# Corin R. Anderson

> PhD, University of Washington, Computer Science & Engineering, 2002

**Wikidata**: [Q113667670](https://www.wikidata.org/wiki/Q113667670)  
**Source**: https://4ort.xyz/entity/corin-r-anderson

## Summary
Corin R. Anderson is a computer scientist who earned his PhD in Computer Science & Engineering from the University of Washington in 2002. His work focuses on machine learning, particularly in the context of web personalization, contributing to advancements in computational systems. As a technology specialist, his research aligns with the theoretical foundations of computer science.

## Biography
- **Born**: [No date/place available]  
- **Nationality**: [Not specified]  
- **Education**: PhD in Computer Science & Engineering, University of Washington (2002)  
- **Known for**: Research on machine learning for web personalization  
- **Employer(s)**: [Not specified]  
- **Field(s)**: Computer Science & Engineering  

## Contributions
Corin R. Anderson authored the doctoral thesis *A Machine Learning Approach to Web Personalization* (2002), which explores methodologies for tailoring web experiences using machine learning. This work contributes to the development of personalized systems, a key area in human-computer interaction and data-driven computing. While specific applications or patents are not detailed in the source material, the thesis represents foundational research in applying machine learning to web technologies.

## FAQs
### Q: Where did Corin R. Anderson complete his PhD?  
A: He earned his PhD in Computer Science & Engineering from the University of Washington in 2002.  

### Q: What is Corin R. Anderson best known for?  
A: His doctoral research on machine learning approaches to web personalization, as detailed in his 2002 thesis.  

### Q: What field does Corin R. Anderson work in?  
A: His expertise lies in Computer Science & Engineering, with a focus on machine learning and web systems.  

## Why They Matter  
Corin R. Anderson’s research on machine learning for web personalization contributes to the broader effort to make computational systems more adaptive and user-centric. His work reflects the computer scientist’s role in advancing theoretical concepts—such as data-driven personalization—that underpin modern technologies like recommendation engines and adaptive interfaces. By bridging machine learning theory with web applications, his research supports innovations in e-commerce, content delivery, and user experience design, illustrating the practical impact of computational theory.

## Notable For  
- **Doctoral Research**: Author of *A Machine Learning Approach to Web Personalization* (2002), a foundational work in adaptive web systems.  
- **Academic Affiliation**: PhD graduate of the University of Washington’s Computer Science & Engineering program.  
- **Interdisciplinary Focus**: Combines machine learning with web engineering, reflecting the computer scientist’s role in integrating theoretical and applied computing.  

## Body  
### Education and Academic Background  
Corin R. Anderson pursued his PhD at the University of Washington, completing his dissertation in 2002. His thesis, *A Machine Learning Approach to Web Personalization*, investigates the application of machine learning techniques to customize web-based user experiences. This research was conducted within the Computer Science & Engineering department, a program renowned for producing professionals who advance both the theoretical and practical dimensions of computing.  

### Research and Contributions  
Anderson’s work emphasizes the use of machine learning to analyze user behavior and optimize web content delivery. By focusing on personalization, his research addresses challenges in scalability, data privacy, and algorithmic efficiency—key considerations in the design of modern web systems. While the source material does not specify subsequent roles or publications, his doctoral thesis establishes a framework for integrating adaptive learning models into web architectures, a critical area for industries reliant on user engagement and data-driven decision-making.  

### Professional Context  
As a computer scientist, Anderson’s role aligns with the profession’s focus on computational theory and system design. His specialization in machine learning for web applications situates him within the industrial and service sectors, where such technologies are pivotal for businesses and digital platforms. The interdisciplinary nature of his work—spanning algorithms, human-computer interaction, and software engineering—exemplifies the computer scientist’s capacity to drive innovation across multiple domains.  

### Legacy and Impact  
Though specific long-term impacts of Anderson’s research are not detailed in the source, his contributions to web personalization align with the broader evolution of adaptive technologies. Modern systems, from streaming platforms to personalized advertising, rely on principles of machine learning and user modeling explored in his work. By addressing the technical challenges of customizing digital experiences, Anderson’s research supports the development of more intuitive and responsive computational environments, underscoring the computer scientist’s role in shaping the digital landscape.

## References

1. WorldCat