I am a PhD candidate in the Joint Carnegie Mellon University- University of Pittsburgh PhD Program in Computational Biology, where I work on AI/ML research for immunology.
My research interests include statistical modeling and deep learning for noisy, high-dimentionsal signals. Currently, I am developing an interpretable variant of the attention mechanisms for transformer models.
Highlighted Publications and Projects (scroll down for more):
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SLIDE: Significant Latent Factor Interaction Discovery and Exploration across biological domains
J Rahimikollu *, H Xiao * , et al
Nature Method, * represents equal contribution
Link to Manuscript
Link to Research Briefing
Link to Media Coverage
Link to Media Coverage
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Interpretable machine learning uncovers epithelial transcriptional rewiring and a role for Gelsolin in COPD
J Su *, H Xiao * , et al
JCI Insight, * represents equal contribution
Link to Manuscript
- From bench to bedside via bytes: Multi-omic immunoprofiling and integration using machine learning and network approaches
H Xiao , et al
Human Vaccines & Immunotherapeutics Link to Manuscript
- Spatial microniches of IL-2 combine with IL-10 to drive lung migratory TH2 cells in response to inhaled allergen
k He, H Xiao , et al
Nature Immunology Link to Manuscript
Updates & News (scroll down for more):
- October 2024: My co-authored paper, Spatial microniches of IL-2 combine with IL-10 to drive lung migratory TH2 cells in response to inhaled allergen, is published in Nature Immunology.
- October 2024: My co-first-authored paper, Interpretable machine learning uncovers epithelial transcriptional rewiring and a role for Gelsolin in COPD, is published in JCI Insight.
- September 2024: I recieved research presentation award for my project titled 'Interpretable machine learning uncovers spatial-microenvironment-specific drivers of pathogenesis in myocardial infarction' at the University of Pittsburgh Immunology Retreat.
- September 2024: My co-authored paper, Deep humoral profiling coupled to interpretable machine learning unveils diagnostic markers and pathophysiology of schistosomiasis, is published in Science Translational Medicine.
- August 2024: My co-authored paper, Aberrant mitochondrial DNA synthesis in macrophages exacerbates inflammation and atherosclerosis, where I applied machine learning methods to analyze murine single-cell RNA-sequencing data is published in Nature Communications.
- August 2024: My co-authored paper, Regulatory T Cell Insufficiency in Autoimmune Diabetes Is Driven by Selective Loss of Neuropilin-1 on Intraislet Regulatory T Cells, is published in Nature Communications.
- May 2024: University of Pittsburgh and Cornell University write about my work SLIDE.
- May 2024: My co-first-authored paper where we developed a novel interpretable machine learning model, SLIDE, has been published at Nature Methods.
- December 2023: I have been awarded the Quantitative Methodologies Pilot Program (QuMP) grant as a co-principle investigator for the project "Uncovering immunomodulatory spatial microniches in asthma involving Th2 and Tfh2 cells using interpretable machine learning ."
- December 2023: My firt-authored review, From bench to bedside via bytes: Multi-omic immunoprofiling and integration using machine learning and network approaches, is published in Human Vaccines and Immunotherapeutics.
- October 2023: I passed my thesis proposal and doctoral candidate exam!