جست‌وجوی استاد و پژوهشگر

Daniel Hlubinkaمشاهده پروفایل

دانشیار

• Statistics
• Theoretical Foundations
• Multivariate Functional Processes
• +۴ مورد دیگر

Daniel Hlubinka is an Associate Professor at the Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University. He has been an academic staff member since 1999 and was promoted to associate professor in 2007. His teaching includes courses like Statistics for Financial Mathematicians 2 (NMFM332) and Proseminar in Probability and Mathematical Statistics (NMSA262). He supervises bachelor's, diploma, and doctoral theses, with over 30 bachelor's, 20 diploma, and 5 doctoral theses supervised to date, including former students now working as associate professors. Education: Mathematical Physics (1989-1994) at Charles University; Erasmus stay at Limburgs Universitaire Center (1994-1995); Doctorate (1995-1999) under Professor Josef Štěpán. Research Interests: Statistics, theoretical foundations, multivariate functional processes, nonparametric asymptotics, data depth, optimal transport, and mathematics of chance. Academic Affiliations: Member of the Union of Czech Mathematicians and Physicists, Czech Mathematical Society, Czech Statistical Society, European Mathematical Society, Bernoulli Society, and Institute of Mathematical Statistics. Hlubinka's recent research focuses on functional data analysis, multivariate quantiles, and nonparametric testing. His work applies optimal transport theory, empirical characteristic functionals, and permutation tests to functional statistical problems. He contributes to methodological advancements in depth-based classification, time reversibility testing, and regression models.

Michal Pavelkaمشاهده پروفایل

دانشیار

• Geometric mechanics and thermodynamics (GENERIC)
• Modelling of electrochemical systems (fuel cells, batteries)
• Non-equilibrium continuum thermodynamics and hyperbolic systems
• +۱ مورد دیگر

Michal Pavelka is an Associate Professor at the Division of Mathematical Modeling, Mathematical Institute, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic. His career spans roles from Postdoc (part time) at the Institute of Chemical Technology to positions at École Polytechnique de Montréal and New Technologies Research Centre. He earned his Ph.D. in 2015 and M.Sc. in 2012 at Charles University under František Maršík. Michal Pavelka's research integrates Non-equilibrium Thermodynamics , Geometric Mechanics , and Machine Learning . His work bridges advanced mathematical frameworks like GENERIC and Extended Irreversible Thermodynamics with practical applications in electrochemical systems (fuel cells, batteries) and quantum fluids . Notably, he has contributed to Smoothed Particle Hydrodynamics and Hamiltonian mechanics in complex systems. His recent publications focus on Multiscale Thermodynamics , Superfluid Modeling , and Machine Learning in Physics . Scientific awards include the Best paper award, Entropy (2021) and Czech Grant Agency President's award (2020). He has secured significant grants, including a €363k Czech Grant Agency award (2023–2025) for geometric multiscale thermodynamics of complex fluids. Scientific Awards: Best paper award, Entropy (2021) Czech Grant Agency President's award (2020) High quality monographs of Charles University competition (1st-3rd place, 2020) Current Projects: He leads research on geometric multiscale thermodynamics and co-supervises projects on zinc-air batteries and solid oxide fuel cells. His lab develops the SmoothedParticles.jl Julia package for fluid dynamics simulations.

• Probability Theory
• Stochastic Processes
• Optimization Theory
• +۴ مورد دیگر

Petr Lachout is an Associate Professor at the Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University. His teaching and research focus on advanced mathematical topics including stochastic processes, optimization theory, and invariance principles in probability. He has led lectures on subjects such as Random Processes I , Optimization Theory , and Principles of Invariance , with syllabi covering convex sets, duality in linear programming, weak convergence of probability measures, and Skorokhod spaces. Contact: Petr.Lachout@mff.cuni.cz . Office located in Karlín building, Sokolovská 49/83, Prague 8.

Erin Claire Carsonمشاهده پروفایل

استادیار

• Numerical Linear Algebra
• Parallel Computing
• High-Performance Computing
• +۷ مورد دیگر

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.

• Adaptive Software Architectures
• Smart Cyber-Physical Systems (CPS)
• Internet of Things (IoT)
• +۵ مورد دیگر

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 .

• Mathematical programming
• Stochastic optimization
• Integer optimization
• +۳ مورد دیگر

Martin Branda is an Associate Professor at Charles University's Faculty of Mathematics and Physics, Department of Probability and Mathematical Statistics. He serves as Guarantor of the Master's Program in Financial and Actuarial Mathematics and maintains an active research and teaching profile. Workplace: Department of Probability and Mathematical Statistics Room: K 157 (2030a), 1st floor, Karlín, Sokolovská 49/83, Prague 8 Contact: Phone 95155 3404, Email Martin.Branda@mff.cuni.cz Homepage: https://www2.karlin.mff.cuni.cz/~branda/ Dr. Branda's research focuses on mathematical programming, stochastic optimization, and their applications in financial risk management and actuarial mathematics. His work bridges theoretical optimization methods with practical insurance applications. His recent publications demonstrate expertise in operational research applied to insurance markets, with particular emphasis on risk modeling and calculation methodologies. The research shows strong connections between mathematical optimization techniques and practical insurance applications. Dr. Branda actively supervises student research, with numerous bachelor's and master's theses completed under his guidance. His teaching portfolio includes core optimization courses and specialized finance/insurance applications. He has led multiple research projects funded by the Fund for the Support of Education in the Insurance Industry, particularly in non-life insurance rate calculation (2014/2015), generalized linear models in insurance (2012/2013), and modeling annuities in compulsory insurance (2010/2011).

• Financial Mathematics
• Actuarial Science
• Statistical Analysis
• +۶ مورد دیگر

Assoc. Prof. Jan Hurt, CSc. is an Associate Professor at the Faculty of Mathematics and Physics , Charles University , Prague, Czech Republic. He holds leadership as Head of the Department of Financial and Actuarial Mathematics and is affiliated with the Department of Probability and Mathematical Statistics . With over two decades of teaching experience, Prof. Hurt specializes in computational finance, actuarial modeling, and statistical inference using Mathematica . Department of Financial and Actuarial Mathematics (Head) Department of Probability and Mathematical Statistics Faculty of Mathematics and Physics, Charles University His research focuses on Financial Mathematics , Actuarial Science , and Computational Statistics . He has developed extensive Mathematica -based educational resources for courses like Financial Management, Risk Measures, and Multivariate Analysis. His work spans Portfolio Optimization , Epidemiological Modeling , and Statistical Inference . Prof. Hurt has supervised numerous student defenses and integrated computational tools into actuarial education. He actively contributes to academic conferences, including the Wolfram Technology Conference and Morgan Stanley Quantitative Finance Conference . As a Mathematica license administrator for MFF and CERGE, he supports institutional software infrastructure.

Zdenek Hanzalekمشاهده پروفایل

استاد

• Scheduling Algorithms
• Real-Time Systems
• Robotics
• +۳ مورد دیگر

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.

Miloš Kopaمشاهده پروفایل

دانشیار

• Stochastic Programming
• Financial Mathematics
• Portfolio Optimization
• +۵ مورد دیگر

Miloš Kopa is an Associate Professor and Chair of the Department of Probability and Mathematical Statistics at Charles University's Faculty of Mathematics and Physics, where he also directs the Financial Mathematics study programme. He serves as secretary of the EURO working group on stochastic optimization and actively participates in the Stochastic Programming Community, EURO working group on commodities and financial modelling, and EUROPT. Education: Ph.D. in Mathematics (Econometrics and Operations Research), Charles University, 2006 (Supervised by Prof. Jitka Dupačová) Research Focus: Dr. Kopa's work centers on stochastic programming theory with financial applications, emphasizing portfolio efficiency analysis, stochastic dominance criteria, and integration of data envelopment analysis with stochastic dominance. His research explores robustness in risk-constrained stochastic programs, asset-liability management, and decision-dependent randomness, bridging theoretical advances with practical financial modeling. Scientific Awards: No specific awards, prizes, or fellowships were documented in the source materials. Advising and Professional Service: He has supervised four Ph.D. students to completion (Václav Kozmík, Karel Macek, Barbora Petrová, Tomáš Rusý) and currently mentors three others (Karel Kozmík, Monika Kaľatová, Jana Junová). As vice-president (and former president 2020-2023) of the Czech Society for Operations Research, he also serves on the Czech National Accreditation Authority's Mathematics expert group and chaired the Czech Science Foundation's Finance and Operations Research committee (2019-2021). Research Environment: Based in room 155 at Karlín (Sokolovská 83, Prague), his work operates within the Department of Probability and Mathematical Statistics without mention of dedicated laboratories or specialized research teams beyond departmental structures.

Antonin Kuceraمشاهده پروفایل

استاد

• Stochastic Processes
• Probabilistic Systems
• Markov Decision Processes
• +۸ مورد دیگر

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.

Radek Valaمشاهده پروفایل

استادیار

• Web Information Systems
• Mobile Technology
• Cybersecurity
• +۳ مورد دیگر

Radek Vala serves as an Assistant Professor at the Institute of Informatics and Artificial Intelligence within the Faculty of Applied Informatics at Tomas Bata University in Zlín. His academic career spans over a decade at the institution, progressing from assistant to his current position since 2015. His educational background includes a Doctoral degree (2009-2015), Master's degree (2007-2009), and Bachelor's degree (2004-2007) in Engineering Informatics from Tomas Bata University, preceded by secondary education at Gymnasium in Bruntál. Vala's research focuses on web information systems development , mobile technology , and cybersecurity , with significant contributions to Industry 4.0 applications and modern development frameworks. His work bridges theoretical research with practical implementation through numerous industry collaborations. His publication portfolio demonstrates expertise across evolutionary algorithms , wavelet transforms , and security systems , showing consistent focus on optimization techniques and cybersecurity applications from 2011-2014. Gold Winner in Horizon Interactive Awards (School and University Websites category) 2nd place in Czech Golden Semicolon competition (Best Websites and Online Applications) As principal investigator for Ministry of Industry and Trade Innovation Voucher projects, Vala has led development of information systems for Industry 4.0 monitoring, order management, and CRM applications. He previously served as Head of Web Development for utb.cz (2017-2018), where he mentored over 50 students to completion of their Ing. degrees. Vala remains actively involved in the Penetration Testing Laboratory and Mobile Technology Testing Laboratory (PTLab) since 2015, contributing to practical security testing and mobile technology research.