Find Academic Supervisors

• Boolean Functions
• Horn Formulas
• Computational Complexity
• +7 more

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.

Martin KouteckýView profile

Associate Professor

• Parameterized Complexity
• Integer Programming
• Combinatorial Optimization
• +1 more

Martin Koutecký is an Associate Professor at the Institute of Informatics, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic. His research primarily focuses on parameterized complexity of integer programming, combinatorial optimization, and computational social choice. He completed his PhD under Petr Kolman at Charles University and conducted postdoctoral research at Technion (Haifa, Israel) under Asaf Levin and Shmuel Onn. Research Interests: Koutecký's work bridges theoretical computer science and optimization, with emphasis on: Designing efficient algorithms for integer programming under structural constraints Applying optimization techniques to computational social choice problems Developing parameterized approaches for combinatorial optimization Exploring geometric perspectives in election modeling and bribery problems Publication Focus: His recent articles (2020-2025) demonstrate consistent work in algorithm design for optimization problems, particularly in integer programming variants and computational social choice. Key themes include block-structured IP, parameterized complexity, election modeling, and convex optimization. Methodological innovations frequently involve polyhedral theory, approximation algorithms, and complexity analysis.

• Forest Management
• Climate Change Impacts
• Optimization
• +4 more

Prof. Róbert Marušák is a faculty member at the Czech University of Life Sciences Prague (CZU), serving as Dean of the Faculty of Forestry and Wood Technology and Chairman of its Scientific Council. He leads the Forest Risk Research Department and contributes to academic governance via the Rector's Board. His research focuses on forest management optimization , climate change impacts (e.g., bark beetle outbreaks, fire risks), and decision support systems using GIS and remote sensing. Key interests include sustainable harvest scheduling, disturbance resilience, and ecosystem service valuation. Recent publications emphasize climate-forest interactions, fire modeling, pest prediction, and geospatial tools. Trends show strong integration of computational methods (fuzzy-AHP, Bayesian networks) with ecological fieldwork, advancing adaptive forest management in Central Europe. He coordinates projects like the Excellent Research EVA 4.0 and oversees labs specializing in forest inventory technologies (e.g., terrestrial LiDAR) and risk assessment frameworks.

• Numerical Analysis
• Computational Mathematics
• Applied Mathematics
• +2 more

Jiří Felcman serves as an Associate Professor in the Department of Numerical Mathematics at the Faculty of Mathematics and Physics, Charles University. His office is located in room K 462 (4th floor, Karlín building, Sokolovská 49/83, Prague 8) with contact details including phone 95155 3392 and email felcman@karlin.mff.cuni.cz. He actively participates in faculty governance through advisory bodies of the faculty management. His research centers on advanced numerical methodologies, particularly in computational solutions for partial differential equations and finite element analysis. His work bridges theoretical mathematics with practical engineering applications, focusing on algorithmic efficiency and numerical stability in complex systems. Primary research domains include scientific computing, mathematical modeling, and computational fluid dynamics. Professor Felcman maintains significant teaching responsibilities with documented course schedules and exam administrations. His academic contributions extend to supervision of student theses and research projects, as evidenced by references to supervised work in institutional records. While specific grant details are unavailable, his departmental role suggests involvement in Czech and EU-funded computational mathematics initiatives.

• Numerical Analysis
• Applied Mathematics
• Scientific Computing
• +3 more

Martin Vohralík is a Professor at the French Institute for Research in Computer Science and Automation (INRIA) within the Department of Numerical Mathematics, focusing on advanced computational methodologies for mathematical problem-solving. His research spans core areas of numerical mathematics, with emphasis on algorithmic innovation and theoretical rigor. Key interests include: Numerical Analysis Partial Differential Equations Finite Element Methods Scientific Computing Computational Mathematics Applied Mathematics Professor Vohralík actively supervises graduate students and contributes to academic instruction, as evidenced by teaching schedules and supervised works documentation. His institutional role integrates research with educational responsibilities at INRIA.

• Artificial Intelligence
• Multi-Agent Path Finding
• Robotics
• +4 more

Jiří Švancara is a Lecturer at the Department of Theoretical Computer Science and Mathematical Logic (KTIML) within the Faculty of Mathematics and Physics at Charles University in Prague. His academic career focuses on Artificial Intelligence, particularly Multi-Agent Path Finding (MAPF), where he has established himself as a prominent researcher with numerous publications in top-tier conferences. His research interests span across Multi-Agent Path Finding , Robotics , Algorithm Design , and Constraint Satisfaction Problems . Švancara has made significant contributions to the field of MAPF, developing novel approaches for large-scale maps, temporal uncertainty handling, and efficient solving methods. His work bridges theoretical foundations with practical applications in robotics and transportation systems. Analysis of his recent publications reveals a strong focus on improving the scalability and robustness of MAPF algorithms. His research explores graph pruning techniques for large maps, handling temporal uncertainty in path execution, and comparing different objective functions for optimization. He has also investigated applications of MAPF in autonomous intersections and train routing systems, demonstrating the practical relevance of his theoretical work. Best Paper Award for 'Multi-agent Path Finding on Real Robots: First Experience with Ozobots' at IBERAMIA 2018 Švancara actively teaches multiple courses including Introduction to Artificial Intelligence, Propositional and Predicate Logic, and Algorithms and Data Structures. His teaching spans both theoretical foundations and practical implementation, with students engaging in programming assignments that reflect current AI challenges. His research collaborations are extensive, with frequent co-authorship with Roman Barták and other researchers in the field, indicating strong integration within the international AI research community. His laboratory work involves practical implementations of MAPF algorithms, including testing on real robots as evidenced by several publications describing experiments with Ozobots and other robotic platforms. This hands-on approach connects theoretical research with tangible robotic applications, providing valuable validation for his algorithmic contributions.

Zdenek HanzalekView profile

Professor

• Scheduling Algorithms
• Real-Time Systems
• Robotics
• +3 more

Zdenek Hanzalek is a professor at the Czech Technical University in Prague, affiliated with the Industrial Informatics Department within the Czech Institute of Informatics, Robotics and Cybernetics (CIIRC). His research focuses on scheduling algorithms, real-time systems, robotics, optimization, embedded systems, and automation. He leads projects such as ROBOPROX and CERTICAR, addressing advanced industrial production and autonomous vehicle certification. Notable contributions include work on periodic scheduling for time-sensitive networks, energy-efficient robotic systems, and trajectory planning for autonomous vehicles. Research Interests : - Development of efficient scheduling algorithms for real-time and embedded systems. - Optimization techniques for manufacturing systems and robotic applications. - Autonomous driving technologies, including trajectory planning and control systems. - Energy consumption reduction in production and robotic processes. - Time-triggered communication protocols and network scheduling. Recent Trends in Articles : Recent publications emphasize integration of machine learning with scheduling, optimization of charging infrastructure for electrified transportation, and robust scheduling under uncertainty. Key areas include reconfigurable manufacturing systems, mixed-criticality scheduling, and pandemic-resilient workforce planning. Awards & Grants : - Best Student Paper Award (ICORES 2023) for work on analog circuit placement. - Best Paper Award (ICORES 2022) for incremental scheduling algorithms. - Multiple Grade 1 Application Results in national evaluations. - Supported by EU, TAČR, and industry grants (e.g., Horizon 2020, ECSEL). Advising & Teams : Supervised over 20 PhD and master’s students in scheduling, robotics, and embedded systems. Collaborates with industry partners like Porsche Engineering, Skoda Auto, and Honeywell. Leads the CERTICAR project for autonomous vehicle certification and the HERCULES project on many-core systems for autonomous driving. Labs & Infrastructure : - Develops tools like TORSCHE scheduling toolbox and autonomous driving demonstrators (e.g., Porsche Panamera Turbo). - Engages in hardware-software co-design for real-time embedded systems.

• 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

• Numerical Analysis
• Scientific Computing
• Linear Algebra
• +3 more

Prof. Miroslav Tůma is a Professor in the Department of Numerical Mathematics at the Faculty of Mathematics and Physics, Charles University in Prague. He is part of the Workplace Scientific Council and can be reached at his office K 481 (5028) in the Karlín building (Sokolovská 49/83, Prague 8). His contact details include a phone extension 95155 3387 and an email address listed above. His professional profile includes teaching responsibilities, as evidenced by links to his teaching schedule and exam dates. He supervises academic work and maintains a homepage with further details at http://www.karlin.mff.cuni.cz/~mirektuma . His research interests are inferred to focus on numerical mathematics and computational methods given his departmental affiliation.

Pavel VeselýView profile

Assistant Professor

• Theoretical Computer Science
• Algorithms
• Data Structures
• +9 more

Pavel Veselý is an Assistant Professor at the Computer Science Institute of the Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic. His research focuses on the design and analysis of efficient algorithms and data structures, particularly in streaming, online, and approximation algorithms, with applications in bioinformatics and data privacy. His research interests include: Streaming algorithms for quantile estimation, geometric problems, and adversarial robustness Online algorithms, especially in scheduling and buffer management Approximation algorithms, including shortest superstrings and their use in genomic data (k-mer sets) Randomized algorithms and algorithmic data privacy His recent work has advanced the state of the art in streaming quantile estimation (KLL sketch), indexed k-mer representations using masked superstrings, and streaming facility location in high dimensions. His publications appear in top venues such as FOCS, STOC, PODS, and SODA. Notable scientific awards include: Best Paper Award at PODS 2021 2022 ACM SIGMOD Research Highlight Award Supervision of award-winning student theses, including Dean’s Award and Czech-Slovak competition wins He actively advises students, including PhD and master’s level researchers, and leads a research group focused on data sketches and streaming algorithms. He has taught courses such as Algorithmic Data Privacy, Randomized Algorithms, and Streaming Algorithms, and previously served as a postdoc at the University of Warwick under Graham Cormode.

• Theoretical Computer Science
• Mathematical Logic
• Computational Complexity
• +3 more

Assoc. Prof. Iveta Mrázová works at the Faculty of Mathematics and Physics (Charles University) in the Department of Theoretical Computer Science and Mathematical Logic . Her contact email is mrazova@mbox.ms.mff.cuni.cz , and her office is located in room S 304, 3rd floor, Lesser Town, Malostranské nám. 2/25, Prague 1. Her research focuses on: Theoretical foundations of computer science Mathematical logic applications Computational complexity Formal verification methods More information about her teaching schedule, supervised work, and publications (not listed here) can be accessed via her homepage: http://ktiml.mff.cuni.cz/~mrazova/

• Statistics
• Probability Theory
• Mathematical Statistics
• +4 more

Professor Jaromír Antoch is a distinguished faculty member at the Department of Probability and Mathematical Statistics within the Faculty of Mathematics and Physics at Charles University in Prague. His office is located in Karlín at Sokolovská 83, Prague 8, in room K 154 (2028) on the 1st floor. Institution: Charles University, Faculty of Mathematics and Physics Department: Department of Probability and Mathematical Statistics (KPMS) Office: K 154 (2028), 1st floor, Karlín, Sokolovská 49/83, Prague 8 Contact: Phone (+420) 221 913 275, Email: Jaromir.Antoch@mff.cuni.cz Professor Antoch's research spans multiple areas of statistics with particular emphasis on robust statistical methods, change point detection, regression analysis, and ROC curve analysis. His work demonstrates strong theoretical foundations with practical applications across various domains. He has made significant contributions to the development of robust statistical techniques that can handle outliers and non-standard data distributions. His publication record shows a consistent trajectory of scholarly work focused on methodological advancements in statistical theory. His research on change point detection in panel data represents cutting-edge work in time series analysis, while his investigations into genetic algorithms for variance calculation over interval data demonstrate innovative computational approaches to statistical problems. The recurring theme throughout his work is the development of robust statistical methods that maintain validity under non-ideal data conditions. Professor Antoch has been actively involved in the ROBUST conference series, which focuses on robust statistical methods, serving in organizational and presenting capacities across multiple years from at least 2004 through 2016. This demonstrates his standing within the international statistical community and his commitment to advancing the field of robust statistics. As an educator, Professor Antoch supervises academic work and maintains an active teaching schedule at Charles University. His involvement in conference organization and scholarly presentations indicates his commitment to mentoring students and colleagues in the field of statistics.

• Theoretical Computer Science
• Graph Theory
• Algorithms

Prof. Zdeněk Dvořák serves as a Professor at the Institute of Informatics within the Faculty of Mathematics and Physics at Charles University, Prague. His academic work is centered at the Institute for Theoretical Computer Science (IUUK), with an office located in room S 220 on the 2nd floor in the historic Lesser Town district (Malostranské nám. 2/25, Prague 1). Contact details include phone 95155 4390 and email Zdenek.Dvorak@mff.cuni.cz. Professor Dvořák's research focuses on Theoretical Computer Science, specializing in Graph Theory and Algorithms as evidenced by his affiliation with IUUK. His work explores structural graph properties, combinatorial optimization, and discrete mathematics, contributing to foundational advancements in algorithmic theory and computational complexity. He actively supervises student research projects and theses, as indicated by the "Supervised work" section on his profile. Teaching responsibilities include course instruction and examinations, with schedules and exam dates available through university channels. His academic homepage at https://iuuk.mff.cuni.cz/~rakdver/ provides comprehensive details on his scholarly activities.

• Online Algorithms
• Approximation Algorithms
• Scheduling
• +9 more

Jiří Sgall is currently a Professor and Vice-Dean for Computer Science at the Computer Science Institute of Charles University, Faculty of Mathematics and Physics. He previously held affiliations with the Department of Applied Mathematics (until 2011) and the Institute of Mathematics of the Czech Academy of Sciences (until 2016). Research Interests: Online and approximation algorithms, scheduling, computational complexity, combinatorics, communication complexity, propositional proof systems, circuit complexity, combinatorial games, cryptography, DNA computations, and alternative set theory. Scientific Contributions: His work spans competitive analysis of online scheduling, approximation algorithms, and complexity theory. Notable contributions include analyses of bin packing, packet scheduling, and multi-level aggregation algorithms. Editorial and Conference Roles: Associate Editor for multiple journals (Information and Computation, Operations Research Letters, Discrete Optimization) and chair/program committee member for conferences like ICALP, MFCS, and MAPSP. Grants and Leadership: Served as panel chair for the Czech Science Foundation (2009-2011) and council member of the EATCS (2001-2009, 2017 onwards). Contact Information: Email - sgall@iuuk.mff.cuni.cz; Office - Malostranské nám. 25, Prague 1, Czech Republic.

Antonin KuceraView profile

Professor

• Stochastic Processes
• Probabilistic Systems
• Markov Decision Processes
• +8 more

Antonin Kucera is a Professor at the Faculty of Informatics , Masaryk University, Czech Republic. His work focuses on stochastic processes, probabilistic systems, Markov decision processes, stochastic games, infinite-state systems, and applications of game theory in security and operational research. He has led multiple research projects funded by institutions like the US Army Research Office and the Czech Science Foundation. Research Interests : Stochastic processes, probabilistic verification, infinite-state systems, multi-objective optimization, game theory, and security applications. Projects : Leading studies on adversarial security patrolling, probabilistic systems analysis, and game-theoretic verification. Past projects include European Network for Game Theory (COST) and Institute for Theoretical Computer Science. Advising : Mentored 13 PhD/Master's students, including Tomáš Brázdil, Petr Novotný, and Jan Křetínský. Teaching : Courses on Petri Nets, Semantics of Programming Languages, and Mathematical Logic.