HSE Researchers Develop Python Library for Analysing Eye Movements
A research team at HSE University has developed EyeFeatures, a Python library for analysing and modelling eye movement data. This tool is designed to simplify the work of scientists and developers by enabling them to efficiently process complex data and create predictive models.
The project was implemented as part of the Strategic Project 'Human-Centred AI' (Priority 2030).
Modern research increasingly leverages machine learning and artificial intelligence to analyse vast amounts of eye movement data. However, despite significant advancements in this field, certain challenges continue to limit the effectiveness of these methods. One such challenge is the limited flexibility of existing software solutions, which often offer a narrow range of parameter settings, making it difficult to customize them for specific research tasks. Additionally, the integration of these tools with other specialised software remains a significant limitation.
The Python library EyeFeatures, developed by the Laboratory for Social and Cognitive Informatics at HSE Campus in St Petersburg, addresses these challenges by providing a versatile and user-friendly toolkit for working with eye movement data. It includes modules for processing and analysing data collected from eye trackers, devices that monitor eye movement during the performance of various tasks.
Processing eye movement data is a complex task that involves several stages. Since the eyes do not move smoothly but rather in a series of rapid, jerky motions, focusing on specific points, the first stage of data processing is identifying areas of fixation. In the second stage, metrics such as the average gaze fixation duration and the average distance between points are calculated, enabling the creation of initial, simple predictive or diagnostic models.
All stages of data processing can be carried out using the various modules of the EyeFeatures library. The flexible, modular approach makes it easy to integrate eye movement data processing into existing research and commercial projects, from raw data to a fully developed predictive or explanatory model. For example, using the library in marketing research allows for the evaluation of consumer reactions to advertisements. Eye movement analysis will reveal which elements capture the most attention from the audience.
According to Anton Surkov, Project Head, Junior Research Fellow at Laboratory for Social and Cognitive Informatics at HSE Campus in St Petersburg, 'The library can be valuable to researchers, as it enables them not simply to replicate existing functionality from other software but to implement new algorithms and create more advanced models for research in fields such as marketing, cognitive process diagnostics, user interface and neural interface development (where control and interaction with the program occur through eye movement), as well as combine components in innovative ways to achieve new results and enhance methodology.'
This solution streamlines data analysis and accelerates the creation of predictive models, which is particularly beneficial in medical diagnostics, marketing, and the study of cognitive processes. The library has already been applied in research conducted as part of the Strategic Project 'Human-Centred AI' and was presented at the ECEM 2024 international conference in Ireland.
See also:
'Our Goal Is Not to Determine Which Version Is Correct but to Explore the Variability'
The International Linguistic Convergence Laboratory at the HSE Faculty of Humanities studies the processes of convergence among languages spoken in regions with mixed, multiethnic populations. Research conducted by linguists at HSE University contributes to understanding the history of language development and explores how languages are perceived and used in multilingual environments. George Moroz, head of the laboratory, shares more details in an interview with the HSE News Service.
Slim vs Fat: Overweight Russians Earn Less
Overweight Russians tend to earn significantly less than their slimmer counterparts, with a 10% increase in body mass index (BMI) associated with a 9% decrease in wages. These are the findings made by Anastasiia Deeva, lecturer at the HSE Faculty of Economic Sciences and intern researcher in Laboratory of Economic Research in Public Sector. The article has been published in Voprosy Statistiki.
Scientists Reveal Cognitive Mechanisms Involved in Bipolar Disorder
An international team of researchers including scientists from HSE University has experimentally demonstrated that individuals with bipolar disorder tend to perceive the world as more volatile than it actually is, which often leads them to make irrational decisions. The scientists suggest that their findings could lead to the development of more accurate methods for diagnosing and treating bipolar disorder in the future. The article has been published in Translational Psychiatry.
Scientists Develop AI Tool for Designing Novel Materials
An international team of scientists, including researchers from HSE University, has developed a new generative model called the Wyckoff Transformer (WyFormer) for creating symmetrical crystal structures. The neural network will make it possible to design materials with specified properties for use in semiconductors, solar panels, medical devices, and other high-tech applications. The scientists will present their work at ICML, a leading international conference on machine learning, on July 15 in Vancouver. A preprint of the paper is available on arxiv.org, with the code and data released under an open-source license.
‘Economic Growth Without the AI Factor Is No Longer Possible’
The International Summer Institute on AI in Education has opened in Shanghai. The event is organised by the HSE Institute of Education in partnership with East China Normal University (ECNU). More than 50 participants and key speakers from over ten countries across Asia, Europe, North and South America have gathered to discuss the use of AI technologies in education and beyond.
HSE Linguists Study How Bilinguals Use Phrases with Numerals in Russian
Researchers at HSE University analysed over 4,000 examples of Russian spoken by bilinguals for whom Russian is a second language, collected from seven regions of Russia. They found that most non-standard numeral constructions are influenced not only by the speakers’ native languages but also by how frequently these expressions occur in everyday speech. For example, common phrases like 'two hours' or 'five kilometres’ almost always match the standard literary form, while less familiar expressions—especially those involving the numerals two to four or collective forms like dvoe and troe (used for referring to people)—often differ from the norm. The study has been published in Journal of Bilingualism.
Overcoming Baby Duck Syndrome: How Repeated Use Improves Acceptance of Interface Updates
Users often prefer older versions of interfaces due to a cognitive bias known as the baby duck syndrome, where their first experience with an interface becomes the benchmark against which all future updates are judged. However, an experiment conducted by researchers from HSE University produced an encouraging result: simply re-exposing users to the updated interface reduced the bias and improved their overall perception of the new version. The study has been published in Cognitive Processing.
Mathematicians from HSE Campus in Nizhny Novgorod Prove Existence of Robust Chaos in Complex Systems
Researchers from the International Laboratory of Dynamical Systems and Applications at the HSE Campus in Nizhny Novgorod have developed a theory that enables a mathematical proof of robust chaotic dynamics in networks of interacting elements. This research opens up new possibilities for exploring complex dynamical processes in neuroscience, biology, medicine, chemistry, optics, and other fields. The study findings have been accepted for publication in Physical Review Letters, a leading international journal. The findings are available on arXiv.org.
Mathematicians from HSE University–Nizhny Novgorod Solve 57-Year-Old Problem
In 1968, American mathematician Paul Chernoff proposed a theorem that allows for the approximate calculation of operator semigroups, complex but useful mathematical constructions that describe how the states of multiparticle systems change over time. The method is based on a sequence of approximations—steps which make the result increasingly accurate. But until now it was unclear how quickly these steps lead to the result and what exactly influences this speed. This problem has been fully solved for the first time by mathematicians Oleg Galkin and Ivan Remizov from the Nizhny Novgorod campus of HSE University. Their work paves the way for more reliable calculations in various fields of science. The results were published in the Israel Journal of Mathematics (Q1).
Recommender Systems: New Algorithms and Current Practices
The AI and Digital Science Institute at the HSE Faculty of Computer Science hosted a conference focused on cutting-edge recommender system technologies. In an atmosphere of active knowledge sharing among leading industry experts, participants were introduced to the latest advancements and practical solutions in recommender model development.