Matthew J. Patitz Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Federal Grant PI High Impact

Associate Professor

University of Arkansas at Fayetteville

faculty

22 h-index 139 pubs 1,570 cited

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Biography and Research Information

OverviewAI-generated summary

Matthew J. Patitz's research centers on the principles and applications of algorithmic self-assembly, particularly within the abstract Tile Assembly Model. His work investigates how hierarchical self-assembly can reduce program-size complexity and explores the capabilities and limitations of geometric hindrance in self-assembly processes. Patitz has published on topics including self-replication via tile self-assembly, the strict self-assembly of discrete self-similar fractals, and the assembly of patterns in abstract tile systems.

His research also examines the influence of dimensionality, diffusion, and directedness on intrinsic cross-model simulation in tile-based self-assembly. Patitz has received federal funding for his investigations into algorithmic self-assembly, including a significant grant from the National Science Foundation (NSF) for collaborative research on "Algorithmic Self-Assembly with Crisscross Slats." He leads a research group at the University of Arkansas at Fayetteville and collaborates with colleagues including Daniel Hader, Andrew Alseth, Phillip Drake, and Tyler Tracy, with whom he has co-authored multiple publications.

Patitz's scholarly contributions are reflected in his h-index of 22 and over 1,570 total citations across his more than 130 publications. He is recognized as a high-impact, highly cited researcher and a principal investigator on federal grants.

Metrics

  • h-index: 22
  • Publications: 139
  • Citations: 1,570

Selected Publications

  • Simulation of the abstract Tile Assembly Model using crisscross slats (extended version) (2026) DOI
  • Synchronous Versus Asynchronous Tile-Based Self-Assembly (2025) DOI
  • Self-assembly of patterns in the abstract tile assembly model (2025) DOI
  • Simulation of programmable matter systems using active tile-based self-assembly (2025) DOI
  • Self-assembly of Patterns in the Abstract Tile Assembly Model (2024) DOI
  • Simulation of the Abstract Tile Assembly Model Using Crisscross Slats (2024) DOI
  • Universal shape replication via self-assembly with signal-passing tiles (2024) DOI
  • Self-replication via tile self-assembly (2024) DOI
  • The Impacts of Dimensionality, Diffusion, and Directedness on Intrinsic Cross-Model Simulation in Tile-Based Self-Assembly (2024) DOI
  • The Impacts of Dimensionality, Diffusion, and Directedness on Intrinsic Cross-Model Simulation in Tile-Based Self-Assembly (2023) DOI
  • The Need for Seed (in the Abstract Tile Assembly Model) (2023) DOI
  • Implementing a Theoretician’s Toolkit for Self-Assembly with DNA Components (2023) DOI
  • The Impacts of Dimensionality, Diffusion, and Directedness on Intrinsic Cross-Model Simulation in Tile-Based Self-Assembly (2023) DOI
  • Fractal dimension of assemblies in the abstract tile assembly model (2023) DOI
  • The Need for Seed (in the abstract Tile Assembly Model) (2023) DOI

Federal Grants 1 $533,690 total

NSF PI

Collaborative Research: FET: Small: Algorithmic Self-Assembly with Crisscross Slats

FET-Fndtns of Emerging Tech, EPSCoR Co-Funding $533,690

Collaborators

Researchers in the database who share publications