جست‌وجوی استاد و پژوهشگر

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.

• Discourse Analysis
• Sentence Information Structure
• Word Order
• +۷ مورد دیگر

Kateřina Rysová is a researcher at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics, Charles University in Prague. Her work focuses on discourse analysis, sentence information structure, Czech word order, dependency syntax, corpus linguistics, and historical Czech studies. Key Affiliations: Charles University in Prague (ÚFAL), Institute of Czech Language (Czech Academy of Sciences), Czech-German collaborations. Research Interests: She investigates how contextual and valency factors shape Czech word order, with a focus on obligatory and free verbal modifications. Her work bridges functional generative description with empirical corpus analysis, including studies on discourse connectives (primary vs. secondary), text coherence, and older Czech syntax. Publication Trends: Her recent articles (2018–2015) emphasize discourse connectives, coherence evaluation, and Czech-German comparative syntax. Earlier works (2014–2011) explore valency-driven word order, annotation principles in the Prague Dependency Treebank, and historical Czech lexicon. Her contributions to older Czech studies include lexicographical projects like the Lexikální databáze humanistické a barokní češtiny (2010) and Elektronický slovník staré češtiny (2011). Labs & Teams: She contributes to the Prague Dependency Treebank and LINDAT/CLARIN projects, focusing on multilingual corpus annotation and computational analysis of text structure.

• Molecular dynamics simulations
• Quantum-chemical calculations
• Rational drug design
• +۵ مورد دیگر

Ivan Barvík is a Researcher at the Department of Biomolecular Physics within the Faculty of Physics at Charles University , where he has been affiliated since 1999. His work bridges computational physics, biophysics, and drug design. Education : Ph.D. (1995) in Mathematical and Computer Modeling from Charles University, supervised by Doc. RNDr. Jiří Bok CSc. Mgr. (1995) in Mathematical and Computer Modeling in Physics and Technology from Charles University, supervised by RNDr. Miroslav Kotrla CSc. Research Interests : Barvík specializes in molecular dynamics simulations and quantum-chemical calculations , applying these methods to rational drug design and biological membranes . He focuses on computational techniques for modeling biomolecules, including free energy calculations and parallelization via OpenMP , MPI , and CUDA . Teaching : He teaches computer modeling of biomolecules , molecular dynamics , advanced programming methods , and numerical methods in computational physics , contributing to both undergraduate and graduate education. Supervision : Barvík has mentored numerous students, including Artem Rakhimbekov and Krystof Prusa , and supervised theses on topics like computational physics, biomolecular simulations, and numerical methods. Tools and Collaborations : He utilizes software such as CHARMM-gui , NAMD , Gromacs , and Gaussian , and is associated with resources like AlphaFold3 and MetaCentrum .

• Theoretical Computer Science
• Computational Complexity
• Data Structures
• +۳ مورد دیگر

Prof. Michal Koucký is a faculty member at the Institute of Informatics, Faculty of Mathematics and Physics, Charles University in Prague. His research focuses on theoretical computer science, particularly computational complexity, data structures, algorithms, and combinatorics. He leads significant research projects including EPAC (supported by GA CR) and LBCAD (funded by ERC). His educational background includes a Ph.D. from Rutgers University (2003) and a Master's degree from Charles University (1998). Prof. Koucký's research spans multiple areas of theoretical computer science with emphasis on computational complexity , data structures , algorithms , and combinatorics . His work explores fundamental questions about computational efficiency, lower bounds, and algorithmic techniques. He has made significant contributions to edit distance algorithms, string processing, and circuit complexity. His research often bridges theoretical foundations with practical algorithmic applications, particularly in areas like dynamic data structures and approximation algorithms. An analysis of his recent publications (2019-2024) reveals a strong focus on string algorithms, particularly edit distance problems. His work develops novel approximation techniques, sketching methods, and sublinear-time algorithms for pattern matching. There's also significant work on data structure lower bounds and connections to popular complexity conjectures. His research demonstrates a consistent pattern of tackling fundamental problems with innovative approaches that push theoretical boundaries while maintaining practical relevance. Antonin Svoboda award for best dissertation in 2014 (awarded to Jan Bulánek) Best paper award at SAGT 2016 for 'The Big Match in Small Space' Best paper award at FOCS 2018 for 'Approximating Edit Distance Within Constant Factor in Truly Sub-Quadratic Time' He has successfully advised numerous graduate students including Pavel Dvořák, Karel Král, Debarati Das, and Jan Bulánek who have gone on to positions at prestigious institutions like Bristol, Google (Zurich), and Penn State. His research is supported by significant grants including the EPAC project (GA CR) and LBCAD project (ERC), demonstrating the impact and relevance of his work in theoretical computer science. Prof. Koucký is an active member of the theoretical computer science community, regularly presenting at major conferences including STOC, FOCS, ICALP, and SODA. His work often involves collaborations with researchers from institutions worldwide, contributing to a vibrant research environment at Charles University's Institute of Informatics.

• 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.

• Computational Linguistics
• Natural Language Processing
• Czech Language Processing
• +۴ مورد دیگر

Zuzana Nevěřílová serves as an Assistant Professor at Masaryk University's Department of Czech Language within the Faculty of Arts. She also maintains external cooperation with the Department of Machine Learning and Data Processing at the Faculty of Informatics, demonstrating interdisciplinary engagement between linguistic theory and computational approaches. Her research interests span computational linguistics with particular emphasis on Czech language processing, natural language processing methodologies, and development of language resources. Her work bridges theoretical linguistics with practical computational applications, focusing on areas such as named entity recognition, text analysis, word embeddings, and language resource development. Dr. Nevěřílová's recent publication trends (2021-2025) reveal strong focus on Czech language technologies, including named entity processing in parallel corpora, efficient language models, and educational applications of NLP. Her work demonstrates consistent contributions to Slavonic language processing communities through workshops like RASLAN and conferences like TSD. Her scientific contributions include extensive publications in proceedings of international conferences and workshops, software development for language resources, and educational materials for digital humanities. She has supervised various projects related to language technology and has contributed to significant resources like the New Encyclopedic Dictionary of Czech and VerbaLex lexical database. Her research has practical applications in language services, educational technology, and digital humanities. Dr. Nevěřílová works within the Institute of the Czech Language at Masaryk University, contributing to research teams focused on Czech language processing, corpus development, and computational lexicography.