Ing. Jurij Ružejnikov
Ph.D student
Biography
Publication list
Ing. Jurij Ruzheinikau
Contact Information
Phone: +420 777 772 243
Email: ruzheinikau@email.cz
LinkedIn: Jurij Ružejnikov
Employment History
Institute of Information Theory and Automation – Department of Adaptive Systems
Location: Prague, Czech Republic
Length of employment: July 2024 – Present
Position: Ph.D. student
Key responsibilities:
• PhD thesis on the topic of Adaptive dynamic AI focused on humans.
CZU Faculty of Economics and Management – Department of Information Engineering
Location: Prague, Czech Republic
Length of employment: April 2024 – September 2024
Position: Technical worker
Key responsibilities:
• Administrative position in the department’s secretariat.
UniCredit Bank Czech Republic and Slovakia, a.s.
Location: Prague, Czech Republic
Length of employment: September 2022 – May 2024
Position: Market Risk Specialist
Key responsibilities:
• Development of a statistical model for predicting early mortgage repayment.
• Development of a statistical model for forecasting current account balances.
• Implementation of the models.
• Development of documentation for the models.
• Communication with the validation team.
• Communication with the Group’s Holding regarding model development.
Institute of Information Theory and Automation – Department of Adaptive Systems
Location: Prague, Czech Republic
Length of employment: October 2019 – February 2024
Projects and Responsibilities:
Bachelor Thesis
Bayesian estimation for adaptive dynamic decision-making (link)
• Problem formulation for real-time bidding in online advertisement.
• Algorithm development and implementation in Matlab.
• Experimental evaluation of the solution quality.
Research Assignment
Probabilistic Modeling of Opinion Formation
• Studied probabilistic merging of opinions.
• Collected and processed user data on mobile phone preferences.
• Applied theory to a real-world example.
Master’s Thesis
Targeted merging of customers’ opinions based on trust (link)
• Enhanced understanding of opinion merging and trust.
• Extended earlier research by incorporating subjective trust levels.
• Developed and tested a Matlab algorithm on simulated data.
Education
Czech Technical University in Prague – Faculty of Nuclear Sciences and Physical Engineering
Location: Prague, Czech Republic
Bachelor’s Degree
Applied Mathematical Stochastic Methods (link)
• Thesis: Bayesian estimation for adaptive dynamic decision-making (link)
Master’s Degree
Applied Mathematical Stochastic Methods (link)
• Thesis: Targeted merging of customers’ opinions based on trust (link)
Research Interests
Bayesian Statistics, Decision Theory, Time Series Analysis, Machine Learning
Computer Skills
Programming Languages:
• R (expert)
• Python (intermediate)
• Matlab (intermediate)
• C++ (basic knowledge)
Applications:
LaTeX, Visual Studio Code, Microsoft Excel, Microsoft Word
Operating Systems:
Linux, Windows, Mac
Language Knowledge
• English: C1
• Russian: Native speaker
• Czech: Native speaker
Other publications
- : Targeted Trust-Based Merging of Customers’ Opinions, Artificial Neural Networks and Machine Learning – ICANN 2025, p. 351-365, Eds: Ružejnikov Jurij, Guy Tatiana Valentine Download DOI: 10.1007/978-3-032-04555-3_29 [2025]
- : MDP-Based Analysis of Agent Interactions: From Collaborative to Adversarial Dynamics, 2025 DYNALIFE Conference on QUANTUM INFORMATION AND DECISION MAKING IN LIFE SCIENCES PROGRAMME and ABSTRACTS Download [2025]
- : Adapting Value Iteration with Adversarial Risk Analysis for Secure Reinforcement Learning, DYNALIFE : Theoretical Biology Meets Big Data: Dynamical Systems, Machine Learning, and Applications in Life Sciences Download [2025]
- : 2025 DYNALIFE Conference on QUANTUM INFORMATION AND DECISION MAKING IN LIFE SCIENCES PROGRAMME and ABSTRACTS, Czech University of Life Sciences Prague (Prague, 2025) Download DOI: https://doi.org/10.5281/zenodo.15854639 [2025]