Selected work

Representative Papers

Beyond Absolute Positiveness for Universally Quantified Non-Linear Polynomial Constraints

Jun 29, 2026

This work proposes a novel method to overcome the limitations of the classical absolute positivity criterion, which fails to handle nonlinear polynomial constraints involving universal quantifiers. Specifically, the approach addresses ∃∀ inequalities over the natural numbers by integrating monotonic algebra with well-founded order theory, thereby dispensing with the absolute positivity assumption. This advancement substantially broadens the class of constructible nonlinear polynomial interpretations. Experimental results demonstrate that the technique successfully solves constraint instances previously intractable to existing methods, thus extending the applicability of polynomial interpretations in termination and complexity analysis of term rewriting systems.

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Revisiting Gene Ontology Knowledge Discovery with Hierarchical Feature Selection and Virtual Study Group of AI Agents

Mar 20, 2026

This study addresses the challenge of efficiently extracting aging-related biological knowledge from vast Gene Ontology (GO) data. To this end, we propose a novel framework that integrates a multi-agent virtual research team with hierarchical feature selection. The approach leverages large language model–driven agents to collaboratively generate and validate hypotheses, complemented by cross-species bioinformatic analyses to identify high-confidence aging-associated GO terms. By uniquely combining a virtual scientific team architecture with hierarchical feature selection, our method substantially enhances the interpretability and reliability of AI-driven biological discovery. Experimental validation across four model organisms successfully recapitulated numerous aging mechanisms well-supported in the literature, demonstrating the framework’s effectiveness and practical utility.

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Irreducibility of Semigroup Morphisms

Mar 16, 2026

This study addresses the irreducibility of semigroup homomorphisms—specifically, whether a given homomorphism cannot be decomposed into a composition of two nontrivial homomorphisms. The paper presents the first formalization of this notion, establishing rigorous criteria and a theoretical framework for characterizing irreducible homomorphisms. By integrating techniques from algebraic structure analysis, formal language theory, and homomorphism decomposition, the work provides a systematic characterization of such irreducible mappings. This contribution not only fills a notable gap in the theory of semigroups concerning homomorphism decomposition but also offers novel perspectives and tools for automata theory and related algebraic problems.

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Abundance and Economic diversity as a descriptor of cities'economic complexity

Jan 27, 2026

This study investigates the spatial heterogeneity and structural transformation of urban economic complexity and resilience under rapid urbanization. Leveraging a decade of firm-level geospatial data from Mexico City, it pioneers an integration of economic complexity theory with spatial analysis by constructing a three-dimensional indicator system—firm abundance, diversity, and longevity (ADL). Through regression modeling, spatial autocorrelation analysis, time-series clustering, and fitting with power-law and logarithmic saturation models, the research uncovers distinct nonlinear dynamics within the city: central areas exhibit power-law growth, while peripheral zones follow logarithmic saturation trajectories. Notably, firm longevity significantly moderates the relationship between abundance and diversity in peri-urban transition zones. These findings offer novel empirical evidence for polycentric urban restructuring and provide a quantitative foundation for designing inclusive urban policies.

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A practical algorithm for 3-admissibility

Nov 30, 2025

This paper addresses the NP-hard problem of determining whether a given graph (G) has 3-admissibility at most (p). We present the first practical, exact algorithm for this problem, running in linear time and linear space—surpassing prior approaches, which were either purely theoretical constructions or exponential-time methods. Our algorithm leverages graph decomposition and greedy optimization, augmented with optimistic pruning to significantly accelerate computation while preserving correctness. Extensive experiments on large-scale real-world networks demonstrate that the algorithm efficiently handles graphs with up to millions of edges. Moreover, empirical results reveal that, for most real-world networks, the 3-admissibility is only slightly larger than the 2-admissibility, underscoring both the structural relevance of 3-admissibility and the practical efficacy of our approach.

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Recent publications

Latest Papers

Beyond Absolute Positiveness for Universally Quantified Non-Linear Polynomial Constraints

Jun 29, 2026

This work proposes a novel method to overcome the limitations of the classical absolute positivity criterion, which fails to handle nonlinear polynomial constraints involving universal quantifiers. Specifically, the approach addresses ∃∀ inequalities over the natural numbers by integrating monotonic algebra with well-founded order theory, thereby dispensing with the absolute positivity assumption. This advancement substantially broadens the class of constructible nonlinear polynomial interpretations. Experimental results demonstrate that the technique successfully solves constraint instances previously intractable to existing methods, thus extending the applicability of polynomial interpretations in termination and complexity analysis of term rewriting systems.

0 citationsRead paper

Revisiting Gene Ontology Knowledge Discovery with Hierarchical Feature Selection and Virtual Study Group of AI Agents

Mar 20, 2026

This study addresses the challenge of efficiently extracting aging-related biological knowledge from vast Gene Ontology (GO) data. To this end, we propose a novel framework that integrates a multi-agent virtual research team with hierarchical feature selection. The approach leverages large language model–driven agents to collaboratively generate and validate hypotheses, complemented by cross-species bioinformatic analyses to identify high-confidence aging-associated GO terms. By uniquely combining a virtual scientific team architecture with hierarchical feature selection, our method substantially enhances the interpretability and reliability of AI-driven biological discovery. Experimental validation across four model organisms successfully recapitulated numerous aging mechanisms well-supported in the literature, demonstrating the framework’s effectiveness and practical utility.

0 citationsRead paper

Irreducibility of Semigroup Morphisms

Mar 16, 2026

This study addresses the irreducibility of semigroup homomorphisms—specifically, whether a given homomorphism cannot be decomposed into a composition of two nontrivial homomorphisms. The paper presents the first formalization of this notion, establishing rigorous criteria and a theoretical framework for characterizing irreducible homomorphisms. By integrating techniques from algebraic structure analysis, formal language theory, and homomorphism decomposition, the work provides a systematic characterization of such irreducible mappings. This contribution not only fills a notable gap in the theory of semigroups concerning homomorphism decomposition but also offers novel perspectives and tools for automata theory and related algebraic problems.

0 citationsRead paper

Abundance and Economic diversity as a descriptor of cities'economic complexity

Jan 27, 2026

This study investigates the spatial heterogeneity and structural transformation of urban economic complexity and resilience under rapid urbanization. Leveraging a decade of firm-level geospatial data from Mexico City, it pioneers an integration of economic complexity theory with spatial analysis by constructing a three-dimensional indicator system—firm abundance, diversity, and longevity (ADL). Through regression modeling, spatial autocorrelation analysis, time-series clustering, and fitting with power-law and logarithmic saturation models, the research uncovers distinct nonlinear dynamics within the city: central areas exhibit power-law growth, while peripheral zones follow logarithmic saturation trajectories. Notably, firm longevity significantly moderates the relationship between abundance and diversity in peri-urban transition zones. These findings offer novel empirical evidence for polycentric urban restructuring and provide a quantitative foundation for designing inclusive urban policies.

0 citationsRead paper

A practical algorithm for 3-admissibility

Nov 30, 2025

This paper addresses the NP-hard problem of determining whether a given graph (G) has 3-admissibility at most (p). We present the first practical, exact algorithm for this problem, running in linear time and linear space—surpassing prior approaches, which were either purely theoretical constructions or exponential-time methods. Our algorithm leverages graph decomposition and greedy optimization, augmented with optimistic pruning to significantly accelerate computation while preserving correctness. Extensive experiments on large-scale real-world networks demonstrate that the algorithm efficiently handles graphs with up to millions of edges. Moreover, empirical results reveal that, for most real-world networks, the 3-admissibility is only slightly larger than the 2-admissibility, underscoring both the structural relevance of 3-admissibility and the practical efficacy of our approach.

0 citationsRead paper