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Research
My research focuses on machine learning and its applications, such as, Bioinformatics, Glycomics, Materials Research, FinTech, Medical Informatics, and so on. I am recruiting PhD students with solid backgrounds in math and programming.
Recent publications:
- Li, Y., Zarei, Z., Tran, P., Wang, Y., Baskaran, A., Fraden, S., Hagan, M.F., Hong, P. A Machine Learning Approach to Robustly Determine Director Fields and Analyze Defects in Active Nematics. Soft Matter 2024. DOI: 10.1039/D3SM01253K
- Ni, Y., Murray, N.B., Archer-Hartmann, S., Pepi, L.E., Helm, R.F., Azadi, P., Hong, P. Toward Automatic Inference of Glycan Linkages Using MSn and Machine Learning - Proof of Concept Using Sialic Acid Linkages. Journal of the American Society for Mass Spectrometry 2023. DOI: 10.1021/jasms.3c00132s
- Chen, Z.; Li, P.; Liu, H.; Hong, P. Characterizing the Influence of Graph Elements. ICLR 2023
- Wang, Y.; Chen, S.; Chen, G.; Shurberg, E.; Liu, H.; Hong, P. Motif-Based Graph Representation Learning with Application to Chemical Molecules. Informatics 2023, 10, 8. DOI: 10.3390/informatics10010008
- Yue, H., Hong, P., Liu, H. (2022). Graph-Graph Similarity Network. IEEE Transactions on Neural Networks and Learning Systemss. PMID: 36374897. DOI: 10.1109/TNNLS.2022.3218936
- Yang, T., Wang, Y., Sha, L., Engelbrecht, J., and Hong, P. (2022). Knowledgebra: An Algebraic Learning Framework for Knowledge Graph. Machine Learning and Knowledge Extraction. DOI: 10.3390/make4020019
- Tan, W., Zhang, Q., Quinones-Frias, M.C., Hsu, A.Y., Zhang, Y., Rodal, A., Hong, P., Luo, H.R., and Xu, B. (2022). Enzyme-Responsive Peptide Thioesters for Targeting Golgi Apparatus. J. Am. Chem. Soc. DOI: 10.1021/jacs.2c02238
- Tan, W., Zhang, Q., Hong, P., and Xu, B. (2022). A Self-Assembling Probe for Imaging the States of Golgi Apparatus in Live Single Cells. Bioconjugate Chemistry. DOI: 10.1021/acs.bioconjchem.2c00084
- Chen, Z., Wei, J., Tang, Y., Lin, C., Costello, C.E., and Hong, P. (2022). GlycoDeNovo2: An Improved MS/MS-Based De Novo Glycan Topology Reconstruction Algorithm. Journal of the American Society for Mass Spectrometry DOI:10.1021/jasms.1c00288
- Wang, Y., Tang, J., Vimal, V.P., Lackner, J., DiZio, P. and Hong, P. (2022). Crash Prediction Using Deep Learning in a Disorienting Spaceflight Analog Balancing Task. Front. Physiol. DOI: 10.3389/fphys.2022.806357
- Du, H.*, Chen, F.*, Liu, H., and Hong, P. (* equal contribution) (2021). Network-based Virus-Host Interaction Prediction with Application to SARS-CoV-2. Cell Patterns. DOI: 10.1016/j.patter.2021.100242
- Li, P., Wang, Y., Zhao, H., Hong, P., and Liu, H. (2021). On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections. International Conference on Learning Representations 2021.
- Zhou, Z., Joshi, C., Liu, R., Norton, M. M., Lemma, L., Dogic, Z., Hagan, M. F., Fraden, S., and Hong, P. (2020). Machine Learning Forecasting of Active Nematics. Soft Matter. DOI: 10.1039/D0SM01316A
- Yang, T., Sha, L., and Hong, P. (2020). NagE: Non-Abelian Group Embedding for Knowledge Graphs. ACM International Conference on Information and Management.
- Yang, T., Sha, L., Li, J. and Hong, P. (2020). A Deep Learning Approach for COVID-19 Trend Prediction. International Workshop on Epidemiology Meets Data Mining and Knowledge Discovery
- Vimal, V. P., Zheng, H., Hong, P., Fakharzadeh, L. N., Lackner, J. R., DiZio, P. (2020). Characterizing Individual Differences in a Dynamic Stabilization Task using Machine Learning. Aerospace Medicine and Human Performance, 91(6):479-488. https://doi.org/10.3357/amhp.5552.2020.
- Yoong, L. F., Lim, H. K., Tran, H., Lackner, S., Zheng, Z., Hong, P., Moore, A. W. (2020). Atypical Myosin Tunes Dendrite Arbor Subdivision. Neuron, 106:1–16. https://doi.org/10.1016/j.neuron.2020.02.002
- Zhao, R., Hong, P., and Liu, J.S. (2020). IMMIGRATE: A Margin-based Feature Selection Method with Interaction Terms. Entropy, 22(3):291. https://doi.org/10.3390/e22030291
- Xing, X., Sha, L., Hong, P., Shang, Z., Liu, J.S. (2020). Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks. International Conference on Learning Representations 2020.
- Wei, J., Tang, Y., Bai, Y., Zaia, J., Costello, C., Hong, P., Lin, C. (2020). Towards Automatic and Comprehensive Glycan Characterization by On-line PGC-LC-EED MS/MS. American Chemical Society. 92(1):782-791. https://doi.org/10.1021/acs.analchem.9b03183
Teaching (co-teach)
- COSI 101A Fundamentals of Artificial Intelligence
- COSI 123A Statistical Machine Learning
- COSI/ECON 148B Introduction to Machine Learning with Economic Applications
- COSI 149B Practical Machine Learning with Big Data (with applications in FinTech, Computer Vision, NLP, and Life Sciences)
- COSI 178A Computational Biology
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