Find Academic Supervisors

• Speech Recognition
• Speaker Verification
• Language Identification
• +7 more

Professor Jan Černocký serves as Head of Department at the Department of Computer Graphics and Multimedia (DCGM) within the Faculty of Information Technology at Brno University of Technology (FIT VUT). With a professional email cernocky@fit.vut.cz and office L221.2, he maintains an active research profile with numerous publications spanning over 20 years in the field of speech processing and recognition. His work is well-documented through multiple research identifiers including ORCID iD 0000-0002-8800-0210, Scopus Author ID 6604040821, and Researcher ID M-7494-2019. Professor Černocký's research interests focus primarily on advanced speech processing technologies, with particular emphasis on speech recognition, speaker verification, language identification, and multimodal systems. His work demonstrates a strong trajectory from traditional speech processing techniques toward modern deep learning approaches, especially in self-supervised learning for speech applications. Recent publications show his leadership in developing benchmarks like TS-SUPERB for target speech processing and innovative methods for speaker verification using transformer models. His research group at BUT has made significant contributions to multi-channel speech processing, target speech extraction, and speaker diarization systems. The analysis of Professor Černocký's recent publications (2023-2025) reveals several key trends in his research direction. There's a clear shift toward self-supervised learning approaches for speech processing, with numerous papers exploring how pre-trained models can be adapted for speaker verification, target speech extraction, and multi-channel processing. His work increasingly incorporates transformer architectures and attention mechanisms, reflecting the broader trends in speech processing research. The 2024 publications particularly highlight work on multimodal analysis (BESST dataset for stress detection) and practical applications of speech technology for social inclusion. Throughout his career, Professor Černocký has maintained strong collaborative relationships with researchers across Europe and internationally, evidenced by his extensive publication record with co-authors from multiple institutions. His leadership role as Head of Department at DCGM places him at the center of speech processing research at Brno University of Technology, where his team continues to produce cutting-edge research in speech technology.

Michal PavelkaView profile

Associate Professor

• Geometric mechanics and thermodynamics (GENERIC)
• Modelling of electrochemical systems (fuel cells, batteries)
• Non-equilibrium continuum thermodynamics and hyperbolic systems
• +1 more

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.

Jakub CapekView profile

Assistant Professor

• Phenomenology
• Hermeneutics
• 20th-century philosophy
• +3 more

Jakub Capek is an Assistant Professor at the Institute of Philosophy and Religious Studies within the Faculty of Arts and Sciences in Prague . His work bridges phenomenology and hermeneutics, focusing on the philosophical exploration of human practice, decision-making, and temporal experience. Education: 1997: Master of Philosophy and History at Faculty of Arts and Sciences in Prague 2001: Dissertation defense on time and decision-making under Pavel Kouba and Jean-Michel Salanskis His research interrogates how human action and existential situations are revealed through 20th-century phenomenology and hermeneutics, engaging thinkers like Bergson, Heidegger, Sartre, and Ricoeur. His publications explore concepts such as the phenomenon of time, metaphysical frameworks, and Fink's educational philosophy. The articles and translations he has produced reflect a deep engagement with phenomenological traditions, particularly in understanding existential structures, freedom, and the interpretation of lived experience. His work often synthesizes continental philosophy with historical and ethical inquiries.

• History of Architecture
• Art History
• Museology
• +4 more

Professor Pavel Šopák serves as a Professor in the Department of Theory at the Faculty of Architecture, Brno University of Technology. He actively teaches the History of Architecture series (DA1-T to DA4-T) and History of Art (DEU-T) for the 2025/2026 academic year, delivering lectures in Czech across winter and summer semesters. Additionally, he contributes to academic discourse as a Member of the Editorial Board for scholarly publications. His research spans architectural history with deep regional expertise in Moravia and Silesia, focusing on: 19th-20th Century Czech Architecture Museology and Cultural Heritage Preservation Sacral and Urban Architecture Biographical Studies of Architects Architectural Theory and Phenomenology Historical Documentation Methods Analysis of Šopák's 2020-2025 publications reveals a cohesive scholarly trajectory centered on documenting Czech architectural heritage through interdisciplinary lenses. His work consistently examines individual architects (Miloš Laml, Franz Kachler, Adolf Loos), museum evolution (particularly technical museums in Ostrava), and regional architectural character. A defining trend is the integration of architectural history with museology and intellectual history, contextualizing built environments within socio-historical frameworks while emphasizing visual standards, spatial relationships, and cultural identity in Central European contexts.

• Computer Vision
• Image Processing
• Machine Learning
• +5 more

Prof. Ing. Adam Herout, Ph.D., is a faculty member at the Faculty of Information Technology (FIT) of Brno University of Technology (BUT). He serves as Deputy Head of the Department of Computer Graphics and Multimedia (DCGM), focusing on computer vision, image processing, and 3D reconstruction. His research spans traffic surveillance, augmented reality, and real-time processing, with applications in medical imaging and autonomous systems. Academic Rank: Professor Department: Computer Graphics and Multimedia Email: herout@fit.vut.cz Herout's research interests lie in computer vision, machine learning, and their interdisciplinary applications. He has pioneered techniques for camera calibration using vehicle landmarks, density-based traffic analysis, and medical imaging solutions like cranial implant design. His work combines theoretical advancements with practical implementations in real-time systems. Key trends in his 15 most recent articles (2019–2023) include deep learning for traffic analysis, medical image segmentation, and optimization of computer vision algorithms. Sub-fields span from automated checkout systems to CNN-based AFM data correction, reflecting his interdisciplinary expertise. Scientific recognitions include the Commemorative Medal of FIT BUT (Bronze 2012, Silver 2019) and the Imagine Cup 2013. He leads the Computer Graphics Research Group at FIT and chairs disciplinary committees.

• Speech Recognition
• Language Identification
• Speaker Recognition
• +3 more

Ing. Petr Schwarz, Ph.D. , is an Assistant Professor at the Department of Computer Graphics and Multimedia, Faculty of Information Technology, Brno University of Technology. He specializes in speech recognition and biometric systems, with a focus on robustness in real-world conditions. Current roles: Assistant Professor, Researcher, Project Lead Key affiliations: Brno University of Technology (FIT), EU Horizon Europe, Czech Defense Research Program His research spans speech recognition , language identification , and multimodal datasets for security applications. Recent work includes AI-driven emergency call systems and tools to combat voice deepfakes. Notable projects include: Multilingual and Cross-cultural Dialogue Systems (EU Horizon Europe, 2024-2026) Voice Deepfake Detection (Czech Sectech Program, 2024-2026) His publications analyze Gaussian mixture models, i-vector migration, and phonetic search techniques. Trends emphasize robust algorithms for security-critical domains . Scientific accolades include the Silver Medal from BUT Rector (2006) and Brno FIT Bronze Medal (2022). He has contributed to open-source tools like Kaldi and developed systems for NIST evaluations.

• Image Restoration
• Blind Deconvolution
• Superresolution
• +5 more

Assoc. Prof. Filip Šroubek, Ph.D., DSc. is a Professor of Applied Mathematics at the Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University , and an Associate Professor at the Faculty of Mathematics and Physics, Charles University . He serves as Deputy Head of the Department of Image Processing at the Czech Academy of Sciences. His career spans postdoctoral research at Instituto de Optica (CSIC, Madrid) and a Fulbright scholarship at University of California, Santa Cruz . Education: M.Sc. in Computer Science, Czech Technical University (1998) Ph.D. in Computer Science, Charles University (2003) D.Sc. (Habilitation), Czech Academy of Sciences (2014) Research Interests: Šroubek specializes in image restoration , blind deconvolution , and superresolution , with applications in biomedical imaging, forensic analysis, and mobile device optimization. His work on multi-object tracking and blur-invariant algorithms bridges theoretical and applied computer vision. Publication Trends: His recent articles focus on neural networks for image processing (2025), biomedical imaging (2024), and dynamic object tracking (2021-2023). Collaborations span neuroscience , materials science , and forensic engineering . Scientific Awards: Fulbright Visiting Scholarship (2010/2011) Honorable Mention at GCPR (2019) Outstanding Contribution Award (2013) Advising & Grants: Supervised projects include PIZZARO (forensic image analysis), 4D-STEM/PNBD (electron diffraction), and SONO (ultrasound technology). Grants emphasize interdisciplinary applications of image processing in medicine and engineering. Labs & Teams: Affiliated with the Department of Image Processing (UTIA, Czech Academy of Sciences) , he collaborates with teams in biomedical imaging, quantum dot characterization, and mobile technology optimization.

• Speaker Recognition
• Biomedical Image Analysis
• Signal Processing
• +3 more

Johan Andréas Rohdin is an Assistant Professor at the Department of Computer Graphics and Multimedia , Faculty of Information Technology , Brno University of Technology. His research focuses on Speaker Recognition , Biomedical Image Analysis , and Signal Processing , with applications in forensic speaker comparison and retinal disease diagnosis. University: Brno University of Technology Role: Assistant Professor Research Groups: Speech Data Mining Research Group, BUT Speech@FIT His work addresses speaker diarization , embedding extractor optimization , and automated retinal symmetry analysis using GANs. Recent publications emphasize self-supervised learning, anti-spoofing techniques, and forensic multimodal datasets. Key projects include contributions to NIST Speaker Recognition Evaluations and development of the ROXSD multimodal dataset. He actively collaborates with the Speech Data Mining Research Group and participates in doctoral examination commissions.

Jana StrakováView profile

Researcher

• Natural Language Processing
• Deep Learning
• Multilingual Text Processing
• +3 more

Jana Straková is a researcher at the Institute of Formal and Applied Linguistics (ÚFAL) within the Faculty of Mathematics and Physics at Charles University in Prague. Her work focuses on advancing natural language processing techniques for multilingual applications, particularly in deep learning architectures for linguistic analysis. Her research interests span Natural Language Processing , Deep Learning , and Multilingual Text Processing with specialization in named entity recognition, dependency parsing, and morphological analysis. She has pioneered neural network approaches for tasks like diacritics restoration and grammar error correction, with particular emphasis on Czech language processing while extending methodologies to Latin and other languages. Analysis of her publication record from 2019-2025 reveals consistent innovation in NLP tool development, particularly the NameTag and UDPipe systems. Her work demonstrates strong integration of contextual embeddings with linguistic resources, showing increasing focus on cross-lingual transfer and historical language processing in recent years. As part of the ÚFAL research group, she collaborates extensively with Milan Straka and Jan Hajič on developing open-source NLP pipelines. Her projects include creating large-scale datasets like CWRCzech for web relevance ranking and advancing ontology engineering through LLM-augmented approaches.

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.

• Musicology
• Historical Musicology
• Baroque Music
• +5 more

Prof. PhDr. Jana Perutková, Ph.D. is a distinguished Professor at the Department of Musicology within the Faculty of Arts at Masaryk University in Brno, Czech Republic. Her academic career spans decades of dedicated research and teaching in historical musicology, with particular expertise in Baroque music traditions and Central European musical heritage. She maintains an active research profile with numerous publications and currently supervises multiple graduate students working on musicological topics. Professor Perutková's research interests focus on historical musicology, particularly 18th-century music, opera studies, early music performance practice, and Czech musical history. Her work demonstrates deep engagement with music archives, especially monastic collections, and the transmission of musical works across Central Europe. She has developed significant expertise in pasticcio operas, sacred music traditions, and the musical networks surrounding aristocratic courts in the Habsburg Empire. Her recent publications reveal a strong thematic concentration on Baroque music, particularly examining music collections from monastic institutions, opera productions at Viennese theaters including the Kärntnertor Theater, and the works of composers associated with Count Questenberg's circle. Her research shows consistent attention to manuscript studies, music transmission across Central Europe, and the intersection of religious and secular musical practices during the Enlightenment period. Supervises multiple graduate students working on topics ranging from 18th-century composer migrations to monastic music collections Leads several research projects focused on Baroque music history and e-learning development Active participant in academic committees including the Industry Council for Musicology and Program Boards for Musicology study programs

• Computational Linguistics
• Natural Language Processing
• Language Technology Infrastructure
• +5 more

Jan Hajič is a Full Professor of Computational Linguistics and Deputy Director of the Institute of Formal and Applied Linguistics at Charles University in Prague, Czech Republic. He also directs the LINDAT/CLARIAH-CZ infrastructure, part of the EU CLARIN network. His academic roles include Adjunct Full Professor at the University of Colorado Boulder (since 2016). He holds leadership positions in major initiatives like the European Language Grid (ELG) and chairs META-NET, the European language technology network. Education: PhD in Computational Linguistics (1995) from Charles University, with earlier studies in Mathematics and Physics (1984). Industrial experience includes IBM Research (1991) and Johns Hopkins University (1999–2000 as Visiting Assistant Professor). Research interests focus on semantic analysis, multilingual NLP, treebanking (e.g., Prague Dependency Treebank), and large-scale language technology infrastructure. He leads projects like OpenEuroLLM (2025), HPLT (2022–2025), and UMR (2023–2027). Over 180 publications and a book on computational morphology highlight his scholarly contributions. Awarded Donatio Prize (2022), Silver Medal (2020), and recognition for best student paper (2005). PI/co-PI of 40+ projects, including EU Horizon grants and NSF-funded initiatives. Key roles in international conferences: ACL 2010 General Chair, CoNLL Shared Tasks, and TLT workshop series. Labs/Teams: Oversees LINDAT/CLARIAH-CZ, collaborates with Brandeis University, University of Colorado Boulder, and European research consortia. Active in policy through Czech Science Foundation and EU advisory boards.

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.

• Natural Language Processing
• Artificial Intelligence
• Information Extraction
• +4 more

Assoc. Prof. Pavel Pecina, Ph.D., is a faculty member at the Institute of Formal and Applied Linguistics, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic. His primary academic role as an Associate Professor focuses on Natural Language Processing , Artificial Intelligence , and related areas. Research Interests: Information extraction, information retrieval, machine translation, multimodal data interpretation, optical music recognition Teaching: Courses since 2012-2022 including Natural Language Processing , Information Retrieval , and Statistical Methods in NLP Key Research Projects include GI-Insight (AI for healthcare), RES-Q+ (global stroke care registry), and MEMORISE (heritage digitization). His recent publications (2023-2025) demonstrate expertise across clinical NLP , historical document analysis , and music technology domains. Advising: Supervised 10+ graduate students in areas ranging from semantic search to optical music recognition. Collaborates with international institutions on multilingual translation and medical informatics challenges through initiatives like IWSLT and CLEF eHealth.

• interpretation of deep neural networks
• machine learning
• dependency syntax
• +3 more

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.