Hong Qin, Ph.D. School of Data Science & Department of Computer Science, Old Dominion University

Publications

Selected Recent Journal Publications

  1. Hatami, P., R. Annan, L.U. Miranda, J. Gorman, M. Xie, L. Qingge, and H. Qin. “Explainable Convolutional Neural Network Model Provides an Alternative Genome-Wide Association Perspective on Mutations in SARS-CoV-2.” Scientific Reports, 2025 (in review).
  2. Pantho, M.J., L.A. Bauder, S. Huang, and H. Qin. “A Data-Driven Sliding-Window Pairwise Comparative Approach for the Estimation of Transmission Fitness of SARS-CoV-2 Variants and Construction of the Evolution Fitness Landscape.” Quantitative Biology, 13:e70003, 2025.
  3. Chauhan, S., R. Cheruku, D.R. Edla, et al. and H. Qin. “BT-CNN: A Balanced Binary Tree Architecture for Classification of Brain Tumour Using MRI Imaging.” Frontiers in Physiology, 15:1349111, 2024.
  4. Dash, S., S.K. Giri, S. Mallik, et al. and H. Qin. “Predictive Healthcare Modeling for Early Pandemic Assessment Leveraging Deep Auto-Regressor Neural Prophet.” Scientific Reports, 14(1):5287, 2024.
  5. Gayathri, R., S.K.B. Sangeetha, S.K. Mathivanan, et al. and H. Qin. “Enhancing Heart Disease Prediction with Reinforcement Learning and Data Augmentation.” Systems and Soft Computing, 6:200129, 2024.
  6. Pasha, A., S.T. Ahmed, R.K. Painam, et al. and H. Qin. “Leveraging ANFIS with Adam and PSO Optimizers for Parkinson's Disease.” Heliyon, 10(9):e30241, 2024.
  7. Sangeetha, S.K.B., S.K. Mathivanan, P. Karthikeyan, et al. and H. Qin. “An Enhanced Multimodal Fusion Deep Learning Neural Network for Lung Cancer Classification.” Systems and Soft Computing, 200068, 2024.
  8. Dhakhinamoorthy, C., S.K. Mani, S.K. Mathivanan, et al. and H. Qin. “Hybrid Whale and Gray Wolf Deep Learning Optimization Algorithm for Prediction of Alzheimer's Disease.” Mathematics, 11(5):1136, 2023.
  9. Bhandari, M., A. Neupane, S. Mallik, L. Gaur, and H. Qin. “Auguring Fake Face Images Using Dual-Input Convolution Neural Network.” Journal of Imaging, 9(1):3, 2023.
  10. Rucker, G., H. Qin, and L. Zhang. “Structure, Dynamics and Free Energy Studies on the Effect of Point Mutations on SARS-CoV-2 Spike Protein Binding with ACE2 Receptor.” PLoS ONE, 18(10):e0289432, 2023.
  11. Ou, J., P. Elizalde, H.B. Guo, H. Qin, B.T.D. Tobe, and J.S. Choy. “TCA and SSRI Antidepressants Exert Selection Pressure for Efflux-Dependent Antibiotic Resistance Mechanisms in Escherichia coli.” mBio, 13(6):e0219122, 2022.
  12. Ghafari, M., J. Clark, H.B. Guo, R. Yu, Y. Sun, W. Dang, and H. Qin. “Complementary Performances of Convolutional and Capsule Neural Networks on Classifying Microfluidic Images of Dividing Yeast Cells.” PLoS ONE, 16(3):e0246988, 2021.
  13. Guo, H.B., M. Ghafari, W. Dang, and H. Qin. “Protein Interaction Potential Landscapes for Yeast Replicative Aging.” Scientific Reports, 11(1):7143, 2021.
  14. Sun, Y., R. Yu, H.B. Guo, H. Qin, and W. Dang. “A Quantitative Yeast Aging Proteomics Analysis Reveals Novel Aging Regulators.” GeroScience, 2021.
  15. Yan, D., H. Qin, H.Y. Wu, and J.Y. Chen. “Editorial: AI-Enabled Data Science for COVID-19.” Frontiers in Big Data, 4:802452, 2021.
  16. Guo, H.B. and H. Qin. “Association Study Based on Topological Constraints of Protein–Protein Interaction Networks.” Scientific Reports, 10(1):10797, 2020.
  17. Qin, H. “Estimating Network Changes from Lifespan Measurements Using a Parsimonious Gene Network Model of Cellular Aging.” BMC Bioinformatics, 20(1):599, 2019.
  18. Qin, H., H.H. Lu, W.B. Wu, and W.H. Li. “Evolution of the Yeast Protein Interaction Network.” Proceedings of the National Academy of Sciences USA, 100(22):12820–12824, 2003.

Selected Conference Papers

  1. Annan, R., U. Nkonu, P. Hatami, M.J. Pantho, L. Qingge, and H. Qin. “Predicting Variant Fitness of SARS-CoV-2 from Full Viral Genome Sequences.” Proceedings of the AAAI Symposium Series, 7(1):428–437, 2025.
  2. Qingge, L., H.L. Yimer, M. Sam, R. Annan, R. Newman, and H. Qin. “C2BM: Causal Concept Disentanglement for Fair Multimodal COVID-19 Detection.” Proceedings of the AAAI Symposium Series, 7(1):567–575, 2025.
  3. Al Amin, M.A.U., D. Filienko, and H. Qin. “Influence of Gender-Specific Data Imbalance on scGPT Fine-Tuning for Single-Cell Genomics.” Proceedings of the AAAI Symposium Series, 7(1):420–427, 2025.
  4. Annan, R., H. Qin, X. Yuan, K. Roy, R. Newman, and L. Qingge. “Efficient Federated Learning with Multi-Teacher Knowledge Distillation for COVID-19 Detection.” Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Article 56, 2024.
  5. Qin, H. “Self-Attention Mechanisms as Representations for Gene Interaction Networks in Hypothesis-Driven Gene-Based Transformer Genomics AI Models.” Proceedings of the AAAI Symposium Series, 2024.

Preprints and Technical Reports

  1. Qin, H. “The Emergent Aging Model: Aging as an Emergent Property of Biological Systems.” arXiv preprint, 2024.
  2. Qin, H., J. Kong, W. Ding, et al. “Towards Trustworthy Artificial Intelligence for Equitable Global Health.” arXiv [cs.CY], 2023.
  3. Qin, H., M. Xie, L. Qingge, H. Song, and C.T. Lu. “Pandemic Forecasting with End-to-End Privacy-Preserved Federated Learning.” White paper, Sep 2022.
  4. Qin, H. “A Network Model for Cellular Aging.” arXiv:1305.5784, 2013.

For a complete and continuously updated list, visit Dr. Qin's Google Scholar profile.