Welcome to my GitHub! I'm a PhD student in Molecular and Computational Biology at the University of Southern California (USC). I build and apply both conventional and deep learning models to understand complex biological systems—particularly those involved in cancer biology, metastasis, and rare cell detection through liquid biopsy.
- PhD Candidate @ USC, Molecular & Computational Biology
- Focused on deep learning for liquid biopsy, rare circulating cells, and tumor microenvironment characterization
- Interested in bridging computational modeling and translational oncology
Here’s a selection of research publications and corresponding code repositories:
| Publication | Journal | Repository | Year |
|---|---|---|---|
| Unsupervised Detection of Rare Events in Liquid Biopsy Assays | NPJ Precision Oncology | RED GitHub Repo | 2025 |
| Representation Learning Enables Robust Single Cell Phenotyping in Whole Slide Liquid Biopsy Imaging | Scientific Reports | DeepPhenotyping GitHub Repo | 2025 |
I'll keep this section up to date as new work is published.
I also recently developed a web-based social media for sharing academic papers between researchers called Quorum. Basic tech stack: React, Node, Supabase, and a $5 VPS from DigitalOcean.
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Rare Cell Phenotyping
Instance-level models for identifying rare events in blood-derived imaging data. -
Foundational Models in Biology
Contrastive and generative models to build high-resolution, modality-aware cell embeddings. -
Cancer Bioinformatics
Translating raw image data and patient metadata into interpretable, actionable clinical insights.
- Languages: Python, R
- Frameworks: PyTorch, TensorFlow, Scanpy, scikit-learn, Seurat, BioConductor, DESeq
- Specialties: Cancer Biology, Liquid Biopsy, MIL, Contrastive Learning, Image Segmentation
- Email: tessone@usc.edu
- LinkedIn: linkedin.com/in/deantessone
- Google Scholar: https://scholar.google.com