RNDr. Vít Musil, Ph.D.

Curriculum Vitae

Person-Related Identification Information

• OrcID: 0000-0001-6083-227X
• Scopus Author ID: 57142131700
• ReasearcherID: C-1754-2017A

Employment - Position

• Assistant Professor

Education and Academic Qualifications

• 2018: PhD. in Mathematical Analysis, Faculty of Mathematics and Physics, Charles University
• 2015: RNDr. (Rerum Naturalium Doctor) in Mathematics, Faculty of Mathematics and Physics, Charles University
• 2014: Mgr. in Mathematical Analysis, Faculty of Mathematics and Physics, Charles University

Employment

• Jul 2023 –: Assistant Professor, Faculty of Informatics, Masaryk University
• Dec 2022 – Jun 2023: Researcher, Faculty of Informatics, Masaryk University
• Dec 2020 – Nov 2022: Postdoc, Faculty of Informatics, Masaryk University
• Nov 2018 – Nov 2020: Postdoc, Dipartimento di Matematica e Informatica 'Ulisse Dini', University of Florence
• Oct 2018 – Oct 2020: Postdoc, Institute of Mathematics, Czech Academy of Sciences

Scientific and Research Activities

• Explainability of neural networks: improving methods to understand and interpret complex neural models; compositional concept-based explainability; applications in medical imaging.
• Digital and computational pathology: developing machine learning methods for histopathological image analysis, with a focus on interpretability and clinical applicability.
• Optimization problems as layers in neural networks: mathematically sound methods for training neural networks with non-differentiable or computationally challenging optimization layers.
• Optimization in agent-based systems: strategies for security games using novel relaxation techniques and gradient-based methods, with applications in defense and security.
• Functional analysis, differential equations and approximation theory.

Internship

• May, Aug, Oct -- Nov 2019, Feb, Mar, Jul, Sep 2020, May, Jul 2022: Max Planck Institute for Intelligent Systems, Germany
• Jun 2022, The University of Warwick, Coventry, UK
• Mar 2018, The Ohio State University, Columbus, Ohio, USA
• Jan 2017 – May 2017: Visiting Scholar, The Ohio State University, Columbus, Ohio, USA
• Oct 2016; Jan, Nov 2017; Nov 2018: University of Florence, Italy
• Nov 2015: Brock University, St. Catharines, Canada

University Activities

• 2023 –: Member of the State examination board (Bachelor's) – Informatics; Programming and application development; Cybersecurity; Computer science in education
• 2023 –: Member of the State examination board (Master's) – Theoretical computer science
• 2024, 2025: Head of the organizing committee, Summer School on XAI in Digital Pathology, MUNI

Activities Outside University

• 2026 –: ELLIS Society member
• 2025 –: European Society of Digital and Integrative Pathology member
• 2020 –: European Mathematical Society member
• 2011 –: Czech Mathematical Society and Union of Czech Mathematicians and Physicists member

Awards Related to Science and Research

• 2025: Masaryk University Rector's Award for Outstanding Research Achievements for Young Scientists Under 40 in Economics and Informatics
• 2021: Selected among 200 young researchers, 8th Heidelberg Laureate Forum
• 2020: Best Paper Award shortlist, CVPR (Seattle, virtual)
• 2020: Postdoc2MUNI two-year postdoctoral fellowship, Masaryk University
• 2018: Postdoctoral fellowship, Elliptic and Parabolic Equations and Relative Functional Inequalities, University of Florence
• 2017: USA travel scholarship, Karel Urbanek Fund
• 2017: Visiting scholarship, University of Florence
• Jun 2026: Invited lecture, Conference NAFSA, Prague
• Jul 2025: Invited lecture, Workshop on neuro-symbolic AI, Prague
• Feb 2023: Invited lecture, Conference GEOFI, Prague
• 2019–2022: Repeated invited lectures, Autonomous Learning seminar, MPI for Intelligent Systems, Tübingen
• Feb 2021: Invited lecture, Workshop on Discrete Methods in ML, Ostrava

Major Publications

• PEKÁR, Matěj; Vít MUSIL; Rudolf NENUTIL; Petr HOLUB a Tomáš BRÁZDIL. LSP-DETR: Efficient and scalable nuclei segmentation in whole-slide images. Computer Methods and Programs in Biomedicine. CLARE: Elsevier Ireland Ltd, 2026, roč. 287, -, s. 109614-109629. ISSN 0169-2607. Dostupné z: https://doi.org/10.1016/j.cmpb.2026.109614. URL info
• MALÝ, Jan; Zdeněk MIHULA; Vít MUSIL a Luboš PICK. Maximal noncompactness of embeddings into Marcinkiewicz spaces. ANNALI DI MATEMATICA PURA ED APPLICATA. HEIDELBERG: SPRINGER HEIDELBERG, 2025, roč. 204, č. 6, s. 2633-2658. ISSN 0373-3114. Dostupné z: https://doi.org/10.1007/s10231-025-01585-w. Published version, Preprint info
• KREBS, Martin; Jan OBDRŽÁLEK; Vít MUSIL a Tomáš BRÁZDIL. Beyond Occlusion: In Search for Near Real-Time Explainability of CNN-Based Prostate Cancer Classification. Online. In 2025 IEEE 22nd International Symposium on Biomedical Imaging, ISBI. NEW YORK: IEEE, 2025, s. 1-5. ISBN 979-8-3315-2053-3. Dostupné z: https://doi.org/10.1109/ISBI60581.2025.10980802. Published version, Preprint info
• BRÁZDIL, Tomáš; Vít MUSIL; Karel ŠTĚPKA; Adam KUKUČKA; Rudolf NENUTIL; Adam BAJGER a Petr HOLUB. Strojové učení v digitální patologii. Ceskoslovenska Patologie. Nakladatelske Stredisko CLSJE Purkyne, 2025, roč. 61, č. 2, s. 58-69. ISSN 0009-0611. URL info
• PAULUS, Anselm; Georg MARTIUS a Vít MUSIL. LPGD: A General Framework for Backpropagation through Embedded Optimization Layers. Online. In Salakhutdinov R. and Kolter Z. and Heller K. and Weller A. and Oliver N. and Scarlett J. and Berkenkamp F. Proceedings of Machine Learning Research. 235. vyd. Neuveden: ML Research Press, 2024, s. 39989-40014. ISSN 2640-3498. Proceedings of Machine Learning Research info
• SAHOO, Subham Sekhar; Anselm PAULUS; Marin VLASTELICA; Vít MUSIL; Volodymyr KULESHOV a Georg MARTIUS. Backpropagation through combinatorial algorithms: identity with projection works. In 11th International Conference on Learning Representations, ICLR 2023. 2023. Poster, Openreview info
• ROLINEK, Michal; Vít MUSIL; Anselm PAULUS; Marin VLASTELICA; Claudio MICHAELIS a Georg MARTIUS. Optimizing Rank-based Metrics with Blackbox Differentiation. Online. In 978-1-7281-7168-5. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020). Los Alamitos: IEEE COMPUTER SOC, 2020, s. 7617-7627. ISSN 1063-6919. Dostupné z: https://doi.org/10.1109/CVPR42600.2020.00764. Springer info
• ROLÍNEK, Michal; Paul SWOBODA; Dominik ZIETLOW; Anselm PAULUS; Vít MUSIL a Georg MARTIUS. Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers. Online. In Vedaldi A.Bischof H.Brox T.Frahm J. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 12373 LNCS. Springer Science and Business Media Deutschland GmbH, 2020, s. 407-424. ISBN 978-3-030-58603-4. Dostupné z: https://doi.org/10.1007/978-3-030-58604-1_25. Springer info

2026/08/31