H. W. Hays Source Confirmed
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Postdoctoral Research Associate
University of Arkansas at Fayetteville
postdoc
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Biography and Research Information
OverviewAI-generated summary
H. W. Hays researches computational network modeling, focusing on the application of graph neural networks and hierarchical molecular language models (HMLMs) to biological systems. This work aims to advance precision medicine by integrating computer science with biophysics, nonlinear dynamics, and biomathematical modeling. Hays investigates cellular signaling networks, predicting context-dependent biological responses across multiple scales using transformer architectures and graph-structured attention mechanisms.
Further research involves network medicine, where attention-based insights are used to identify critical regulatory nodes, pathway crosstalk, and potential therapeutic targets. Additionally, Hays explores the use of quantum computing and quantum circuits to optimize signaling network parameters, aiming for superior global optimization compared to classical computational methods. This interdisciplinary approach leverages novel computational algorithms, ordinary differential equations (ODEs), and nonlinear dynamics to analyze complex biological networks.
Metrics
- h-index: 12
- Publications: 34
- Citations: 321
Selected Publications
- Encyclopedia of Large Language Models and Foundation Models (2026) DOI
- Encyclopedia of Large Language Models and Foundation Models (2026) DOI
- Hierarchical Molecular Language Models (HMLMs). (2025)
- Transcriptome-based nutrigenomics analysis reveals the roles of dietary taurine in the muscle growth of juvenile turbot (Scophthalmus maximus) (2023) DOI
- Synergistic effects of dietary taurine and carbohydrates supplementation on skeleton muscle of juvenile turbot <i>Scophthalmus maximus</i> (2023) DOI
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