Research projects

  • CYBERTHRETS (OYCESNET20221, Use of artificial intelligence for defence against cyber security attacks)

  • Smart ADS (TH04010073, cooperation with Flowmon Networks supported by Technology Agency (TAČR))

  • Flow based Encrypted Traffic Analysis (VJ02010024, security research challenge IMPAKT 1, Ministry of Interior Czech Republic)

  • Grant Agency of the CTU in Prague, grant No. SGS20/210/OHK3/3T/18 funded by the MEYS of the Czech Republic.

Conference organizing

  • Poster Co-Chair at 20th International Conference on Network and Service Management (CNSM) 2024 LINK

  • Member of Session Committee of PhD Workshop at 20th International Conference on Network and Service Management (CNSM) 2024 LINK

  • Student Poster Session Co-Chair at The 12th Prague Embedded Systems Workshop (PESW) 2024 LINK

Teaching

BI-PSI

Students understand the basic common techniques, protocols, technologies, and algorithms necessary to communicate in computer networks focusing primarily the 2nd to 4th layer of the ISO OSI model. They also get a basic understanding of communication media, security, and network administration. Students will be able to write a simple network application and configure a simple network.

BI-TPS

The course introduces students with basic and advanced technologies, components, and interfaces of contemporary computer networks at the physical layer with the overlap to the link layer. The lectures provide theoretical foundations of these technologies and explain relevant physical principles. In the labs, the respective technologies will be demonstrated and with the most important ones students will get hands-on experience. Thematically, the course covers both local and long-range optical networks, Ethernet, modern wireless networks, always with focus on high-speed networks.

Fundamentals of the Python programming language

  • The essentials about the philosophy and history of the Python language.
  • The environment: command line, scripts, Jupyter notebooks or virtual environment.
  • The syntax of the Python programming language.
  • The data and control structures in Python.
  • The Python standard library.
  • Working with files (binary, csv, json, yaml…).
  • Scripting with the Python language.

Basic Data Science

  • The theoretical minimum of data analysis and science.
  • The libraries suitable for data science - Pandas, Numpy and others.
  • Statistical analysis and data visualization.
  • Machine learning - from data preprocessing to basic classification using machine learning algorithms to applying machine learning to a real problem.
  • Deep learning and basic classification using deep learning algorithms.
  • Theoretical foundations of time series analysis and the know-how for their analysis and evaluation.