2024 - Now
Postdoc, UThealth Houston
- Concentrate on image informatics and deep learning applications.
- Projects on Alzheimer's Disease study using single-cell sequencing.
- Developed a multi-omics pipeline.
2022
Internship, Merck
- Developed an AI-based PD-L1 CPS scoring model for KEYTRUDA® therapy.
- Designed test cases and benchmarked AI performance against pathologist scores.
- Implemented data quality control, cell segmentation, and predictive modeling using Python and PyTorch.
2020 - 2024
Lab Technician, MBB Lab & CBG Center, Tulane University
- Managed data systems, ensuring organized and clean datasets.
- Maintained and updated the MBB Lab website.
- Coordinated meetings, collaborated with partners, and managed project timelines.
- Trained new members on lab protocols and software tools.
2018 - 2024
Research Assistant, Tulane University
- Developed graph deep learning models to analyze fMRI data and predict phenotypes.
- Integrated multimodal data to identify key biomarkers.
- Implemented advanced machine learning algorithms for enhanced precision.
- Collaborated on neuroimaging studies with TReNDS Center, DICoN Lab, and Mind Research Network, supported by NIH and NSF grants.
2017 - 2018
Research Assistant, University of Florida
- Developed a data preprocessing pipeline for whole-slide images, including quality control and segmentation labeling.
- Designed a rule-based CNN model for classifying breast cancer cells using TensorFlow and PyTorch.