Ross Geller · CV · Book Title Page

· Curriculum Vitæ · Seoul · Boston ·

A Vita of Research in

Ross Geller

Doctor of Philosophy · Biomedical Sciences

Computational biologist moving from single-cell and spatial multi-omics into connectome-scale neuroscience.

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220 Harbor Street, Boston, Massachusetts 02135
(555) 019-2847 · ross.geller@example.com · Google Scholar
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MMXXVI

Profile

Statement of the Author

Moving from wet-lab immunology into computational neuroscience. I build methods that infer cellular identity, state, and interaction from large, incomplete single-cell and spatial data. Research objective: connect molecular cell identity to circuit structure and function by integrating connectomics with transcriptomics, growing into connectome-constrained circuit models.

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Education

Degrees Conferred

Doctor of Philosophy, Biomedical Sciences

MMXIV – MMXXIII

Hangang National University · Seoul, Republic of Korea

Thesis: Mapping Dendritic Cell Heterogeneity Across Chronic Inflammatory Contexts · Advisor: Min-Ho Suh, M.D., Ph.D.

Master of Science, Biomedical Sciences

MMXII – MMXIV

Hangang National University · Seoul

Thesis: Enhanced LPS-Induced Monocyte Activation by Recombinant Human Soluble CD180

Bachelor of Science, Genetic Engineering

MMVIII – MMXII

Suwon Institute of Life Sciences · Suwon

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Experience

Positions Held

Postdoctoral Researcher

MMXXV – MMXXVI

Nakdong University Wonju College of Medicine · Physiology / Cellular Systems Research Center

Developed deep-learning multimodal-integration models fusing imaging, transcriptomic, and clinical data into single predictive models.

Associate Director

MMXXIII – MMXXV

Meridian Immune Therapeutics Inc. · Basic Research, Seoul

Built in-house single-cell and spatial transcriptomics analysis code from scratch; led NHP (cynomolgus, marmoset) EAE/MS multi-omic studies; oversaw regulatory documentation for an anti-CD25 humanized-antibody program.

Researcher

MMXIX – MMXXI

Xenotransplantation Research Center, HNU · Seoul

Rhesus macaque tissue processing, longitudinal immune monitoring, CNS (brain/spinal cord) tissue handling.

Research Student, MOSAIC

MMXX – MMXXIII

Multi-Organ Single-cell Atlas of Immune Cells, HNU · Genomic Medicine Institute

Contributed the founding proposal; executed within the funded program (500+ donors × 6 organs): milestone tracking, multi-site QC, multi-PI coordination.

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Selected Publications

18 total · 17 peer-reviewed · 6 first / co-first · 1 under review

i.Reyes M*, Geller R*, Alvarez T*, et al. "Conserved PDE9X short-isoform bias defines pathogenic Th1.17 state across human inflammatory diseases." Nature Immunology IF 27.7 · under review, 2026. UMI-aware BAM-level isoform analysis; scRNA + scTCR + snATAC integration; ML classifier AUC 0.812; 702 samples, 251,055 CD4⁺ T cells.

ii.Geller R*, Tanaka Y*, Truong P*, et al. "Infiltrated CD8⁺ T resident memory cells and meningeal lymphatic endothelium in Parkinson's disease." Journal of Neuroimmunology IF 2.9 · 2025. 9,240 cells, 8 immune populations.

iii.Geller R*, Delgado J*, Moreau S, et al. "Deciphering Dysfunctional Regulatory T Cells in Vitiligo." Allergy IF 12.6 · 2025.

iv.Alvarez J*, Geller R*, et al. "Long-term control of diabetes by a baricitinib-based regimen after allo-islet transplantation in rhesus monkeys." Xenotransplantation IF 3.9 · 2024.

v.Novak L*, Geller R*, et al. "Intra-tumoral heterogeneity and immune escape of melanoma from chronic UV photodamage by spatial gene expression." JEADV IF 9.2 · 2022.

vi.Geller R*, et al. "mTOR inhibitor-based immunosuppression in allogeneic islet transplantation." Islets IF 2.2 · 2019. Co-author: eBioMedicine (2024), JEADV (2024), Current Diabetes Reports (2021).

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Technical Skills

Instruments of the Trade

Single-cell, spatial and multi-omic. scRNA-seq, scTCR-seq, snRNA/snATAC; Seurat, Scanpy, Squidpy, Monocle3, CellChat/NicheNet; scVI/scANVI, consensus NMF; custom UMI-aware BAM-level isoform code (Python); Milo, GLIPH, InferCNV; GeoMx DSP; Olink proteomics.

Machine learning and deep learning. Python (scikit-learn, XGBoost/LightGBM/CatBoost, PyTorch); AUC-validated classifiers; VAE/GAN/GNN; multimodal DL (imaging + transcriptomic + clinical); AlphaFold2/3, ProteinMPNN, DiffDock; Linux, R, Git.

Experimental. 10x 5′/3′ scRNA + scTCR libraries; high-dimensional flow cytometry (24 markers); brain/CNS immune profiling; IHC/IF; two-photon; NHP CNS tissue (rhesus, cynomolgus, marmoset); EAE/MS and islet-transplant models.

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