About

IRK Lab

The Laboratory of Computational Science and Engineering (IRK) focuses on foundational theories of computation and mathematical modeling, encompassing discrete mathematics as the logical foundation of data structures, linear algebra for high-dimensional data modeling, automata theory for abstract machine models and formal language design, algorithmic strategies for producing optimal and efficient problem-solving solutions, as well as probability and statistics for numerical modeling.

Our Courses

IRK Lab Assistants are responsible for the following courses:

[IF1220] Discrete Mathematics

This course equips you with the tools to analyze fundamental structures like graphs and algorithms. It focuses on counting techniques, logic, and relations, providing a foundation for solving problems in computer science that deal with finite sets of data.

[IF2120] Probability and Statistics

This course provides the mathematical framework for analyzing the performance of algorithms and dealing with uncertainty in computing. You'll learn about probability distributions, statistical analysis, and random processes, which are crucial for understanding the behavior of algorithms in real-world scenarios with inherent randomness.

[IF2123] Geometric and Linear Algebra

This course dives into the mathematics behind computer graphics, image processing, and optimization. You'll learn about vectors, matrices, and geometric transformations, which are essential for manipulating and analyzing spatial data used in various computing applications.

[IF2211] Algorithm Strategies

This course focuses on how to design and analyze algorithms efficiently. You'll learn various problem-solving techniques, analyze the time and space complexity of algorithms, and explore strategies for optimizing their performance.

[IF2224] Formal Language Theory and Automata

This course explores the theoretical underpinnings of languages and how machines process them. By studying formal languages and automata (theoretical machines), you gain the groundwork for understanding compilers, which translate code into machine language, and even artificial intelligence, which deals with computer programs that can understand and generate languages.