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:

• Chen, Z.; Li, P.; Dong, X.; Hong, P. (accepted) Uncertainty Quantification for Clinical Outcome Predictions with (Large) Language Models. The 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguisticss.
• Li, Y.; Xu, H.; Kumar, A.; Wang, D.; Heiss, C.; Azadi, P.; Hong, P. (2025) TransPeakNet for Solvent-aware 2D NMR Prediction via Multi-Task Pre-Training and Unsupervised Learning. Nature Communications Chemistry. DOI:10.1038/S42004-025-01455-9
• Hong, P.; Xia, C.; Tang, Y.; Wei, J.; Lin, C. (2025) Glycan mixture analysis by kernel component composition for matrix factorization. Analytical and Bioanalytical Chemistry. DOI: 10.1007/s00216-025-05777-4
• Chen, Z.; Madireddy, S.; Hong, P. (2024) Quantifying Uncertainty in Large Language Models: Applications in Molecular Chemistry Tasks. NeurIPS Workshop Statistical Foundations of LLMs and Foundation Models.
• Hao, X.; Zhou, Z.; Hong, P. (2024) Enhancing Peak Assignment in CNMR Spectroscopy: A Novel Approach Using Multimodal Alignment. ICML 2024 Workshop AI for Science: Scaling in AI for Scientific Discovery .
• Hao, X.; Zhou, Z.; Hong, P. (2024) Graph Multi-Similarity Learning for Molecular Property Prediction. ICML 2024 Workshop AI for Science: Scaling in AI for Scientific Discovery .
• Tran, P.N.; Ray, S.; Lemma, L.; Li, Y.; Sweeney, R.; Baskaran, A.; Dogic, Z.; Hong, P.*; Hagana, M.F.* (2024) Deep-learning Optical Flow Outperforms PIV in Obtaining Velocity Fields from Active Nematics. Soft Matter. DOI: 10.1039/D4SM00483C
• Chen, Z.; Badman, R.P.; Foley, L.; Woods, R.; Hong, P.* (2024) GlycoNMR: Dataset and Benchmark of Carbohydrate-Specific NMR Chemical Shift for Machine Learning Research. Journal of Data-centric Machine Learning Research 2024.
• Chung, J.; Li, J.; Saimon, A.I.; Hong, P.*; Kong, Z.J.* (2024) Predicting the Stereoselectivity of Chemical Reactions by Composite Machine Learning Method. Scientific Reparts (14):12131. DOI: 10.1038/s41598-024-62158-0
• Li, Y.; Zarei, Z.; Tran, P.; Wang, Y.; Baskaran, A.; Fraden, S.; Hagan, M.F.; Hong, P.* (2024) 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.* (2023) 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.*; 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.; 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.; 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.; 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.; Liu, H. (2021). On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections. International Conference on Learning Representations 2021.

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