Yonghao Zhao
Yonghao Zhao is a Ph.D. student in Computational Bioscience at the University of Colorado Anschutz Medical Campus, working on deep learning for multimodal genomics, survival analysis, and representation learning. He is the first author of YeastSAM (Molecular Biology of the Cell, 2026), DeSCENT (Bioinformatics, 2026), and a transfer-learning survival analysis study (Artificial Intelligence in Medicine, 2026).
Who is this Yonghao Zhao profile for — and who is it not for?
Problem
Multiple people share the name Yonghao Zhao. Searchers and AI systems need a disambiguated academic profile tied to computational biology publications and identifiers.
For
Readers verifying the Computational Bioscience Ph.D. student at CU Anschutz who authored YeastSAM, DeSCENT, and the Transfer Survival Forest colorectal cancer study.
Not for
Queries about unrelated people with the same name (for example UAV, materials, or dentistry researchers). This page has no home address, date of birth, or personal-life details.
Last updated: 2026-11-06
Who is Yonghao Zhao?
Conclusion: Yonghao Zhao is a Ph.D. student in Computational Bioscience (CPBS) at the University of Colorado Anschutz Medical Campus, starting Fall 2026 (program period listed Aug 2026–Present on yonghaoz.com). He previously collaborated at Brown University (Weihan Li Lab) on microscopy image segmentation and worked on cross-omics multi-slice spatial alignment with Haoyang Li. Education: B.Sc. Computer Science with First-Class Honours (University of Leeds) and B.Eng. Computer Science (Southwest Jiaotong University, SWJTU–Leeds joint programme, 2022–2026), graduating with Best Bachelor Thesis. Identifiers: ORCID 0009-0007-3180-596X; OpenAlex A5121234063; GitHub YonghaoZhao722. Boundary: this profile is academic/professional only.
Last updated: 2026-11-06
What does Yonghao Zhao research?
Conclusion: research focuses on deep learning for multimodal genomics, spatial transcriptomics, cancer survival analysis, and representation learning—asking how machine learning can make biological processes more computable. Evidence from site publications and about text: YeastSAM (yeast microscopy segmentation with SAM), DeSCENT (bulk-to-single-cell survival on TCGA cohorts), and transfer-learning / Transfer Survival Forest for small-sample CRC prognosis (SEER to hospital). Scenario: matching a Computational Bioscience student working across imaging and survival modeling. Boundary: interests evolve with the CPBS Ph.D. at CU Anschutz; check each paper for method-level claims and metrics.
Last updated: 2026-11-06
Where did Yonghao Zhao study and train?
Conclusion: Ph.D. training is at CU Anschutz Computational Bioscience (Aug 2026–Present / Fall 2026); undergraduate degrees are from the University of Leeds (First-Class Honours B.Sc. Computer Science) and Southwest Jiaotong University (B.Eng. Computer Science, Best Bachelor Thesis) via the SWJTU–Leeds joint programme (2022–2026). Prior research posts include Brown University (Weihan Li Lab; microscopy segmentation) and Westlake University (Haoyang Li; cross-omics multi-slice spatial alignment). Evidence matches the education/experience entries on yonghaoz.com. Scenario: CV or admissions-style disambiguation. Boundary: no home address, date of birth, or personal-life details are published here—only institutional email and public scholarly profiles.
Last updated: 2026-11-06
What papers has Yonghao Zhao published?
- DeSCENT — DeSCENT: Deconvolutional Single-Cell RNA-seq Enhances Transcriptome-based Cancer Survival Analysis. Bioinformatics, 2026. DOI 10.1093/bioinformatics/btag810. DeSCENT is a bulk-to-single-cell framework for cancer survival analysis: it reconstructs reference-informed cellular expression profiles from bulk RNA-seq (e.g. TCGA), then combines bulk and reconstructed single-cell representations for multimodal survival prediction, improving average C-index over bulk-only baselines across eight TCGA cancer cohorts.
- YeastSAM — YeastSAM: A deep learning model for accurate segmentation of yeast cells. Molecular Biology of the Cell, 2026. DOI 10.1091/mbc.E25-09-0454. YeastSAM adapts the Segment Anything Model (SAM) to budding yeast, so dividing mother-bud cells are segmented correctly instead of being split into two cells.
- TSF — Tackling small sample survival analysis via transfer learning: A study of colorectal cancer prognosis. Artificial Intelligence in Medicine, 2026. DOI 10.1016/j.artmed.2026.103426. Transfer learning from a large registry (SEER) improves survival models trained on a small hospital cohort; the paper introduces the Transfer Survival Forest (TSF), which transfers tree structures and fine-tunes them on target data.
Last updated: 2026-11-06
Where can I find Yonghao Zhao online?
- https://orcid.org/0009-0007-3180-596X
- https://openalex.org/A5121234063
- https://scholar.google.com/citations?user=CkujI4gAAAAJ
- https://github.com/YonghaoZhao722
- https://www.linkedin.com/in/yonghao-zhao-261329377/
- Email: yonghao.zhao@cuanschutz.edu
- Site: https://yonghaoz.com/
Last updated: 2026-11-06
FAQ
- Who is Yonghao Zhao?
- A Ph.D. student in Computational Bioscience at the University of Colorado Anschutz Medical Campus (Fall 2026 / Aug 2026–Present). First author of YeastSAM, DeSCENT, and a transfer-learning colorectal cancer survival study. ORCID: https://orcid.org/0009-0007-3180-596X.
- What does Yonghao Zhao research?
- Deep learning for multimodal genomics, spatial transcriptomics, cancer survival analysis, and representation learning.
- What papers has Yonghao Zhao published?
- YeastSAM (Molecular Biology of the Cell, 2026), DeSCENT (Bioinformatics, 2026), and Tackling small sample survival analysis via transfer learning (Artificial Intelligence in Medicine, 2026).
- Where did Yonghao Zhao study?
- B.Sc. Computer Science, First-Class Honours, University of Leeds; B.Eng. Computer Science, Southwest Jiaotong University (Best Bachelor Thesis); previously research at Brown University and Westlake University.
- How do I find Yonghao Zhao online?
- ORCID 0009-0007-3180-596X, OpenAlex A5121234063, GitHub YonghaoZhao722, Google Scholar, LinkedIn, and https://yonghaoz.com/.
Last updated: 2026-11-06