation panel P103 (2019–2023), and has secured funding for research in formal methods and software verification. His collaborations span institutions in France (LIAFA, CNRS), Austria (TU Vienna), and beyond. Labs and Teams: He leads the VeriFIT research group at FIT BUT, which focuses on formal methods and software verification. The group develops state-of-the-art tools such as Predator (shape analysis), 2LS (heap verification), DiffKemp (semantic diffing), and others used in both academia and industry. The team actively participates in international verification competitions and collaborates with researchers worldwide.

• Physics Education
• Quantum Physics
• Nuclear Physics
• +3 more

Zdeňka Koupilová is a Lecturer at the Department of Physics Didactics , Faculty of Mathematics and Physics , Charles University in Prague. She teaches courses in Quantum Mechanics, Thermodynamics, Theoretical Mechanics, and Physics Education. Nuclear and Subnuclear Physics Quantum Physics Education Science Communication Experiential Learning Educational Technology Her research focuses on innovative physics teaching methods, particularly quantum and nuclear physics education. She has developed interactive tools like the Orbitals project for atomic visualization and electronic problem collections . Her work includes collaborations with ČEZ, a.s. on educational brochures like Jaderné hrátky and Učíme jadernou fyziku . Publications highlight her contributions to physics education and detector simulations for the ATLAS experiment at CERN. Though no scientific awards are listed, her efforts in educational outreach and conference participation (e.g., GIREP 2006, Veletrh nápadů) underscore her impact.

Lubomír BulejView profile

Associate Professor

• Dynamic Program Analysis
• Software Performance Evaluation
• Software Performance Modeling
• +5 more

Lubomír Bulej serves as an Associate Professor at the Department of Distributed and Dependable Systems within the Faculty of Mathematics and Physics at Charles University, Prague. His office is located in room S 205 in the historic Lesser Town district, with contact details including email bulej@d3s.mff.cuni.cz and phone +420 951 554 189. He maintains an active research profile through platforms like Google Scholar, DBLP, and GitHub. His research centers on dynamic program analysis and software performance evaluation , with specific focus on analysis composition, program instrumentation, profiling accuracy, and observability in managed platforms. He develops methods for automatic performance evaluation during development, performance change detection, and testable documentation of performance assumptions. Additional interests span object-oriented programming, programming languages, operating systems, and computer architectures, reflected in his teaching of courses like Computer Architecture and Operating Systems. Analysis of his 2021-2025 publications reveals a consistent trajectory in performance-aware software development , with increasing emphasis on compiler technologies (particularly GraalVM), self-adaptive systems for cloud/edge environments, and cost-optimized performance testing methodologies. His work bridges theoretical program analysis with practical industrial applications, especially in avionics and distributed systems. Dr. Bulej actively contributes to major research projects including GraalVM compiler evaluation, FitOptiVis (avionics systems), ASHLEY (aircraft demonstrators), Ferdinand (model-driven design evaluation), Q-ImPrESS (service-oriented systems), and CoCoME (component modeling). He maintains critical software infrastructure such as the Renaissance Benchmark Suite, DiSL instrumentation framework, and Java Performance Measurement Framework.

• Multi-model data management
• Schema inference and evolution
• XML and semi-structured data
• +3 more

Irena Holubová, Ph.D. , is an Associate Professor at the Department of Software Engineering , Faculty of Mathematics and Physics , Charles University in Prague, Czech Republic. Her work focuses on multi-model data management, schema evolution, XML and graph data processing, and inferred social networks. She has led or co-led numerous national and international research projects, supervised over half a dozen Ph.D. students, and contributed extensively to the academic community. Education: Ph.D. in Computer Science (exact university and year not specified in text) Research Interests: Her research spans multi-model data management , including modeling, schema inference, and evolution. She explores inferred social networks through graph analytics and real-world data. Previously, her work included Linked Data , XML schema inference , XML benchmarking , and management of XML data using relational databases . Grants and Projects: Principal researcher, GAČR 23-07781S: Self-Adapting Management of Multi-Model Databases (2023–2025) Principal researcher, GAČR 20-22276S: Unified Management of Multi-Model Data (2020–2022) Co-researcher, TAČR TH03010276: System for advanced analytics of large connected data (2018–2020) Supervisor, GAUK 292323: Self-adaptive management of multi-model databases (2023–2025) Supervisor, GAUK 1416213: Evolution and adaptability of complex applications (2013–2015) Co-researcher, GAČR P202/10/0573: Handling XML Data in Heterogeneous and Dynamic Environments (2010–2012) Principal researcher, GAČR 201/09/P364: Management of XML data in (object-)relational databases (2009–2011) Member, GAČR 201/06/0756: Development of a Native Storage for XML Data (2006–2008) Member, SemWeb 1ET100300419: Intelligent Models for the Semantic Web (2005–2008) Conference Organization: Co-organizer: FiCloud ’17, MobiWis ’17, Innovate-Data ’17, NoSQL-Net ’15/’14, BenchmarX ’10/’09, X-Schemas ’09, MoViX ’09 Editorial and Reviewing Roles: PC member: MEDI, IDEAS, ACM SAC, ICIST, CoMoNoS, RCIS, VLDB Journal, Big Data Research Journal, and many more Reviewer: VLDB Journal, The Computer Journal, LNCS Transactions, special issues, and books Independent expert: EU FP7, Horizon 2020 Ph.D. Students Supervised: Jáchym Bártík (2022–) Pavel Koupil (2019–2022, finalist Antonín Svoboda Award) Marek Polák (2012–2017) Martin Svoboda (2010–2015, Dean's Award for Best Master Thesis) Jakub Stárka (2010–2013) Tomáš Knap (2008–2013, finalist IT Master Thesis 2009) Labs and Teams: She leads the Data Management Research Group at the Department of Software Engineering, focusing on multi-model databases, schema evolution, and XML technologies. The group has produced tools like MM-cat , Socneto , STOCK , BDgen , DaemonX , jInfer , and Analyzer .

Jan KofroňView profile

Associate Professor

• Program Verification
• Static Analysis
• Software Reliability
• +4 more

Jan Kofroň is an Associate Professor in the Department of Distributed and Dependable Systems at the Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic. His research focuses on program verification, static analysis, and software reliability. His educational background includes a Ph.D., as indicated by his title. He maintains an active research profile with numerous recent publications in top venues. Professor Kofroň's research interests span several key areas in software engineering and formal methods. He specializes in interpolation-based code model checking, static analysis of programs, system behavior models and verification, and programming language semantics. His work bridges theoretical foundations with practical applications in software development. His recent publications demonstrate strong focus on verification techniques for complex software systems, particularly in the areas of Horn clause solving, program comprehension using computational notebooks, and uncertainty-aware self-adaptive cyber-physical systems. His research shows consistent contributions to both theoretical foundations and practical applications of program analysis. Professor Kofroň actively leads and participates in multiple research projects including the current AIDE project (Advanced Analysis and Verification for Advanced Software) and past projects such as SNAPPY, ROBUST, Weverca, Q-ImPrESS, SOFA 2, and ASCENS. He teaches courses related to Java programming, Python programming, program semantics, and mobile devices programming. He maintains an open-door policy for student consultations, requesting students email him to arrange meetings rather than maintaining fixed office hours. His department maintains active GitHub presence, contributing to open-source projects related to software verification and analysis tools.

Martin KrulišView profile

Associate Professor

• High-performance computing
• GPU programming and CUDA optimization
• Parallel algorithms and data structures
• +4 more

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.

Viktor FuglíkView profile

Lecturer

• Educational Data Mining
• Machine Learning
• Learning Analytics
• +4 more

Viktor Fuglík serves as a Lecturer at the Department of Distributed and Dependable Systems within the Faculty of Mathematics and Physics at Charles University . His work bridges distributed systems education with innovative applications of machine learning in academic performance analysis. Teaching: Linux Administration (NSWI106), Operating Systems (NSWI200), Introduction to Linux (NSWI177) Research Focus: Educational data mining, student behavior modeling, and learning analytics Collaborations: Key contributor to EC-TEL and LAK conference publications with Jakub Kuzilek, Zdenek Zdráhal, and Jonas Vaclavek His scholarly output demonstrates a sustained focus on leveraging digital footprints from virtual learning environments to predict student outcomes, optimize exam strategies, and develop actionable dashboards for educational stakeholders. This work intersects with broader FAIR data initiatives and computational education research. While no formal scientific awards are documented in the provided materials, his contributions to student success prediction models and learning analytics dashboards represent significant practical advancements in educational technology. He actively supervises student projects while maintaining teaching responsibilities in systems administration and operating systems courses.

Milan StrakaView profile

Professor

• Machine Learning
• Artificial Neural Networks
• Deep Learning
• +12 more

Milan Straka is a professor at the Institute of Formal and Applied Linguistics (ÚFAL) within the Faculty of Mathematics and Physics at Charles University, Prague. His research focuses on machine learning, artificial neural networks, deep learning, and structured prediction with applications to natural language processing (NLP) tasks including POS tagging, dependency parsing, named entity recognition, and optical music recognition. University: Charles University School: Faculty of Mathematics and Physics Department: Institute of Formal and Applied Linguistics Straka has developed several NLP tools like UDPipe and NameTag, contributing to multilingual coreference resolution, Czech grammar error correction, and historical language processing pipelines. His recent work involves contextualized embeddings, semantic parsing, and large-scale dataset creation for Czech NLP tasks. He collaborates on European Language Grid initiatives and has participated in multiple shared tasks (CRAC, MRP, W-NUT). His publications span topics from algorithm design (functional data structures) to modern transformer-based language models (RoBERTa) with emphasis on Czech language resources.

Michal TöpferView profile

Tutor

• Machine Learning
• Component-based Systems
• Self-adaptive Systems
• +4 more

Michal Töpfer is a PhD student and academic tutor at the Department of Distributed and Reliable Systems within the Faculty of Mathematics and Physics at Charles University in Prague. Holding the RNDr. degree (Doctor of Natural Sciences), he actively contributes to both teaching and research at the university. His academic affiliations include: Department of Distributed and Reliable Systems (D3S) Faculty of Mathematics and Physics Charles University Dr. Töpfer's research centers on integrating machine learning with software architecture, particularly for self-adaptive and component-based systems. His work develops systematic approaches to incorporate ML capabilities into software architectures, enabling systems that can self-optimize and adapt to changing conditions. He has made significant contributions to the DEECo component model through his ML-DEECo extension and has developed visualization components for the IVIS framework used in IoT applications. His publication trajectory shows increasing focus on leveraging large language models for software engineering tasks and optimizing component-based architectures. The research spans theoretical foundations of component models to practical implementations addressing real-world challenges in distributed systems, with applications in smart farming and Industry 4.0. As an educator, he teaches practical sessions for undergraduate courses including Introduction to Algorithms and Programming 1 during winter semesters and Programming 2 during summer semesters. While he supervises student work, specific advisees are not documented in available sources. He actively contributes to the academic community through organizing the Mathematical Correspondence Seminar (PraSe), the Young Mathematicians Camp, and the Kasiopea programming competition. His technical expertise spans web development, software architecture, machine learning integration, and data visualization.

David ŠaurView profile

Assistant Professor

• Severe Convective Storms Prediction
• Flash Flood Risk Forecasting
• Meteorological Data Analysis
• +6 more

David Šaur is an Assistant Professor at the Department of Mathematics within Tomas Bata University's Faculty of Applied Informatics. His work bridges meteorology, applied informatics, and crisis management, focusing on severe convective storms and flash flood risk forecasting for regional governance. Developed FLAPRIS , a system for flash flood risk forecasting in the Zlín Region. Collaborated on X-band radar applications for real-time precipitation monitoring. Teaches mathematics-related courses for Software Engineering and Industrial Automation programs. Research Interests include: Predictive modeling of convective precipitation using radar and station data Integration of NWP (Numerical Weather Prediction) models with regional crisis management systems Development of algorithms for 24-hour quantitative precipitation forecasting Quantitative risk assessment for flash floods and storm phenomena His 15 most recent publications (2022-2016) focus on improving convective precipitation forecasting accuracy through algorithm validation, data mining techniques, and hybrid radar/station measurement thresholds. These works underpin practical crisis management tools for municipalities. Project Leadership : Principal Investigator for FLAPRIS (2022-2023) - Ministry of Interior, Czech Republic Principal Investigator for Improved Convective Precipitation Forecast (2019-2022) Researcher for CEBIA-Tech (2018-2020) - National Sustainability Program Advising Experience : Supervised 6 theses (2016-2022) at Tomas Bata University Mentored Master's works on flood risk software tools and hazardous material incident analysis Labs & Teams : CEBIA-Tech Research Center - Advanced ICT for crisis management Working Group for Digitization - Tomas Bata University Sustainability Working Group - Tomas Bata University