Non-Iterative Cluster Routing: Analysis and Implementation Strategies
Pham, H., & Cheng, S. (2024). "Non-Iterative Cluster Routing: Analysis and Implementation Strategies." Applied Sciences, 14(5), 1706. https://doi.org/10.3390/app14051706
CV
Education
- Ph.D. Candidate in Machine Learning and Computer Vision, University of Oklahoma, USA (Expected Jun 2025)
- Electrical & Computer Engineering Department
- GPA: 3.88/4.0
M.S. in Electrical & Computer Engineering, University of Oklahoma, USA (Dec 2018)
- B.Sc. in Electrical & Computer Engineering, Ho Chi Minh City University of Technology, Vietnam (Dec 2012)
Work Experience
- Ph.D. Student, University of Oklahoma, Norman, OK (Aug 2019 – May 2025)
- Deep Learning Architecture in Image Analysis and Semantic Segmentation
- Advisor: Samuel Cheng
- Achievements:
- Improved cluster routing in capsule networks, enhancing model explainability
- Developed and applied deep learning architectures for medical image segmentation
- Created CAD schemes for radiomic feature analysis in gastric cancer prognosis
- Data Scientist Intern & Extended Part-Time, Promaxo Inc., Oakland, CA (May 2022 – May 2023)
- Real-time guidance software for radiologists in prostate biopsy
- Achievements:
- Deployed production-level software with cloud/offline access
- Reduced image registration time by 60%
- Reduced MRI annotation time by 40%, cutting radiologist hiring costs
- Achieved 70% rectal segmentation accuracy in low-field MRI, 96% in high-field
- Analytics Developer Intern, TIBCO Software Inc., Tulsa, OK (May 2020 – Aug 2020)
- Achievements:
- Developed 15 analytics operators for TIBCO StreamBase
- Contributed to “Dynamic Learning” for adapting models to data distribution shifts
- Achievements:
Skills
- Machine Learning
- Statistical Analysis
- Capsule Networks
- CNN
- Foundational Models
- Programming
- Python
- Java
- C++
- R
- Unix Shell Scripting
- MATLAB
- GCP
- Technologies / Frameworks
- PyTorch
- Google Cloud Platform
- Git
- Databricks
- 3D Slicer
- JIRA
- TIBCO Spotfire
- TIBCO StreamBase
Publications
Enhancing Semantic Segmentation through Reinforced Active Learning: Combating Dataset Imbalances and Bolstering Annotation Efficiency
Han, D., Pham, H., & Cheng, S. (2023). "Enhancing Semantic Segmentation through Reinforced Active Learning: Combating Dataset Imbalances and Bolstering Annotation Efficiency." Journal of Electronic & Information Systems, 5(2), 45–60. https://doi.org/10.30564/jeis.v5i2.6063
Deep Learning-Based Rectum Segmentation on Low-field Prostate MRI to Assist Image-guided Biopsy
Pham, H., Le, D. B. T., Sadinski, M., Narayanan, R., Nacev, A., & Zheng, B. (2023). "Deep Learning-Based Rectum Segmentation on Low-field Prostate MRI to Assist Image-guided Biopsy." In Proceedings of SPIE, Vol. 12466, Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and Modeling. https://doi.org/10.1117/12.2654511
Identifying an Optimal Machine Learning Generated Image Marker to Predict Survival of Gastric Cancer Patients
Pham, H., Jones, M., Gai, T., Islam, W., Danala, G., & Zheng, B. (2022). "Identifying an Optimal Machine Learning Generated Image Marker to Predict Survival of Gastric Cancer Patients." In Proceedings of SPIE, Vol. 12033, Medical Imaging 2022: Computer-Aided Diagnosis. https://doi.org/10.1117/12.2611788