Cognitive Science Seminar
The Cognitive Science Seminar is a course of MEi:CogSci study programme that is a legacy of original interdisciplinary Cognitive Science and Artificial Intelligence Seminar, which started in 2015. In winter semester the seminar is oriented mostly for the students of cognitive science, to provide insight into the current research in the field of cognitive science by people from FMPI UK and beyond. In summer semester it is a community activity and focuses on current trends in AI and CogSci. The seminar is open, everybody is welcome to attend the offered lectures.
The seminar is organized by Kristína Malinovská.
Time and place: Tuesday 16:30-18:00 in I9 and MS Teams CogSci seminar
Program for winter semester 2026/2027
29.09.2026 - Kristína Malinovská
Department of Applied Informatics, Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava
Field: cognitive robotics
Cognitive robotics and bio-inspired neural networks
Cognitive robotics is an interdisciplinary field that brings together research in machine learning, robotics and bio-inspired artificial intelligence, typically artificial neural networks. It focuses on studying and implementing human cognitive abilities in robots, from simple motor skills, sensing and understanding the world, to developing a sense of their own body, acquiring language and the ability to talk to humans about their surrounding world and work with them on collaborative tasks. In connection with the human-robot interaction field, cognitive modeling represents a way to make robots more considerate and aware of people as well as make their behavior more trustworthy, legible and explainable. In the talk, I will present examples of cognitive robotics’ and HRI research of the cognition and neural computation research group, focusing on sensorimotor interaction and cross-modal learning, language and concepts, acquiring a body schema and building a robotic mirror neuron system for understanding of actions. I will also briefly introduce my research on bio-inspired learning in artificial neural networks.
27.10.2026 - Tomáš Gál
Department of Applied Informatics, Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava
Field: human-computer interaction
Cognitive Biases in Human–AI Interaction
Human–AI interaction might be perceived as if cognitive biases were located either in the human user or in the artificial system, while in practice many relevant effects emerge from the interaction between both sides and from the interface that connects them. This lecture examines bias across four connected levels. First, it introduces human cognitive biases that shape how users interpret and rely on AI outputs, including confirmation bias, anchoring, automation bias, authority effects, and anthropomorphism. Second, it turns to systematic tendencies of AI systems themselves, such as sensitivity to framing, sycophancy, preference for coherent and complete answers, and other recurring patterns that may resemble human biases without sharing the same underlying mechanisms. Third, it considers the role of interface affordances, including conversational fluency, answer-first design, confidence cues, personalization, and other features that influence perceived competence, trust, and scrutiny. Finally, these layers are brought together in the concept of an emergent Human–AI feedback loop, in which human expectations shape prompts and interpretation, model tendencies shape responses, and interface design influences how these patterns are reinforced or corrected over time. The lecture does not treat cognitive bias simply as an error to be eliminated. Instead, it asks which systematic tendencies become unhelpful in a given context, which can support efficient judgment and decision-making, and how Human–AI interaction can be designed and used to reduce maladaptive biases while preserving, exploiting, or even strengthening useful cognitive heuristics and forms of epistemic support.
08.12.2026 - Michal Teplan
Institute of Measurement Science, Slovak Academy of Sciences
Field: psychology
The mental state of flow as a research challenge
The phenomenon of mental Flow, characterized by a sense of energized focus, full immersion, and enjoyment, represents a peak state of human performance and well-being. Emerging in modern times through the pioneering work of Csikszentmihalyi, the scientific quest for understanding Flow’s underlying mechanisms remains a challenging and ongoing endeavor. My personal journey and motivation stem from the conviction that this elusive state can be transformed from a random occurrence into a scientifically monitored and intentionally trained skill. Psychologically, Flow is related to concentration on the task in a challenge-skill balance situation, with the loss of self-consciousness. Physiologically, Flow is associated with higher Heart Rate Variability, indicating parasympathetic activity, and lower galvanic skin response, confirming reduced emotional stress. Neuroscientifically, it involves a decrease in EEG powers over the prefrontal cortex pointing to the reduction of the analytical, self-critical mind. In this seminar, the initial phase of our investigation will be introduced, and hypotheses will be formed. The role of mindfulness meditation training and extensions to spirituality will be explained. Basically, we focus on defining ground truth data by combining subjective psychological scales and expert assessment with objective physiological and biomechanical measurements, aiming to create a robust, measurable Flow Index. We intend to leverage biomechanics (GPS trackers, accelerator sensors, and micro-movement analysis) and data science to seek secondary Flow correlates in quantifiable sport performance metrics. Ultimately, our goal is to develop a comprehensive system for the assessment, monitoring, and training of the Flow state, with utilization of real-time biofeedback, providing athletes, managers, and artists with the tools for achieving lifelong excellence and well-being.