The Faculty of Humanities was created on December 1, 2014. It trains instructors and researchers in the field of language and literature, as well as specialists in philosophy, history, and modern culture.
The main goal of the faculty is to teach students how to understand and analyse various cultural processes, employ current research strategies, and effectively put their knowledge into practice.
The faculty’s staff are leading Russian academics and practitioners from various cultural fields, as well as invited foreign specialists. Students receive a modern education in the humanities, as well as thorough language preparation, which allows them to find extensive professional opportunities upon graduation. Students are given the opportunity to conduct research and gain practical experience at major private and public establishments.
Our strengths:
1. Interdisciplinary approach
We study the humanities alongside other academic fields so that students can apply their skills in various areas.
2. International cooperation
We maintain active international ties, which allows students to undertake internships and study abroad, as well as broaden their outlook and cultural experiences.
3. Research
We encourage and support student participation in research projects. This gives them an opportunity to apply their knowledge in practice and make a contribution to the development of the humanities.
Our graduates pursue careers in public and commercial organisations and various types of mass media. They also implement their own media, cultural, social, and educational projects.
Publications
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Book
Problem Solving in Philosophy. How to Do Philosophy in the Age of Ultra-Intelligent AI
This open access book provides a method for philosophical problem solving, offering philosophers the tools to stay ahead of machine intelligence. Louis Vervoort argues that, with ultra-intelligent AI knocking at the door, philosophy can no longer rely solely on its ancient methodological toolkit. The proposed method is essentially the same as used in natural science, theoretical physics in particular, and aims at solving problems through theory-synthesis. The author shows by first case studies that current AI can already assist us in this task – a trend that will surely strengthen in the near future. After explaining the method in detail, the book proceeds by proposing unified solutions to classic problems of (analytic) philosophy, such as Gettier’s problem, the problem of induction, of causation, of the interpretation of probability, of free will. The author argues that these solutions maximise a quantitative measure of solidity, and that philosophy can now reach standards of certainty that are comparable to those of natural science. The book is written for professional philosophers, but avoids jargon, so it should also be accessible to laypeople and scientists.
Springer, 2026.
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Article
Avant-Garde Poetry and the Tékhnē of Traditional Versification
This article offers a theoretically nuanced and empirically grounded investigation into the paradoxical afterlife of classical versification within the poetic practices of the Russian and Soviet avant-garde. Challenging the persistent historiographic narrative that equates avant-garde poetics with an unequivocal rupture from tradition, the study demonstrates that canonical metrical forms—most notably iambic tetrameter—continued to operate as structurally productive, albeit critically reconfigured, elements within experimental verse. Drawing on a broad corpus encompassing poetic manifestos, verse texts, and prose writings by Vladimir Maiakovskii, Ilia Sel’vinskii, Semen Kirsanov, and Nikolai Aseev, the authors combine close formal analysis with quantitative prosodic modeling, including linguistic and speech models derived from Kolmogorov–Taranovsky verse theory. The article argues that avant-garde poets did not simply negate inherited metrics but subjected them to a process of internal recomposition, shifting attention from meter as a fixed scheme to rhythm as a dynamic, semantically charged construct. While rhythmic innovation is shown to be consciously engineered in verse, the analysis of verse-like fragments in prose reveals persistent, unconscious attachments to “classical” rhythmic patterns, particularly the Pushkinian alternating rhythm. This tension between declarative rejection and latent continuity illuminates the avant-garde’s distinctive mode of negotiating tradition: not abolishing it, but instrumentalizing it within a broader project of total artistic reorganization. The study thus reframes avant-garde prosody as a site where innovation and inheritance coexist in a state of productive contradiction, reshaping our understanding of modernist poetic technique.
Arts. 2026. Vol. 15(5). No. 97. P. 1-24.
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Book chapter
Ancient Greek Polis: From Homoarchy to Heterarchy and Back Again
The chapter considers the historical development of the Ancient Greek city-state (polis) viewed through the categories of homoarchy and heterarchy basic for the present monography. The author traces its formation on the base of the homoarchical society of the Dark Ages, the peculiarities of its heterarchical structure, the background of its crise in the 4th century B.C.
In bk.: Principles and Forms of Sociocultural Organization: Historical Contexts of Interaction. L.; NY: Anthem Press, 2026. Ch. 2. P. 33-52.
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Working paper
An Annotation Scheme and Classifier for Personal Facts in Dialogue
The advancement of Large Language Models (LLMs) has enabled their application in personalized dialogue systems. We present an extended annotation scheme for personal fact classification that addresses limitations in existing approaches, particularly PeaCoK. Our scheme introduces new categories (Demographics, Possessions) and attributes (Duration, Validity, Followup) that enable structured storage, quality filtering, and identification of facts suitable for dialogue continuation. We manually annotated 2,779 facts from Multi-Session Chat and trained a multi-head classifier based on transformer encoders. Combined with the Gemma-300M encoder, the classifier achieves 81.6±2.6\% macro F1, outperforming all few-shot LLM baselines (best: GPT-5.4-mini, 72.92\%) by nearly 9 percentage points while requiring substantially fewer computational resources. Error analysis reveals persistent challenges in semantic boundary disambiguation, temporal aspect interpretation, and pragmatic reasoning for followup assessment. The dataset\footnotemark[1] and classifier\footnotemark[2] are publicly available.arxiv.org. Computer Science. Cornell University, 2026