Find Academic Supervisors

• Static Analysis of Programs
• Formal Verification
• Concurrency
• +12 more

Tomáš Vojnar is a Professor at the Department of Intelligent Systems, Faculty of Information Technology, Brno University of Technology (FIT BUT), Czech Republic. He has been a faculty member since 1999, promoted to Associate Professor in 2007 and full Professor in 2012. He leads the VeriFIT research group and has extensive experience in academic leadership, including candidacy for Dean of FIT BUT in 2023 and chairing major conferences such as TACAS'19 and SV-COMP 2018. Research Interests: Static and dynamic analysis of programs, especially those with pointers and dynamic data structures Formal verification of concurrent and infinite-state systems Automata-theoretic and logical methods in verification Binary code analysis and performance analysis His recent publications show a strong trend in developing and applying static analysis tools for verifying memory safety, concurrency, and semantic equivalence in C programs. He has made significant contributions to tools like Predator, 2LS, and DiffKemp, which are widely used in the verification community and have achieved top rankings in international competitions such as SV-COMP. His work bridges theoretical foundations in automata and logic with practical software verification applications. Scientific Awards: Best theory paper award of ETAPS'10 (EATCS) Best paper awards at CADE'19 and CIAA'08 Best tool paper awards at ISSTA'18 and RV'12 Multiple gold, silver, and bronze medals in SV-COMP (Predator, 2LS, Symbiotic) Bronze Humies award for automated design of approximate circuits Gödel prize from FLoC 2014 Olympic Games 1 gold and 3 silver medals at SL-COMP'14 Siemens prize for outstanding PhD thesis (2001) Advising and Grants: He has supervised numerous PhD and Master's students who have contributed to major verification tools and publications. He has been actively involved in national and international research projects, including the Czech Science Foundation panel P103 (2019–2023), and has secured funding for research in formal methods and software verification. His collaborations span institutions in France (LIAFA, CNRS), Austria (TU Vienna), and beyond. Labs and Teams: He leads the VeriFIT research group at FIT BUT, which focuses on formal methods and software verification. The group develops state-of-the-art tools such as Predator (shape analysis), 2LS (heap verification), DiffKemp (semantic diffing), and others used in both academia and industry. The team actively participates in international verification competitions and collaborates with researchers worldwide.

• Computational Intelligence
• Genetic Programming
• Evolutionary Algorithms
• +3 more

Martin Pilát is an Associate Professor at Charles University's Faculty of Mathematics and Physics, specifically within the Department of Theoretical Computer Science and Mathematical Logic. His research and teaching focus on computational intelligence, genetic programming, and evolutionary algorithms. His work includes development of surrogate models in genetic programming, teaching materials for computational intelligence seminars, and implementation frameworks for evolutionary algorithms. He maintains a professional GitHub presence with repositories related to multi-agent systems, machine learning pipelines, and academic Python implementations. Contact details: Martin.Pilat@mff.cuni.cz

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.

• Population Genetics
• Ancient DNA Analysis
• Human Evolutionary History
• +7 more

Pavel Flegontov, Ph.D. is a researcher at the Department of Biology and Ecology within the Faculty of Science at the University of Ostrava. He specializes in population genetics, archaeogenetics, and genomic analysis with a particular focus on human evolutionary history across Eurasia and Southeast Asia. His research integrates ancient DNA analysis with computational methods to reconstruct population histories and migration patterns. Dr. Flegontov's primary research interests center on population genetics and human evolutionary history, with significant contributions to understanding the genetic history of Eurasian and Southeast Asian populations. His work employs advanced statistical methods including f-statistics and qpAdm modeling to analyze genetic admixture events. He has made important contributions to studies of Indo-European origins, Kra-Dai speakers in Thailand, and South Asian genetic influences in Southeast Asia, demonstrating expertise in connecting genetic data with historical and linguistic evidence. His publication record shows a strong trend toward increasingly sophisticated methods for analyzing complex population histories, with recent work focusing on methodological limitations and improvements in genetic admixture analysis. His research spans both human population genetics and marine microbial ecology, reflecting interdisciplinary approaches to evolutionary questions. The consistent publication in high-impact journals like Nature, Science, and PLOS Genetics demonstrates significant contributions to the field. Dr. Flegontov serves as principal investigator for multiple research grants, including projects funded by the Czech Science Foundation (GA ČR) and the Czech Academy of Sciences (GA AV). His current projects include "Archeogenetic perspective on the spread of Slavs in the first millennium AD" (2025-2027) and previously led "Genomic formation of Indo-Europeans: new approaches to modeling genetic admixture guided by simulated data" (2021-2024). He has also collaborated with Harvard University on subcontract research agreements. He teaches courses in genome analysis (WGEAN, 7GEAN, 8GEAN) and has supervised doctoral research, including Nefize Ezgi Altinişik's 2019 dissertation on the connection between America and Eurasia: Population history of people in the American Arctic. His work demonstrates strong mentorship in training the next generation of population geneticists.

Roman ŠenkeříkView profile

Associate Professor

• Artificial Intelligence
• Evolutionary Algorithms
• Neural Networks
• +9 more

Roman Šenkeřík is an Associate Professor at the Department of Informatics and Artificial Intelligence within the Faculty of Applied Informatics at Tomas Bata University in Zlín (TBU Zlín). He serves as the Head of the Artificial Intelligence Laboratory (AILab) and has been actively involved in interdisciplinary research at the intersection of AI and complex systems. Specializes in evolutionary algorithms, neural networks, and hybridization of soft-computing techniques Focuses on optimization of process control using AI and development of metaheuristics Key interests include chaos theory, cryptology, and cybersecurity applications His research spans data mining, high-performance computing, and synthesis of complex systems. He has supervised over 80 bachelor's and master's theses and guided multiple doctoral students to successful completion. Scientific Awards: Best paper award at AETA Conference (2018) Best paper award at CISIM Conference (2014) Best paper awards at Nostradamus Conferences (2012, 2013) Best paper award at PCO Conference (2010) Prof. Šenkeřík has participated in numerous international collaborations through Erasmus and other mobility programs, including extended internships at University of Maribor (Slovenia) and Strathclyde University (UK). He is a Senior Researcher at CEBIA-Tech Regional Research Centre and has contributed to multiple EU-funded projects.

Radek ValaView profile

Assistant Professor

• Web Information Systems
• Mobile Technology
• Cybersecurity
• +3 more

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.

Adam ViktorinView profile

Assistant Professor

• Artificial Intelligence
• Data mining
• Adaptive strategies for the Differential Evolution algorithm

Adam Viktorin is an Assistant Professor at the Faculty of Applied Informatics, Tomas Bata University in Zlín, Czech Republic, where he is affiliated with the Institute of Informatics and Artificial Intelligence. He has held this position continuously since 2019, with his current appointment starting in 2021. His educational qualifications are as follows: Ph.D. in Engineering Informatics, Tomas Bata University in Zlín (2015-2021) M.Sc. in Computer and Communication Technologies, Tomas Bata University in Zlín (2013-2015) B.Sc. in Information and Control Technologies, Tomas Bata University in Zlín (2010-2013) Vocational degree from Vsetín Secondary Technical School (2005-2009) Dr. Viktorin's research focuses on Artificial Intelligence with specialized expertise in Adaptive strategies for the Differential Evolution algorithm and Data mining. His work advances evolutionary computation techniques for optimization problems and develops data mining methodologies for complex dataset analysis, contributing to computational intelligence and applied informatics. No scientific awards are documented in the available records. While the text references project outputs and publications, specific details about academic advising, student supervision, or research grants are not provided. His active research engagement is evident through ongoing project involvement and scholarly output. Dr. Viktorin maintains professional visibility through Twitter ( @AdamNimbleGuy ) and is accessible via email aviktorin@utb.cz during scheduled consultation hours on Tuesdays from 12:00-13:00.