# Yiyu Zhuang - Ph.D. Candidate in Computer Science | AI/ML Researcher
Source: https://hello.cv/yiyuzhuang
yiyuzhuang@ucsd.edu | San Diego

## Links
- LinkedIn | https://www.linkedin.com/in/yiyu-zhuang-0b9b3b171/
- GitHub | https://github.com/yiyuzhuang

## About
Highly accomplished Ph.D. Candidate in Computer Science with extensive research experience in advanced Machine Learning and Computer Vision, specializing in innovative applications for medical image analysis and multi-modal learning. Proven ability to develop state-of-the-art deep learning frameworks, evidenced by multiple peer-reviewed publications in top-tier conferences like CVPR, MICCAI, and AAAI, and significant contributions during internships at NVIDIA, Microsoft Research Asia, and Tencent AI Lab.

## Work
### Research Assistant | University of California, San Diego
https://www.ucsd.edu/
Orchestrated advanced machine learning and computer vision research, developing innovative solutions for medical image analysis and multi-modal learning that resulted in multiple top-tier publications.
- Developed novel multi-modal learning frameworks for medical image analysis, achieving state-of-the-art performance in chest X-ray and histopathology tasks.
- Designed and implemented privacy-preserving federated learning approaches for distributed medical AI, improving data security and model robustness by X% (specific metric to be added if available).
- Pioneered self-supervised learning techniques for robust feature extraction across diverse datasets, enhancing model generalization and reducing reliance on labeled data by Y%.
- Authored and co-authored multiple peer-reviewed publications in top-tier conferences including CVPR, MICCAI, AAAI, and BMVC, advancing the state-of-the-art in AI research.
### Research Intern | NVIDIA
https://www.nvidia.com/en-us/research/
Developed and validated a novel multi-modal learning framework for chest X-ray analysis, achieving state-of-the-art performance and contributing to a MICCAI publication.
- Engineered a novel multi-modal learning framework for chest X-ray analysis, integrating clinical text with imaging data to improve diagnostic accuracy by up to 5%.
- Implemented and optimized deep learning models in PyTorch, achieving state-of-the-art performance on public medical benchmarks within a 3-month internship.
- Collaborated with a team of researchers to prepare and publish findings at MICCAI 2023, contributing to the advancement of medical AI technologies.
### Research Intern | Microsoft Research Asia (MSRA)
https://www.microsoft.com/en-us/research/lab/microsoft-research-asia/
Conducted impactful research on self-supervised learning for multi-modal medical image segmentation, significantly enhancing model performance and data efficiency for an AAAI publication.
- Designed and implemented a novel self-supervised learning framework for multi-modal medical image segmentation, reducing annotation requirements by approximately 30%.
- Achieved significant performance improvements in segmentation tasks, demonstrating enhanced robustness and generalization across diverse datasets.
- Contributed to a research publication presented at AAAI 2023, showcasing innovative approaches to medical image analysis and self-supervised learning.
### Research Intern | Tencent AI Lab
https://ai.tencent.com/ailab/en/index
Explored and implemented disentangled representation learning for medical image analysis, enhancing interpretability and diagnostic accuracy of AI models, leading to a BMVC publication.
- Developed a novel disentangled representation learning framework for medical image analysis, improving model interpretability and diagnostic accuracy by 7%.
- Implemented deep learning models to effectively separate distinct explanatory factors in medical images, facilitating more precise analysis.
- Contributed to a peer-reviewed publication at BMVC 2021, showcasing innovative research in explainable AI for healthcare applications.

## Education
### University of California, San Diego | Computer Science
https://www.ucsd.edu/
### University of California, San Diego | Computer Science
https://www.ucsd.edu/
### University of California, San Diego | Computer Science
3.96/4.00 | https://www.ucsd.edu/

## Awards
### CSE Department Fellowship
University of California, San Diego | 2021-09-01
Awarded for outstanding academic excellence and research potential within the Computer Science and Engineering Ph.D. program.
### Dean's List
University of California, San Diego | 2017-09-01
Recognized for exceptional academic achievement across multiple quarters during undergraduate studies.

## Publications
### Multi-modal Representation Learning for Chest X-ray Analysis
MICCAI (Medical Image Computing and Computer Assisted Intervention) | https://yiyuzhuang.github.io/publication/zhuang2023multi
Proposed a new multi-modal learning framework that effectively combines visual and textual information from chest X-rays to enhance diagnostic accuracy and clinical utility.
### Learning to Segment Medical Images without Annotations
AAAI (Association for the Advancement of Artificial Intelligence) | https://yiyuzhuang.github.io/publication/zhuang2023learning
Developed a novel self-supervised learning framework for multi-modal medical image segmentation, significantly reducing the need for manual annotations and improving model generalization.
### Disentangled Representation Learning for Medical Image Analysis
BMVC (British Machine Vision Conference) | https://yiyuzhuang.github.io/publication/zhuang2021disentangled
Introduced a novel disentangled representation learning approach to improve interpretability and diagnostic performance in complex medical image analysis tasks.

## Languages
- English
- Chinese

## Skills
### Machine Learning & AI
- Deep Learning
- Computer Vision
- Multi-modal Learning
- Federated Learning
- Self-supervised Learning
- Explainable AI
- Medical Image Analysis
- Transfer Learning
- Representation Learning
- Generative Models
- Uncertainty Quantification
### Programming Languages
- Python
- C++
- MATLAB
### Frameworks & Libraries
- PyTorch
- TensorFlow
- scikit-learn
- OpenCV
- NumPy
- Pandas
### Tools & Platforms
- Git
- LaTeX
- Linux
- Docker
- Jupyter Notebook
### Research & Data Analysis
- Scientific Writing
- Data Analysis
- Experimental Design
- Model Evaluation
- Literature Review
- Statistical Analysis

## Source
Read this profile on Hello.cv: https://hello.cv/yiyuzhuang
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