Research groups

Laboratories

The group focuses on the application of machine learning methods and artificial intelligence in data processing, especially from industry, but also in other sectors. The group also cooperates in the areas of computing biology and bioinformatics, focusing on optimization methods.

Physical space
We offer up to 15 workstations equipped with presentation technology for collaborative data analysis, result visualization, and team discussions. The spaces are designed for independent research work and group projects, supporting both student work and employee research projects.

Modern AI computing cluster
Our state-of-the-art infrastructure comprises five specialized nodes designed for artificial intelligence and machine learning.

The RTX 4090 series includes 3 servers, each equipped with AMD EPYC 9454 processors, 48GB of RAM, and 2x RTX 4090 with 24GB of VRAM each. The RTX A6000 series includes 2 servers with AMD EPYC 9454 processors, 48GB RAM, and 2x RTX A6000 with 48GB VRAM each.

Main computing server
This powerful system for massive parallel computing features 432 processor cores, 7.5 TB of shared RAM, 2 NVIDIA Tesla A100 GPUs, and 60 TB of disk storage.

Additional GPU computing servers
Linux servers running on CentOS include 2 dual-processor servers with 28 cores each and 4x NVIDIA GTX 1070 per server. The Windows server for specialized applications offers 24 cores and 768GB of RAM.

Network storage
A total capacity of 679TB ensures permanent and secure storage of research data.

Usage options
Our multi-level architecture provides comprehensive support for processing large datasets, optimization tasks and algorithms, machine learning and deep learning workflows, as well as intensive computational analysis. The infrastructure covers the entire research cycle from development and prototyping to production-scale deployment.

Cooperation

The group is actively collaborating with leading industrial partners, applying our AI and data technologies to address specific manufacturing and technological challenges. Among other things, we have participated in the following applications.

We collaborated with Škoda Auto on advanced data analytics in manufacturing processes with a focus on quality control. Our AI algorithms helped optimize production lines and predict potential quality issues before they manifested in the final products.

With Hella Autotechnik, we developed a solution for automatic testing and diagnostics of headlights. Our systems enabled not only automated testing, but also intelligent planning of testing procedures based on historical data and predictive models.

For Brose, we implemented analytical tools focused on monitoring production processes and tracing the causes of production errors. Our AI systems were able to identify hidden patterns in production data and speed up the troubleshooting process.

With SprayVision, we worked on optimizing robotic painting using advanced algorithms. Our solution used machine learning to optimize robot trajectories and ensure even application of coating materials.

With Unicorn, we developed predictive models for gas and electricity consumption that used advanced machine learning algorithms to optimize energy management.

Our group has extensive international connections and actively collaborates with research institutions and universities worldwide. This global network of partnerships enables us to be part of the world research community in artificial intelligence and data analytics.
We collaborate with partners in Central and Eastern Europe, including Slovakia and Poland, as well as in Western Europe with colleagues in Germany and France. In North America, we have projects in Canada and the United States. In the Asia-Pacific region, we maintain contacts with research teams in India and South Korea.
On the African continent, we develop projects in partnership with organizations in South Africa and Ethiopia. In South America, we collaborate with colleagues in Chile. In addition to these explicitly mentioned countries, we maintain active contacts with other research centers around the world.
Forms of international collaboration include joint supervision of doctoral students, implementation of international research projects, and publication of scientific articles in prestigious journals. This network of global contacts enables the exchange of experiences, the sharing of the latest knowledge, and the creation of innovative solutions with an international impact.

Projects

• Snášel Václav prof. RNDr., CSc.: Robotika a pokročilá průmyslová výroba, Ministerstvo školství, mládeže a tělovýchovy (2024 - 2028)
• Kudělka Miloš doc. Mgr., Ph.D.: PŘESNĚJŠÍ SUBKLASIFIKACE OSTEOARTRÓZY KOLENA POMOCÍ IMUNOFENOTYPIZACE IMUNITNÍCH BUNĚK, EXOZOMOVÝCH PROFILŮ A LIPIDOMIKY VZORKŮ KLOUBNÍHO VÝPOTKU A SYNOVIÁLNÍ TKÁNĚ, Ministerstvo zdravotnictví (2024 - 2027)
• Snášel Václav prof. RNDr., CSc.: Indo-Pacific-European Hub for Digital Partnerships: Trusted Digital Technologies for Sustainable Well-Being, Evropská unie (2024 - 2027)
• Platoš Jan prof. Ing., Ph.D.: Automatické optimalizace trajektorií lakovacích robotů s ohledem na přenosovou účinnost, homogenitu nástřiku a délku lakovacího cyklu, Technologická agentura (2024 - 2026)
• Nowaková Jana Ing., Ph.D.: Vývoj nástroje pro národní monitoring velkoobchodního trhu s energiemi, Technologická agentura (2023 - 2024)
• Platoš Jan prof. Ing., Ph.D.: Chytrý přístav - digitalizace vodní dopravy v rekreačních přístavech ČR, Technologická agentura (2022 - 2024)
• Krömer Pavel prof. Ing., Ph.D.: Vícekriteriální optimalizace s omezeními pomocí analýzy potenciálních ploch, Grantová agentura ČR (2022 - 2024)
• Kudělka Miloš doc. Mgr., Ph.D.: Odlišení low-grade infekce TEP kyčle a kolena od aseptických komplikací s využitím imunocytologické analýzy a strojového učení, Ministerstvo zdravotnictví (2021 - 2024)
• Kudělka Miloš doc. Mgr., Ph.D.: Chytrá a bezpečná kancelář Smart Office, Ministerstvo průmyslu a obchodu (2021 - 2023)
• Platoš Jan prof. Ing., Ph.D.: Celoživotní strojové učení z datových proudů, Grantová agentura ČR (2021 - 2023)

Publications

• Huynh, B., Tung, N., Nguyen, T., Trinh, C., Snášel, V., Nguyen, L. (2024). New approaches for mining high utility itemsets with multiple utility thresholds, Applied Intelligence, 54, nestránkováno [detail...]
• Svoboda, R., Kotík, V., Platoš, J. (2024). Data-driven multi-step energy consumption forecasting with complex seasonality patterns and exogenous variables: Model accuracy assessment in change point neighborhoods, Applied Soft Computing, 150, nestránkováno [detail...]
• Zjavka, L. (2024). Power Quality Estimations for Unknown Binary Combinations of Electrical Appliances Based on the Step-by-Step increasing Model Complexity, Cybernetics and Systems, 55, 1184-1204 [detail...]
• Kong, L., Barnová, K., Jaroš, R., Mirjalili, S., Snášel, V., Pan, J., Martinek, R. (2024). Analysis on fetal phonocardiography segmentation problem by hybridized classifier, Engineering Applications of Artificial Intelligence, 135, nestránkováno [detail...]
• Sun, Y., Platoš, J. (2024). Abstractive text summarization model combining a hierarchical attention mechanism and multiobjective reinforcement learning, Expert Systems with Applications, 248, nestránkováno [detail...]
• Snášel, V., Velasquez, JD., Pant, M., Georgiou, D., Kong, L. (2024). A generalization of multi-source fusion-based framework to stock selection, Information Fusion, 102, nestránkováno [detail...]
• Snášel, V., Stepnicka, M., Ojha, V., Suganthan, PN., Gao, R., Kong, L. (2024). Large-scale data classification based on the integrated fusion of fuzzy learning and graph neural network, Information Fusion, 102, nestránkováno [detail...]
• Dráždilová, P., Prokop, P., Platoš, J., Snášel, V. (2024). A hierarchical overlapping community detection method based on closed trail distance and maximal cliques, Information sciences, 662, 120271 [detail...]
• Snášel, V., Dang, T., Kueng, J., Kong, L. (2024). A review of in-memory computing for machine learning: architectures, options, International Journal of Web Information Systems, Neuveden, nestránkováno [detail...]

Application results

• Kudělka, M., Anlauf, T., Horák, Z., Kvapil, J., Hutečka, D., Hutečka, F. (2023). SMARTOFFICE platforma, PANCONNECT s.r.o., Pobřežní 249/46, 186 00 Praha SOFTWARE test [detail...]
• Platoš, J., Kalman, M., Baďura, P., Půžová, Z. (2021). Webová aplikace pro analýzu, sdílení a vizualizaci dat epidemiologické studie HBSC pro tvorbu strategií a politik v oblasti zdravého životního stylu, Vysoká škola báňská - Technická univerzita, Fakulta elektrotechniky a informatiky, Katedra informatiky I - INOVACE [detail...]
• Gajdoš, P., Běhálek, M., Kriegová, E., Schneiderová, P. (2019). CLL kalkulátor - aplikace pro vyhodnocení rizik u pacientů s chronickou lymfocytární leukémií, Vysoká škola báňská - Technická univerzita, Fakulta elektrotechniky a informatiky, Katedra informatiky SOFTWARE [detail...]
• Vašinek, M., Novosád, T., Petráčková, A., Kriegová, E. (2019). OLGEN Coverage Limit kalkulátor, Vysoká škola báňská - Technická univerzita, Fakulta elektrotechniky a informatiky, Katedra informatiky SOFTWARE [detail...]
• Radvanský, M., Kudělka, M., Kriegová, E., Gallo, J. (2019). PJI kalkulátor, Vysoká škola báňská - Technická univerzita, Fakulta elektrotechniky a informatiky, Katedra informatiky SOFTWARE [detail...]
• Radvanský, M., Kudělka, M., Kriegová, E., Gallo, J. (2019). Kalkulátor výskytu revize po TEP, Vysoká škola báňská - Technická univerzita, Fakulta elektrotechniky a informatiky, Katedra informatiky SOFTWARE [detail...]

Team

Group leader

prof. RNDr. Václav Snášel, CSc.

Contact person

prof. Ing. Jan Platoš, Ph.D.

Academic staff:

doc. Mgr. Jiří Dvorský, Ph.D., doc. Ing. Petr Gajdoš, Ph.D., prof. Ing. Pavel Krömer, Ph.D., doc. Mgr. Miloš Kudělka, Ph.D., Rizk Masoud Rizkallah Abd, prof. Ing. Petr Musílek, Ph.D., Ing. Jana Nowaková, Ph.D., RNDr. Eliška Ochodková, Ph.D., Maryam Olfati, prof. Ing. Jan Platoš, Ph.D., Ing. Michal Radecký, Ph.D., MBA, prof. RNDr. Václav Snášel, CSc., doc. Mgr. Pavla Dráždilová, Ph.D., Ing. Michal Vašinek, Ph.D.

Scientists:

Ing. Hussam Abdulla, Ph.D., Ing. Tomáš Anlauf, Ing. Markéta Vašinková, Ph.D., Mgr. Ondřej Janča, Lingping Kong, Ing. Vojtěch Kotík, Ing. Kristýna Kubíková, Mgr. Tomáš Novosád, Ph.D., Ing. Lukáš Papík, Ing. Jakub Plesník, Ing. Petr Prokop, RNDr. Ing. Martin Radvanský, Ph.D., Ing. Martin Radvanský, Ing. Radek Svoboda, Ing. Vojtěch Uher, Ph.D., Mgr. Šárka Zehnalová, Ing. Ladislav Zjavka, PhD.

PhD students:

Mgr. Asim Mohammed Eltahir Ali, Zhonghai Bai, Hossein Barghi Jond, Ph.D., Sebastian Basterrech, PhD., Trong Nghia Dinh, MSc., Ing. Vít Doleží, Arootin Gharibian, Hoang Quoc Thi Ha, Ing. Jaroslav Hořejší, Ing. Rostislav Hřivňák, Mgr. Michal Kalman, Ph.D., Ing. Lukáš Klein, Van Vang Le, Tuan Luc Minh, Phien Ngoc Nguyen, Thi Bich Ngan Nguyen, Quang Hung Nguyen, Tan Thuan Nguyen, Ing. Jan Patschka, Nguyen Huy Phuong Pham, Mgr. David Prycl, MPA, Lam Chan Quan Loi, Mgr. Jakub Savara, Ing. Tereza Škutová, Yujia Sun, Ing. Miloslav Szczypka, Trung Tin Tran, Huy Tran Tien, Phi Cuong Trinh, Nhan Trong Nguyen, Xiaopeng Wang

Externalists: