Bio
I am a computational biologist working at the intersection of spatial regulatory biology, systems immunology, and cell-state dynamics. My central scientific interest is how regulatory programs—including transcription factors, RNA-binding proteins, microRNAs, and chromatin architecture—interact with immune and tissue context to determine which cellular states emerge, persist, transition, or fail in disease.
I am an M.S. candidate in Bioinformatics at Johns Hopkins University and a Graduate Research Assistant in the Advanced Computing and Oncology Laboratory at Memorial Sloan Kettering Cancer Center. My thesis project, StageBridge, develops niche-conditioned models of cell-state transition from cross-sectional single-cell and spatial transcriptomic data. In parallel, my work at MSK integrates quantitative imaging, immune profiling, tumor genomics, circulating biomarkers, and clinical outcomes to study how host biology shapes treatment response and disease trajectory.
Across these projects, I aim to move from static molecular description toward mechanistically interpretable models of biological change. I am especially interested in computational frameworks that connect gene-regulatory programs to spatial organization and cell-state transitions, and in universal differential equations and other hybrid mechanistic-learning approaches that can incorporate known biology while learning the dynamics that remain unknown. This is the research direction I intend to develop through Ph.D. training.
Current focus
Spatial regulatory biology and cell-state dynamics
I study how local niche context and regulatory programs shape cell-state transitions across premalignant, malignant, inflammatory, and tissue-remodeling settings. StageBridge is the current methodological foundation for this direction, combining receiver-centered niche representations with progression-aware transition modeling.
Systems immunology and host response
Through HostBio and the broader thymic-reserve program, I investigate how systemic immune architecture and host tissue state modify treatment response, toxicity, recurrence, and survival. This work connects quantitative imaging with longitudinal immune phenotyping, tumor genomics, radiation exposure, and clinical outcomes across multiple lung cancer cohorts.
Collaborative disease biology
I contribute computational analysis and model development to collaborations in secondary lymphedema, myasthenia gravis and thymoma, cGAS-STING biology, and head and neck squamous cell carcinoma. These projects provide complementary systems in which to study immune regulation, tissue remodeling, and disease-associated cell states.
Mechanistic models of biological dynamics
A growing methods focus is the use of universal differential equations and other hybrid mechanistic-machine-learning models to represent biological systems whose governing structure is partly known but whose context-dependent dynamics must be learned from data.
Research software as scientific infrastructure
I build reproducible, configuration-driven platforms for single-cell analysis, quantitative imaging, microbiome research, and cancer genomics. The goal is not software for its own sake, but infrastructure that makes complex biological questions auditable, scalable, and testable across datasets.
Selected projects
Together, these projects form a connected research program: learning how cell states are regulated in tissue context, quantifying host and immune biology from clinical data, and building rigorous computational infrastructure that can carry those questions across cohorts and modalities.
Education
GPA: 4.0
Master’s thesis: StageBridge: Context-Residual Inference of Cell-State-Resolved Niche Effects in Premalignant Epithelial Transitions.
Advisor: Christopher Bradburne, PhD, Department of Genetic Medicine, Johns Hopkins University School of Medicine / Johns Hopkins Applied Physics Laboratory.
Selected coursework: Advanced Genomics; Gene Expression Analysis; Systems Biology; Deep Learning Using Transformers; Epigenetics; Cellular Signal Transduction.
Summa Cum Laude, GPA 3.9.
Honors thesis: Investigating the Role of MMP14, B7-H3, PTK7, and LRRC15 in Head and Neck Cancers: Implications for Antibody-Drug Conjugates.
Experience
Lead conceptual development and computational strategy for translational studies of tumor-host interaction, immune remodeling, thymic composition, treatment toxicity, and lung cancer outcomes.
- Develop multimodal analysis frameworks integrating thoracic CT, radiation dose, clinical outcomes, targeted sequencing, circulating tumor DNA, RNA-seq, flow cytometry, cytokine profiling, and immune validation assays.
- Build spatial and single-cell workflows for reference-atlas mapping, spatial deconvolution, cell-state annotation, regulatory-network analysis, cell-cell communication, and interpretation of inflammatory, stromal, epithelial, and immune programs.
- Contribute to cross-group collaborations in secondary lymphedema, myasthenia gravis and thymoma, cGAS-STING biology, head and neck squamous cell carcinoma, and translational systems immunology.
- Develop reusable research software for cohort-scale quantitative imaging, single-cell analysis, microbiome comparison, and cancer genomics.
- Generate publication-grade figures, statistical analyses, reproducible workflows, abstracts, and manuscript-ready results; contribute as co-first author and primary quantitative analyst on translational studies.
Supported Mohs micrographic surgery workflow, clinical documentation, tissue handling, and dermatopathology preparation for squamous and basal cell carcinoma cases.
- Prepared frozen tissue sections and H&E-stained slides.
- Assisted with immunohistochemistry-associated workflows and surgical pathology review preparation.
Analyzed TCGA and GEO transcriptomic datasets in R and Bioconductor to study tumor immune microenvironment programs in head and neck squamous cell carcinoma, with emphasis on cancer-associated fibroblast and cancer stem-like cell states.
- Integrated differential expression, pathway enrichment, survival analysis, cell-cell communication evidence, and structural biology context to prioritize candidate antibody-drug conjugate targets.
Built and maintained a clinical oncology research database, performed retrospective survival analyses, and contributed to peer-reviewed studies of prognostic factors and treatment outcomes in gastrointestinal cancers.
Presentations
Selected scientific presentations.
Publications
Selected peer-reviewed publications, preprints, and manuscripts.