Portfolio item number 1
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portfolio
Portfolio item number 2
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publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).
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Development and validation of PAMPA-BBB QSAR model to predict brain penetration potential of novel drug candidates
Published in Frontiers in Pharmacology 14:1291246, 2023
QSAR models trained on the largest PAMPA-BBB dataset to date to predict small-molecule brain penetration—an orthogonal complement to in vivo and Caco-2/MDCK assays.
Recommended citation: Kato, R., Zeng, W., Siramshetty, V. B., Williams, J., Kabir, M., Hagen, N., Padilha, E. C., Wang, A. Q., Mathé, E. A., Xu, X., & Shah, P. (2023). "Development and validation of PAMPA-BBB QSAR model to predict brain penetration potential of novel drug candidates." Frontiers in Pharmacology, 14:1291246. https://doi.org/10.3389/fphar.2023.1291246
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Paper Title Number 4
Published in GitHub Journal of Bugs, 2024
This paper is about fixing template issue #693.
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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Paper Title Number 5, with math \(E=mc^2\)
Published in GitHub Journal of Bugs, 2024
This paper is about a famous math equation, \(E=mc^2\)
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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Learning from Elders: Making an LLM-powered Chatbot for Retirement Communities more Accessible through User-centered Design
Published in arXiv preprint arXiv:2504.08985, 2025
Designing an accessible LLM-powered chatbot to support older adults in retirement communities using a human-centered approach.
Recommended citation: Li, L. X., Chung, R., Chen, F., Zeng, W., Jeon, Y., & Zaslavsky, O. (2025). "Learning from Elders: Making an LLM-powered Chatbot for Retirement Communities more Accessible through User-centered Design." arXiv preprint arXiv:2504.08985. https://doi.org/10.48550/arXiv.2504.08985
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talks
Predicting COVID-19 Severity Levels Using Pre-COVID Metabolomic and Clinical Data
Published:
This poster showed the several machine learning models being used to make a multi-level prediction on COVID-19 severity levels using patients’ pre-COVID metabolomic data. The output could further help guide clinical decisions for COVID-19 patients.
Predicting Chemical Toxicity using a Hierarchical Bayesian Approach with Tox21 Assay Data
Published:
Poster presentation on how we built hierarchical bayesian model to predict chemical toxicity with Tox21 data assays. Logistic regression and Naive Bayesian were also built to serve as baseline models to compare with the hierarchical bayesian model.
An Ontology-Guided Analysis to Unveil Disparities of Social History Documentation in Discharge Notes
Published:
This study applies an ontology-based natural language processing framework to examine how social determinants of health are documented in clinical discharge notes. The work uncovers disparities in documentation patterns across demographic groups, underscoring the need for more equitable representation of patients’ social contexts in electronic health records.
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Reveal Glioblastoma Heterogeneity through Spatial Transcriptomics
Published:
Participate in the 3-minute-talk (3MT) competition held by ITHS as a TL1 fellowship trainee. I presented about the importance of studying glioblastoma’s heterogeneity, the reason for using spatial transcriptomic, and the development of our computational pipelines.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.