Jiahui Chen
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor
Also affiliated: Hefei University of Technology (2025); Tianjin Chengjian University (2022); Xiamen University of Technology (2024)
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Jiahui Chen's research program investigates the molecular mechanisms underlying viral infectivity and disease, with a particular focus on SARS-CoV-2 and its variants. Chen has received federal funding from the National Science Foundation (NSF) for projects exploring mathematical and computational frameworks to predict mutation-induced perturbations in molecular recognition, totaling $599,869. Additionally, Chen was awarded $232,771 for research into multiscale differential geometry approaches to protein interaction mechanisms. A recent publication in 2022 addresses the Omicron variant, examining its infectivity, vaccine breakthrough potential, and antibody resistance. Other work has focused on the impact of mutations on SARS-CoV-2 infectivity, the identification of substrains and novel variants in the United States, and the detection of nucleocapsid proteins for diagnosis.
Beyond viral research, Chen's publications also include work on pharmaceutical cocrystals, exploring their preparation, properties, and applications. In 2015, Chen contributed to research on protecting against neuroinflammation and neurodegeneration in an Alzheimer's disease model. Chen's scholarly output includes 6 publications with 12 citations and an h-index of 1. Chen also leads a research group at the University of Arkansas at Fayetteville and collaborates with colleagues such as Fauzia Haque, Soheil Jamali, Emilee Walden, and Jana Shen.
Metrics
- h-index: 1
- Publications: 6
- Citations: 12
Positions
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Assistant Professor publications 2025University of Arkansas at Fayetteville Listing
Selected Publications
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An algebraic graph neural network model for protein-ligand binding affinity prediction (2026)
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Geometry-Induced Hodge Stars on Rips and Dowker--Rips Complexes (2026)arXiv (Cornell University) OpenAlex
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Geometry-Induced Hodge Stars on Rips and Dowker--Rips Complexes (2026)
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BPS2026 – Diffusion models for accelerating molecular dynamics: Synthetic trajectory generation and free-energy reconstruction (2026)
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Dimensionality reduction for k-means clustering of large-scale influenza mutation datasets (2026)
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PLNet : Persistent Laplacian neural network for protein–protein binding free energy prediction (2025)
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Drug Resistance Predictions Based on a Directed Flag Transformer (2025)
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BPS2025 - Free energy calculations using generative models trained based on molecular dynamics trajectories: A diffusion model approach (2025)
Federal Grants 3 $856,640 total
Multiscale Differential Geometry Approaches to Protein Interaction Mechanisms
Collaboration Network
Top Collaborators
- Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation
- Topological deep learning based deep mutational scanning
- Preventing future zoonosis: SARS-CoV-2 mutations enhance human–animal cross-transmission
- PLNet : Persistent Laplacian neural network for protein–protein binding free energy prediction
- Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation
- Preventing future zoonosis: SARS-CoV-2 mutations enhance human–animal cross-transmission
- Drug Resistance Predictions Based on a Directed Flag Transformer
- BPS2025 - Free energy calculations using generative models trained based on molecular dynamics trajectories: A diffusion model approach
- BPS2026 – Diffusion models for accelerating molecular dynamics: Synthetic trajectory generation and free-energy reconstruction
- BPS2025 - Free energy calculations using generative models trained based on molecular dynamics trajectories: A diffusion model approach
- BPS2026 – Diffusion models for accelerating molecular dynamics: Synthetic trajectory generation and free-energy reconstruction
- BPS2025 - Free energy calculations using generative models trained based on molecular dynamics trajectories: A diffusion model approach
- BPS2026 – Diffusion models for accelerating molecular dynamics: Synthetic trajectory generation and free-energy reconstruction
- Drug Resistance Predictions Based on a Directed Flag Transformer
- Dimensionality reduction for k-means clustering of large-scale influenza mutation datasets
- Topological deep learning based deep mutational scanning
- Topological deep learning based deep mutational scanning
- Topological deep learning based deep mutational scanning
- Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation
- Dimensionality reduction for k-means clustering of large-scale influenza mutation datasets
- Drug Resistance Predictions Based on a Directed Flag Transformer
- Drug Resistance Predictions Based on a Directed Flag Transformer
- Drug Resistance Predictions Based on a Directed Flag Transformer
- Drug Resistance Predictions Based on a Directed Flag Transformer
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