جستجوی استاد راهنمای دانشگاهی

Martin Krulišمشاهده پروفایل

دانشیار

• High-performance computing
• GPU programming and CUDA optimization
• Parallel algorithms and data structures
• +۴ مورد دیگر

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.

• Programming Language Theory
• Software Engineering
• Context-Aware Programming
• +۲ مورد دیگر

Tomáš Petříček serves as an Assistant Professor in the Department of Distributed and Dependable Systems at the Faculty of Mathematics and Physics, Charles University. His academic profile bridges theoretical programming language research, practical open-source software development, and interdisciplinary investigations into programming's historical and philosophical dimensions. Holding a PhD from the University of Cambridge focused on context-aware programming theory, his professional trajectory includes significant contributions to the F# programming language at Microsoft Research, data exploration tools at The Alan Turing Institute, and lecturing at the University of Kent. His research program systematically examines programming fundamentals through three interconnected lenses: theoretical formalisms, applied tooling, and meta-analyses of programming culture. While no specific scientific awards are documented in source materials, his career demonstrates recognition through appointments at elite institutions. Departmental listings confirm thesis supervision activities ( Vedené práce ), though individual students remain unnamed. Current research occurs within Charles University's Department of Distributed and Dependable Systems, fostering collaborations in distributed systems and programming language innovation.

Viktor Fuglíkمشاهده پروفایل

مدرس

• Educational Data Mining
• Machine Learning
• Learning Analytics
• +۴ مورد دیگر

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.

• interpretation of deep neural networks
• machine learning
• dependency syntax
• +۳ مورد دیگر

David Mareček is a researcher at the Institute of Formal and Applied Linguistics (ÚFAL) within the Faculty of Mathematics and Physics at Charles University. His work focuses on neural network interpretation, machine learning, dependency syntax analysis, and machine translation, with a particular emphasis on unsupervised and semi-supervised parsing techniques. Current projects: GenderBias (2023–present), EduPo (2024–present) Long-term contributions in dependency treebanks (HamleDT, 2012–2016) and neural machine translation frameworks (Treex, TectoMT) His research explores linguistic structure in neural architectures, including BERT and Transformer models, through methods like structural probing and attention analysis. Recent publications examine gender bias mitigation, automated poetry analysis, and theatre script generation. Key collaborations include Rudolf Rosa, Tomáš Musil, and Tomasz Limisiewicz. He supervises students in projects spanning multilingual representations, language model probing, and bias detection in AI systems. Technical leadership in developing tools like THEaiTRobot and DEPFIX demonstrates his commitment to applied computational linguistics and robust NLP systems.

Milan Strakaمشاهده پروفایل

استاد

• Machine Learning
• Artificial Neural Networks
• Deep Learning
• +۱۲ مورد دیگر

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 Töpferمشاهده پروفایل

مربی

• Machine Learning
• Component-based Systems
• Self-adaptive Systems
• +۴ مورد دیگر

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.

Alexander Wilkieمشاهده پروفایل

استاد

• Computer Graphics
• Predictive Rendering
• Spectral Rendering
• +۷ مورد دیگر

Alexander Wilkie is a Full Professor at Charles University, Faculty of Mathematics and Physics (MFF), Department of Software and Computer Science Education. He has been affiliated with Charles University since 2008 and leads the computer graphics branch of the CGG research group. Position: Full Professor, Head of Computer Graphics Branch (CGG) Location: Mala Strana Room 425, Prague 1 Research interests include Predictive Rendering , Spectral Rendering , Fluorescence Effects , Polarization Modeling , and 3D Printing Optimization . His work focuses on creating physically accurate rendering techniques that predict real-world material appearances, particularly for fluorescent and polarizing surfaces. Recent publications highlight advancements in constrained spectral uplifting , fluorescence handling , and sky/atmosphere modeling . These works are published in venues like Computer Graphics Forum , SIGGRAPH , and Optics Express . Professional roles include membership in ACM SIGGRAPH and IEEE , reviewer for journals/conferences like Computer Graphics Forum (CGF) , and local organizer of EGSR 2011 . Labs and teams: Wilkie is part of the CGG research group , where members present ongoing work at seminars and collaborate on projects like the ART: Advanced Rendering Toolkit and DISTRO (Horizon 2020 grant).

Alice Valkárováمشاهده پروفایل

استاد

• Particle Physics
• Nuclear Physics
• High Energy Physics
• +۳ مورد دیگر

Alice Valkárová is a Professor at the Institute of Particle and Nuclear Physics within the Faculty of Mathematics and Physics at Charles University in Prague. Her office is located in the Troja Campus building at V Holešovičkách 2, Prague 8. She maintains active research in experimental particle physics with a focus on the H1 experiment at the DESY laboratory's HERA electron-proton accelerator facility. Her primary research interests center on photoproduction and "hard" diffraction phenomena in high-energy collisions. She has made significant contributions to understanding diffractive processes, particularly in the context of proton structure and QCD dynamics. Her work bridges theoretical frameworks with experimental data analysis from the HERA collider. She has organized major international conferences including Physics in Collision (PIC 2005) and the International Symposium on Multiparticle Dynamics (ISMD 2005) in the Czech Republic. Professor Valkárová teaches Experimental Methods of Subnuclear Physics (JSF 066), where she shares her expertise in particle detection systems, accelerator physics, and data analysis techniques. Her publication record spans from the early 2000s through 2012, with a concentration on diffraction physics, photoproduction, and HERA data analysis. The publication trends show consistent contributions to major conferences in particle physics including Trento, ISMD, and Physics in Collision series. Her research group actively participates in international collaborations centered around the H1 experiment. She has supervised numerous students and researchers in experimental particle physics techniques, though specific student names aren't documented in the available materials. Her laboratory work involves sophisticated detector systems including calorimeters, tracking devices, and scintillation counters for particle identification.

• General Algebra
• Non-associative Algebra
• Quasigroups
• +۶ مورد دیگر

David Stanovský serves as Associate Professor and chair of the Department of Algebra at the Faculty of Mathematics and Physics, Charles University in Prague. His office is located at Sokolovská 83, 18675 Praha 8 (Karlín campus), room 308, with contact number +420 22191 3359. His research centers on general algebra with emphasis on non-associative structures including quasigroups, loops, and self-distributive systems. He investigates quandles for knot theory applications and solutions to the Yang-Baxter equation, while developing computational tools through automated theorem proving in collaboration with CIIRC's ARG group. Stanovský supervises graduate research and has authored foundational textbooks "Základy algebry" (Foundations of Algebra) and "Počítačová algebra" (Computer Algebra, co-authored with Libor Barto). He actively organizes major conferences including Algebras & Clones fest, Loops series, and Summer Schools on Algebras and Ordered Sets. He leads the Department of Algebra's research initiatives and educational programs, including the "Schools in Nature" student program, while maintaining active collaborations with international research groups in universal algebra and computational mathematics.

Oleksandr Minakovمشاهده پروفایل

استادیار

• Nonlinear integrable equations
• Orthogonal polynomials
• Asymptotic analysis
• +۱ مورد دیگر

Oleksandr Minakov is an Assistant Professor in the Department of Mathematical Analysis at Charles University's Faculty of Mathematics and Physics, Prague. His research centers on nonlinear integrable equations and orthogonal polynomials using asymptotic and Riemann-Hilbert techniques. His core research interests include: Integrable equations Asymptotic analysis Riemann-Hilbert problems Orthogonal Polynomials Analysis of Minakov's recent publications (2020-2023) reveals a consistent focus on long-time dynamics of nonlinear partial differential equations, particularly the modified Korteweg-de Vries equation and nonlinear Schrödinger equation, with significant applications in random matrix theory (e.g., real Ginibre ensemble) and optical pulse propagation in laser physics. His methodology rigorously employs Riemann-Hilbert problem frameworks to derive asymptotic solutions for step-like initial data and shock problems. Minakov maintains active collaborations with researchers including Vladimir Kotlyarov, Tamara Grava, and Tom Claeys, with publications in top-tier journals such as Communications on Pure and Applied Mathematics and Communications in Mathematical Physics. His preprints on arXiv further extend his work into random matrix ensembles and integrable systems. He supervises academic work as indicated on his homepage, though specific student details are unavailable. Contact is available via oleksandr.minakov@mff.cuni.cz or minakov@karlin.mff.cuni.cz from room K226 at Karlín (Sokolovská 83, Prague 8).

• Computer Science
• Theoretical Computer Science
• Discrete Mathematics
• +۳ مورد دیگر

Prof. Vojtěch Rödl serves as a Professor at the Institute of Informatics, Charles University in Prague, Czech Republic. His office is located in room S 220 on the 2nd floor at Malostranské nám. 2/25 in the historic Lesser Town district (Prague 1), reflecting his active institutional presence within one of Europe's oldest academic centers. His research spans foundational areas of computer science and mathematics, with emphasis on: Theoretical Computer Science Discrete Mathematics Combinatorics Graph Theory Algorithmic Design Computational Complexity These disciplines form the mathematical backbone of modern computing, addressing structural problems in data organization, network analysis, and optimization. His work in combinatorics particularly explores extremal set systems and probabilistic methods, contributing to theoretical frameworks that underpin cryptographic systems and distributed computing architectures. Prof. Rödl maintains academic engagement through the Institute of Informatics, though specific advising activities or collaborative projects are not detailed in the source text. His institutional role encompasses teaching, research supervision, and participation in the university's scholarly ecosystem, centered in Prague's academic quarter near Charles Bridge.

• Online Algorithms
• Approximation Algorithms
• Scheduling
• +۹ مورد دیگر

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.

• Silviculture
• Forest Management
• Climate Change Adaptation
• +۷ مورد دیگر

Lukáš Bílek is an Associate Professor at the Department of Silviculture within the Faculty of Forestry and Wood Technology at Czech University of Life Sciences Prague. His academic position combines research, teaching, and management responsibilities, including service on the Dean's Board of the Faculty of Law and the Academic Senate of the Faculty of Law. His work focuses on forest management practices, particularly for Scots pine ecosystems in Czech conditions. Dr. Bílek's research interests center on silviculture, forest management, and climate change adaptation strategies for forest ecosystems. He specializes in close-to-nature forest management approaches, natural regeneration of Scots pine, and the ecological and economic aspects of pine forestry. His work bridges theoretical forest science with practical applications for forest managers, addressing challenges such as climate change impacts, sustainable production, and biodiversity conservation in managed forests. His publication record demonstrates a strong focus on Scots pine ecosystems, with numerous studies examining regeneration methods, growth responses to climate change, and management practices for pine-dominated forests. His research often integrates ecological, economic, and practical considerations, providing comprehensive approaches to forest management challenges. Much of his recent work addresses climate change adaptation strategies for Czech forests. Dr. Bílek has been actively involved in numerous research projects, particularly those addressing practical forest management challenges. He has developed several certified methodologies that translate research findings into practical guidance for forest managers, focusing on pine silviculture, biomass utilization, and sustainable management practices. His work often involves collaboration with forest management entities like Městské lesy Doksy. He is a co-author of the comprehensive book "Český a moravský les. Jeho počátky, současný stav a výhled do budoucnosti" (Czech and Moravian Forest: Its Origins, Current State and Future Outlook), which covers various forest ecosystem types across the Czech Republic.

Josef Štěpánekمشاهده پروفایل

استاد

• Optical Spectroscopy
• Biomolecular Interactions
• Nucleic Acid Structure
• +۴ مورد دیگر

Josef Štěpánek is a Professor at the Institute of Physics, Charles University , with a focus on optical spectroscopy and biomolecular structural analysis . He has led projects on DNA-protein interactions , metal-nucleic acid binding , and nanophotonic biosensors . His work bridges experimental and computational approaches to study nucleic acid dynamics and modified oligonucleotides . Research Highlights : Analysis of vibrational stages in nucleic acids via Raman and absorption spectroscopy Development of statistical methods for physico-chemical property extraction Design of optical measurement systems for surface-enhanced spectroscopy Article Trends reflect his expertise in nucleic acid conformational changes , porphyrin interactions , and SERS/SPR biosensor applications . Collaborations span institutions in Paris , Stockholm , and Moscow , with long-term stays at labs like BioMoCeTi and Laboratoire de Physicochimie Biomoléculaire et Cellulaire. Grants include leadership in projects such as Nanobiophotonics for future health care (GACR) and Nucleic Acid Regulatory Sequences (GACR), advancing plasmonic nanostructures and gene expression regulation .

• Regional Development
• Public Sector Administration
• Creative Industries
• +۷ مورد دیگر

Pavel Bednář is the Head of Department at the Department of Regional Development, Public Sector Administration and Law at Tomas Bata University in Zlín, Czech Republic. He holds the academic rank of Senior Lecturer. He has a Doctor’s degree in Human Geography and Regional Development from Charles University in Prague and multiple Master’s degrees from the University of Ostrava. His research focuses on regional development, creative industries, cluster policies, urban studies, and innovation performance. He has held academic positions at several institutions, including the University of Ostrava and Charles University. Affiliations: Faculty of Management and Economics, Tomas Bata University. Education: Doctor’s degree (2008), Master’s degrees (1998–2000). Bednář’s research explores spatial-temporal variations of coworking spaces, regional innovation systems, and the impact of public policies on development. He has conducted international collaborations through Erasmus and CEEPUS programs, contributing to studies on brownfield redevelopment and urban regeneration in post-socialist cities like Ostrava. His work also addresses socioeconomic impacts of the pandemic on urban workspaces and healthcare system evaluations across Europe. He has advised numerous theses on regional planning, smart city principles, and local development strategies. His publications span journals like Journal of Competitiveness and include projects on creative clusters in Central Europe and regional disparities in healthcare funding.