Author

Andrew C. Kowalczewski

Syracuse UniversityORCID 0000-0002-9629-700XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Organism:human· 3 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:development & morphogenesis· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Huaxiao YangiD· 3 shared Zhen MaiD· 3 shared Benjamin D. CosgroveiD· 1 shared Chenyan WangiD· 1 shared Courtney Sakolish· 1 shared Danny VuiD· 1 shared David W. McKellariD· 1 shared Ivan RusyniD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 26 mutual co-author links

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3 shared papersBioengineering

Huaxiao YangORCID

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Author profile →

3 papers

Recent·Most cited

A Generative AI Framework to Predict Cardiomyocyte Contraction Function from Single Static Images.

Andrew C. Kowalczewski, Chenyan Wang, Xinrui Wang, Huaxiao Yang, Zhao Qin A, Zhen Ma

This paper introduces a generative AI framework that predicts cardiomyocyte contraction from static images, achieving high accuracy and revealing structure-function relationships.

Advanced Intelligent Discovery · Sep 30, 2026Peer-reviewedBioengineering

Size-Modulated Mesoderm-Endoderm Divergence and Myocardial Cavitation in Micropatterned Cardioids

Plansky Hoang, David W. McKellar, Andrew C. Kowalczewski, Mai Nhu Y, Meng Chai, Xiaojun Lance Lian, Yi Zheng, Jeffrey D. Amack, Nathan R. Tucker, Iwijn De Vlaminck, Huaxiao Yang, Benjamin D. Cosgrove, Zhen Ma

This study uses micropatterned cardioids to investigate mesoderm-endoderm interactions in heart development, finding that pattern size affects cavity formation and signaling.

Advanced Science · Mar 16, 2026Peer-reviewedBioengineering

A Deep Learning-Based Scoring Framework for Large-Scale Multi-Donor Cardiotoxicity Screening

Danny Vu, Andrew C. Kowalczewski, Sarah D. Burnett, Courtney Sakolish, Xiyuan Liu, Huaxiao Yang, Ivan Rusyn, Zhen Ma

This paper develops a deep learning framework to screen for cardiotoxicity using hiPSC-derived cardiomyocytes, identifying compounds with high toxicity scores and inter-donor variability.

Computational and Structural Biotechnology Journal · Mar 1, 2026Peer-reviewedBioengineering