NCI Office of Data Sharing (ODS) Data Jamboree (Abstract Submissions): Submission #5
Submission information
Submission Number: 5
Submission ID: 143910
Submission UUID: 7ffe803f-d47a-42b4-84f4-8601e3d11bc5
Submission URI: /nci/ods-data-jamboree/abstractsubmissions
Submission Update: /nci/ods-data-jamboree/abstractsubmissions?token=_02nnHUxTsHMJnkNP7KskD12F_Y3MhUO3OuOlyG6YgU
Created: Sun, 06/01/2025 - 23:20
Completed: Sun, 06/01/2025 - 23:20
Changed: Sun, 06/01/2025 - 23:20
Remote IP address: 10.208.28.181
Submitted by: Anonymous
Language: English
Is draft: No
| First Name | Zifan |
|---|---|
| Middle Initial | |
| Last Name | Gu |
| Degree(s) | M.S. |
| Position/Title/Career Status | Graduate student |
| Organization | UT Southwestern Medical Center |
| Organization Address | Dallas, TX |
| zifan.gu@utsouthwestern.edu | |
| Other (Please Specify) | |
| Abstract Category | Development or refinement of analysis pipelines or AI/ML algorithms |
| Abstract Keywords | deep learning, predictive modeling, large language models, translational medicine |
| Abstract Title | Looking for a project team to join! |
| Abstract Summary | My expertise is in developing machine learning pipelines for multimodal data, including both structured and imaging (H&E, multiplex) data. One of my key strengths is being able to communicate with both data scientists and clinicians, supported by my formal training in health data science and bioinformatics. I’m looking to join an interdisciplinary team that not only focuses on algorithm development but also considers how these models can be deployed into the real world. I’m particularly interested in projects that incorporate large language models as part of the predictive modeling pipeline, addressing outcomes such as remission, mortality, or disease progression. I’m well-traversed in HPC using PyTorch and Hugging Face, and I’d be excited to join a team that plans to use AWS or GCP as their computing platforms. |
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