About

Juan Uriagereka is a Professor in the Department of Linguistics at the University of Maryland, affiliated with the School of Languages, Literatures, and Cultures. Since joining the university in 1989, he has published a dozen books and numerous articles and chapters, contributing significantly to the field of syntax and generative grammar. Uriagereka has (co-)directed 19 dissertations, is co-directing three others, and has participated in the graduate committees of approximately seventy students. His research expertise centers on syntax, with a focus on the organization of natural and linguistic phenomena, the structure of language, and the principles underlying language formation. His recent work includes the monograph 'Structure,' co-authored with Howard Lasnik, which explores language structures as linear operators, and a forthcoming book on code-switching co-authored with Jeff MacSwan. Uriagereka's scholarly activities extend to outreach efforts, including writing for Musica Aperta and co-founding Imagining Reality Insights & Solutions to address literacy and educational issues. His contributions to academia also include leadership roles, such as serving as Associate Provost for Faculty, where he implemented family-friendly policies, regularized the status of professional-track faculty, organized leadership forums, and updated academic policies.

Research topics

• Computer Science
• Artificial Intelligence
• Linguistics
• Philosophy
• Genetics
• Physics
• Evolutionary biology
• Computational biology
• Pure mathematics
• Cognitive science
• Epistemology
• Psychology
• Mathematics
• Biology

Selected publications

• Merge (Including Derivational Workspaces)

  Elsevier eBooks · 2026-01-01

  book-chapter1st authorCorresponding
  PublisherDOI

• Toward an Algebraic Implementation of a Language Faculty

  Communications in computer and information science · 2026-01-01

  book-chapter1st authorCorresponding
  PublisherDOI

• Still a Bridge Too Far?

  2026-01-07

  book-chapterSenior author

  In this paper we discuss how Fibonacci growth patterns are apparent in the structure of human language. We moreover show how familiar dynamics yielding these sorts of patterns in nature may be taken to apply, at some level of abstraction, for the human faculty of language. The overall picture casts doubts on any simplistic treatment of language behavior, of the sort stemming from classical behaviorism in psychology (which is again popular in contemporary computational models). Instead, it appears to be more profitable to study language as a complex dynamic system, emerging in human brains for physical reasons which are yet to be fully comprehended, but which in the end disfavor any dualistic approach to the study of mind in general, and the human mind in particular.

  PublisherDOI

• Real and Presumed Categories: A Formal Approach

  Anuario del Seminario de Filología Vasca Julio de Urquijo · 2025-01-29

  articleOpen access1st authorCorresponding

  Categorization is fundamental to any scientific pursuit, posing the question of what categories themselves amount to. Are categories absolute or mere linguistic constructs? If the latter, are they to be trusted? Otherwise, what can one use to ground categories? The present piece reminds us that one can go about this substantively or formally. Substantive, for beings with a neuro-physiological nature, boils down to how we happen to be “wired” or how our brain “works”, whatever that means. Formal ought to be grounded on some abstract system, of the sort that logic and arithmetic represent — given “the unreasonable effectiveness of mathematics”. In this context, I consider whether primitive linguistic (distinctive) features are substantive or formal. In the end, I suggest that this depends on the nature of the feature, and that in some fundamental sense there is ample space for foundational formal features, which has a variety of technical and philosophical consequences worth pursuing.

  PublisherOA PDFDOI

• Craving the ROSE and grasping the thorn

  Cognitive Neuroscience · 2025-09-18 · 1 citations

  article1st authorCorresponding
  PublisherDOI

• Weak & Strong Emergence in Language & Mind

  Revista Internacional de los Estudios Vascos · 2025-12-31

  articleOpen access1st authorCorresponding

  Despite continuous sensory flows, animal behavior shows discrete actions. This discontinuity requires a weak emergence: spectral channels shaped by biophysical constants leading to categorical motor decisions. But the compositional, inferential, and counterfactual capacities of bilaterians demand a stronger emergence, as afforded in non-commutative representational spaces. This framework connects linear algebra and oscillatory binding for an evolutionary trajectory from sensation to thought.

  PublisherDOI

• The genomic domestication landscape is orchestrated by transcription factors regulating brain and craniofacial development

  Research Square · 2023-03-06

  preprintOpen access

  Abstract Domestication transforms once wild animals into tamed animals that can be then exploited by humans. The process entails modifications in the body, cognition, and behavior that are essentially driven by differences in gene expression patterns. Although genetic and epigenetic mechanisms were shown to underlie such differences, less is known about the role exerted by trans-regulatory molecules, notably transcription factors (TFs) in domestication. In this paper, we conducted extensive in silico analyses aimed to clarify the TF landscape of mammal domestication. We first searched the literature, so as to establish a large list of genes selected with domestication in mammals. From this list, we selected genes experimentally demonstrated to exhibit TF functions. We also considered TFs TFs displaying a statistically significant number of targets among the entire list of (domestication) selected genes. This workflow allowed us to identify 5 candidate TFs (SOX2, KLF4, MITF, NR3C1, NR3C2) that were further assessed in terms of biochemical and functional properties. We found that such TFs-of-interest related to mammal domestication are all significantly involved in the development of the brain and the cranio-facial skull, as well as the immune response and lipid metabolism. A ranking strategy, essentially based on a survey of protein-protein interactions datasets, allowed us to identify SOX2 as the main candidate TF involved in domestication-associated evolutionary changes. These findings should help to clarify the molecular mechanics of domestication and are of interest for future studies aimed to understand the behavioral and cognitive changes associated to domestication.

  PublisherOA PDFDOI

• The genomic landscape of mammal domestication might be orchestrated by selected transcription factors regulating brain and craniofacial development

  Development Genes and Evolution · 2023 · 2 citations

  • Biology
  • Evolutionary biology
  • Genetics

  Domestication transforms once wild animals into tamed animals that can be then exploited by humans. The process entails modifications in the body, cognition, and behavior that are essentially driven by differences in gene expression patterns. Although genetic and epigenetic mechanisms were shown to underlie such differences, less is known about the role exerted by trans-regulatory molecules, notably transcription factors (TFs) in domestication. In this paper, we conducted extensive in silico analyses aimed to clarify the TF landscape of mammal domestication. We first searched the literature, so as to establish a large list of genes selected with domestication in mammals. From this list, we selected genes experimentally demonstrated to exhibit TF functions. We also considered TFs displaying a statistically significant number of targets among the entire list of (domestication) selected genes. This workflow allowed us to identify 5 candidate TFs (SOX2, KLF4, MITF, NR3C1, NR3C2) that were further assessed in terms of biochemical and functional properties. We found that such TFs-of-interest related to mammal domestication are all significantly involved in the development of the brain and the craniofacial region, as well as the immune response and lipid metabolism. A ranking strategy, essentially based on a survey of protein-protein interactions datasets, allowed us to identify SOX2 as the main candidate TF involved in domestication-associated evolutionary changes. These findings should help to clarify the molecular mechanics of domestication and are of interest for future studies aimed to understand the behavioral and cognitive changes associated to domestication.

  PublisherOA PDFDOI

• Correlated attributes: Toward a labeling algorithm of complementary categorial features

  Frontiers in Language Sciences · 2023-02-21 · 1 citations

  articleOpen access1st authorCorresponding

  Classical syntactic features are revisited from an algebraic perspective, recalling a traditional argument that the ± N vs. ± V distinction involves correlated, conceptually orthogonal, features, which can be represented in the algebraic format of ± 1 vs. ± i complementary elements in a vectorial space. Coupled with natural assumptions about shared information (semiotic) systems, such a space, when presumed within a labeling algorithm, allows us to deduce fundamental properties of the syntax that do not follow from the presumed computation, like core selectional restrictions for lexical categories or their very presupposition in the context of a system of grammatical categories. This article suggests how that fundamental distinction can be coupled with neurophysiological realities, some of which (represented as mathematically real) can be pinpointed into punctual representations, while others (represented as mathematically complex) are, instead, fundamentally distributed. The postulated matrix mechanics amounts to a novel perspective on how to analyze syntactic neurophysiological signals.

  PublisherOA PDFDOI

• Structure

  The MIT Press eBooks · 2022 · 8 citations

  Senior authorCorresponding
  • Computer Science
  • Artificial Intelligence
  • Computer Science

  Natural phenomena, including human language, are not just series of events but are organized quasi-periodically; sentences have structure, and that structure matters. Howard Lasnik and Juan Uriagereka “were there” when generative grammar was being developed into the Minimalist Program. In this presentation of the universal aspects of human language as a cognitive phenomenon, they rationally reconstruct syntactic structure. In the process, they touch upon structure dependency and its consequences for learnability, nuanced arguments (including global ones) for structure presupposed in standard linguistic analyses, and a formalism to capture long-range correlations. For practitioners, the authors assess whether “all we need is Merge,” while for outsiders, they summarize what needs to be covered when attempting to have structure “emerge.” Reconstructing the essential history of what is at stake when arguing for sentence scaffolding, the authors cover a range of larger issues, from the traditional computational notion of structure (the strong generative capacity of a system) and how far down into words it reaches to whether its variants, as evident across the world's languages, can arise from non-generative systems. While their perspective stems from Noam Chomsky's work, it does so critically, separating rhetoric from results. They consider what they do to be empirical, with the formalism being only a tool to guide their research (of course, they want sharp tools that can be falsified and have predictive power). Reaching out to skeptics, they invite potential collaborations that could arise from mutual examination of one another's work, as they attempt to establish a dialogue beyond generative grammar.

  PublisherOA PDFDOI

Frequent coauthors

• Serge Nataf

  Université Claude Bernard Lyon 1

  19 shared

• Antonio Benítez‐Burraco

  Universidad de Sevilla

  12 shared

• Howard Lasnik

  10 shared

• Massimo Piattelli‐Palmarini

  University of Arizona

  9 shared

• Román Orús

  8 shared

• Víctor Manuel Longa Martínez

  Universidade de Santiago de Compostela

  8 shared

• Guillermo Lorenzo

  Universidad de Oviedo

  7 shared

• Ángel J. Gallego

  5 shared

Labs

• CLIPPI