Presentation of the new rules for the evaluation of academic staff at the Faculty of Informatics

High-Speed and Flexible Packet Processing on FPGA-based SmartNICs

The continuous growth of network traffic and the deployment of 100 Gb, 400 Gb and the evolution towards 800 Gb and terabit-class Ethernet links present significant challenges for network monitoring, security and data centre applications. Traditional CPUs cannot sustain wire-speed packet processing at nanosecond timescales. This talk will focus on hardware acceleration using FPGA-based SmartNICs, which combine high throughput with flexibility. We will discuss time-critical operations such as packet parsing, classification, pattern matching and stateful connection tracking, and present hardware architectures we have designed to address them. Special attention will be given to the balance between performance and flexibility, including the role of P4 programmability compared to the configurability of specialised application profiles. Practical use cases such as DDoS mitigation, security monitoring and AI training will illustrate these approaches, with a concluding outlook on future terabit-scale networks.

Lab Fest, held as part of the Computer Science Colloquium, aims to familiarise the academic community with the activities of research groups at the faculty, specifically their staffing, areas of interest, involvement in grants, and ongoing collaborations at the university, within the Czech Republic and internationally; their future direction and current research and development outcomes.

HCI: Human-Computer Interaction Laboratory

AVELAB: A newly established research group at the Faculty of Informatics

Insights into Entity Component Systems

Entity Component Systems (ECS) are powerful data structures, often used in video games. In this talk, I will explain how this composition pattern works, what an ECS is, what parts it consists of, and the typical operations it offers to its users. I will also explore architectural choices and optimisation strategies tailored to different use cases.

In particular, the talk will cover the following topics:

What Entity Component Systems are;

How large language models (LLMs) can be used to create them;

Different architectural choices and their impact on performance;

How to optimise and parallelise an ECS;

And finally, VECS: The open-source Vienna Entity Component System (+ a tool to visualise its content).

Unpacking the Degree: Hard Truths About Computer Science Education

With nearly 30 years’ experience on the front line as a professional programmer—and half that time spent recruiting and mentoring new graduates—I’ve come to some blunt conclusions about a university degree in Computer Science. Some skills are taught well, others are only superficially addressed, and a few essential abilities are barely mentioned—or simply cannot be taught in a classroom at all. If you believe a degree alone prepares you for life in real-world software development, brace yourself for a challenging perspective.

This lecture will highlight where academic Computer Science excels, and where it falls strikingly short—especially when it comes to preparing graduates for the sprawling complexity of modern enterprise codebases. I’ll argue that no coursework or ‘toy’ project can substitute for industry-honed skills such as Test-Driven Development, and I’ll point out that developing soft skills—such as effective teamwork and clear communication—is just as important as technical expertise. We’ll also explore practical approaches for bridging the gap between university and the realities of professional software teams. Whether you come ready to debate or simply keen to learn, bring your strong opinions or your curiosity—let’s re-examine what Computer Science education truly needs to deliver.

Information Security in Digital Business and Intelligent Systems

Nowadays, digitalisation and intelligent infrastructure are transforming human activities and industrial systems. Disruptive technologies, such as cloud computing, blockchain, AI/ML systems and others, have found applications in various fields, including self-driving vehicles, e-health, innovative urban applications and industrial automation systems. The intensive use of these technologies also generates and manages vast amounts of data and information, which should be used for their intended purposes, made available when needed, and integral to sound decision-making. This means that security must be treated as a top priority in digitalised processes and intelligent infrastructures. This talk will examine the assets and benefits of digitalised systems and intelligent infrastructures. We will discuss their security vulnerabilities, potential harms, risks and countermeasures to mitigate them.

CoFI break

Sampling-based Motion Planning in Robotics: From Theory to Practice

Motion planning aims to compute feasible motions for robots, machines, drones or even virtual characters in games. This talk introduces the fascinating family of stochastic motion planners — sampling-based planners — which search high-dimensional spaces and can solve problems across a wide range of applications, particularly for systems with many degrees of freedom such as robotic manipulators. Yet their performance can deteriorate in surprising ways, such as when navigating tricky ‘narrow passages’. We will show how vague or approximate knowledge about possible solutions, combined with clever tricks, can significantly boost their efficiency.

Symbolic Analysis of Probabilistic Loops without Sampling

Probabilistic loops are control-flow constructs whose execution is influenced by random variable assignments and probability-based conditions. A key challenge in this field is to automatically quantify the uncertainty of such loops, particularly when the number of iterations may be unbounded. Whilst this task is notoriously undecidable in the general case, we have identified a set of practical restrictions that make automated reasoning feasible without the need for manual intervention. Our method uses symbolic computation, combining algebraic techniques with known properties of probability distributions, to compute closed-form solutions for higher-order statistical moments of programme variables across loop iterations. This presentation will demonstrate our approach in action through illustrative case studies.

Shielding for Safe and Fair Sequential Decision Making

In this talk, we will explore methods to enforce formally specified safety and fairness properties at runtime, an approach known as shielded reinforcement learning. Shields rely on a model of the environment’s behaviour to analyse the safety of actions and prevent a learning agent from executing those that could potentially violate a formal safety specification. We will discuss how shields can be computed for environments that exhibit both probabilistic and adversarial behaviour. Furthermore, we will present recent model learning approaches capable of deriving compact probabilistic models for high-dimensional environments, which can then be used to compute shields. Finally, we will show how similar techniques can be applied to ensure group fairness properties, such as demographic parity, at runtime.

Vojtěch Suchánek: Lying to Hardware: Reverse-Engineering ECC on Smartcards

Elliptic Curve Cryptography (ECC) provides strong security with small keys, making it ideal for constrained devices such as smartcards, although such devices remain vulnerable to side-channel attacks. Side-channel attacks often assume a white-box attacker with detailed knowledge of the implementation. In contrast, real-world implementations of ECC are usually a black box. In this talk, we will bridge this gap for the attacker by designing a catalogue of methods capable of reverse-engineering the implementation details required by the attacker. Whilst motivated by cryptographic attacks, our focus will be on the mathematical tricks we employ on hardware in order to extract the hidden information.

Ondřej Sotolář: Computational Social Science

The Interdisciplinary Research Team on Internet and Society (FSS & FI MU, irtis.muni.cz) studies phenomena at the intersection of the social sciences and informatics. This talk introduces the field of computational social science and outlines how modern Natural Language Processing (NLP) methods open up new possibilities for social inquiry. Representation-learning techniques make it possible to test social theories on large-scale textual data, providing computational evidence regarding communication patterns and social behaviour. At the same time, insights from social science can enrich NLP models by grounding them in theories of language use, context and social structure. We will illustrate this reciprocal relationship between NLP and social science through three recent studies from our group, highlighting both methodological advances and substantive findings.

Algorithms for drawing graphs with no or few crossings in the plane, on surfaces, and beyond

Planarity testing – the problem of determining whether an input graph can be drawn without crossings in the plane – has been known to be solvable in linear time since the 1970s. A distinctive feature of this problem is that it lies at the crossroads between topology and algorithms. In this talk, we will survey some natural and recent generalisations: Since some graphs are non-planar, can we draw them without crossings in more general spaces, such as surfaces, or even more general spaces obtained by gluing vertices, edges and triangles together? If a graph cannot be drawn without crossings on a given space, how can it be drawn with as few crossings as possible? How can we untangle a graph drawn with crossings on a surface, if it is possible?

Lab Fest, held as part of the Computer Science Colloquium, aims to familiarise the academic community with the activities of research groups at the faculty, specifically their staffing, areas of interest, involvement in grants, and ongoing collaborations at the university, within the Czech Republic or internationally; their future direction and current research and development outcomes.

DISA: Laboratory of Data Intensive Systems and Applications

Sitola