Dr. Henry Han

Education

• PhD, Applied Mathematical & Computational Sciences, University of Iowa (2004)
• MS, Computer Science, University of Iowa (2001)
• MS, Applied Mathematics, University of Iowa (2001)

SHORT CV

Research Interests

• Data science
• Fintech
• Artificial Intelligence
• Bioinformatics and Health informatics
• Cybersecurity
• Quantum computing

Selected Publications

1. Han, H, Teng, J, Xia, J, Wang, Y, Guo, Z, Li, D: Predict High-Frequency Trading Marker via Manifold Learning, Knowledge-based system, 213:106662, 2021
    
2. Tian, X, Han, H: Deep Convolutional Neural Networks with Transfer Learning for Automobile Damage Image Classification, Journal of Database Management (Acceptance) 2021
    
3. Zhang, Y, Zhang, F, Guo, L, Han, H: Salient object detection using feature clustering and compactness prior, Multimedia Tools and Applications, 2021, DOI:10.1007/s11042-021-10744
    
4. Han, F, Chen W, Ling, Q, Han, H, Multi-objective particle swarm optimization with adaptive strategies for feature selection, Swarm and Evolutionary Computation, 62:100847, 2021
    
5. Jiang, J., Han, F., Ling, Q., Wang, J, Li, T, Han, H: Efficient Network Architecture Search via Multiobjective Binary Particle Swarm Optimization based on Decomposition, Neural networks, 123 305–316, 2020
    
6. Liu, W, Li, D, Han, H: Manifold learning analysis for Allele-skewed DNA modification SNPs for psychiatric disorders, IEEE Access, 8:1, 33023-33038, 2020
    
7. Xu, P, Lu, D, Yu, J, Kou, Z, Gang, F, Liu, W, Han, H: A shortest pathway study for evaluating the impact of critical miRNAs on cell proliferation and apoptosis, BMC Bioinformatics 21(1): 396 (2020)
    
8. Li, J, Jiang, W, Han, H, et al: ScGSLC: An Unsupervised Graph Similarity Learning Framework for Single-cell RNA-seq Data Clustering, Computational Biology and Chemistry, 2021;90:107415
    
9. Han, H: Hierarchical learning for option implied volatility pricing, the 54th Hawaii International Conference on System Sciences (HICSS) 2021, 1573-1582
    
10. Li, T, Han, H: A high-performance basketball game forecast using magic feature extraction, Recent advances in data science, Springer communications in computer and information science vol 1099, 35-50, 2020