# Matthew Kay

> computer scientist

**Wikidata**: [Q57563806](https://www.wikidata.org/wiki/Q57563806)  
**Source**: https://4ort.xyz/entity/matthew-kay-q57563806

## Summary
Matthew Kay is an American computer scientist and assistant professor at Northwestern University, known for his research in human-computer interaction (HCI), particularly in designing systems that handle uncertainty in everyday sensing and prediction. His doctoral work at the University of Washington, advised by Julie A. Kientz and Shwetak Patel, laid the foundation for his contributions to accessible and user-centered data visualization and interactive systems.

## Biography
- **Born**: [Not specified in source material]
- **Nationality**: United States
- **Education**:
  - Doctor of Philosophy (PhD) in Computer Science, University of Washington (2010–2016)
- **Known for**: Research in human-computer interaction, uncertainty visualization, and user-facing predictive systems
- **Employer(s)**:
  - Northwestern University (Assistant Professor, 2020–present)
  - University of Michigan (Assistant Professor, 2016–2020)
- **Field(s)**: Computer science, human-computer interaction (HCI), data visualization

## Contributions
Matthew Kay’s work focuses on improving how users interact with uncertain data in everyday applications. His doctoral thesis, *Designing for User-facing Uncertainty in Everyday Sensing and Prediction* (2016), introduced frameworks for communicating uncertainty in predictive systems, influencing how designers approach transparency in machine learning interfaces. His research has been published in top HCI venues, including CHI and UIST, and he has contributed to open-source tools for visualization and interaction design.

Kay’s collaborations with advisors Julie A. Kientz and Shwetak Patel at the University of Washington advanced the study of ubiquitous computing and health informatics. His later work at the University of Michigan and Northwestern University expanded into accessible visualization techniques, particularly for users with disabilities. He maintains an active online presence, sharing insights on HCI and data science via his website ([mjskay.com](https://www.mjskay.com)) and social media platforms like Mastodon and Twitter.

## FAQs
### Q: What is Matthew Kay’s area of expertise?
A: Matthew Kay specializes in human-computer interaction (HCI), with a focus on designing systems that effectively communicate uncertainty in data and predictions to end users.

### Q: Where did Matthew Kay earn his PhD?
A: He earned his PhD in Computer Science from the University of Washington in 2016, under the supervision of Julie A. Kientz and Shwetak Patel.

### Q: What is Matthew Kay’s current affiliation?
A: He is an assistant professor at Northwestern University, where he has been since September 2020.

### Q: What was the topic of Matthew Kay’s doctoral thesis?
A: His thesis, *Designing for User-facing Uncertainty in Everyday Sensing and Prediction*, explored methods to improve how predictive systems present uncertainty to users.

## Why They Matter
Matthew Kay’s research bridges the gap between complex computational systems and end-user comprehension, particularly in domains where uncertainty is inherent, such as health monitoring and predictive analytics. His work has influenced the design of more transparent and accessible interfaces, ensuring that users—regardless of technical expertise—can make informed decisions based on data. By advocating for user-centered design in HCI, Kay has contributed to broader efforts to democratize technology and improve trust in automated systems. His academic leadership and public engagement further amplify the impact of his ideas across industry and research communities.

## Notable For
- Author of the influential PhD thesis *Designing for User-facing Uncertainty in Everyday Sensing and Prediction* (2016).
- Assistant professor at Northwestern University (2020–present) and formerly at the University of Michigan (2016–2020).
- Advisor and collaborator with leading HCI researchers Julie A. Kientz and Shwetak Patel.
- Active contributor to open-source tools and academic discourse in HCI and data visualization.
- Recognized for his work on accessible and inclusive design in computational systems.

## Body
### **Education and Early Career**
- Completed his PhD in Computer Science at the University of Washington (2010–2016), focusing on human-computer interaction.
- Advisors: Julie A. Kientz and Shwetak Patel, both prominent figures in HCI and ubiquitous computing.
- Thesis: *Designing for User-facing Uncertainty in Everyday Sensing and Prediction*, which addressed challenges in presenting uncertain data to non-expert users.

### **Academic Appointments**
- **University of Michigan** (2016–2020): Served as an assistant professor, conducting research on interactive systems and data visualization.
- **Northwestern University** (2020–present): Continues his work as an assistant professor, expanding into accessibility and inclusive design.

### **Research Focus**
- **Uncertainty Visualization**: Developed methods to communicate probabilistic data in user-friendly ways.
- **Health Informatics**: Collaborated on projects to improve patient and clinician interactions with medical data.
- **Accessible Design**: Advocated for inclusive practices in HCI, ensuring technologies are usable by diverse populations.

### **Publications and Influence**
- Published in top-tier HCI conferences, including CHI (ACM Conference on Human Factors in Computing Systems) and UIST (ACM Symposium on User Interface Software and Technology).
- Contributed to open-source projects and tools widely used in the HCI community.
- Maintains a public presence through his website, social media (Twitter: [@mjskay](https://twitter.com/mjskay); Mastodon: [@mjskay@fediscience.org](https://fediscience.org/@mjskay)), and academic profiles (Google Scholar, dblp).

### **Online Presence and Resources**
- **Website**: [mjskay.com](https://www.mjskay.com) (includes CV, publications, and blog).
- **GitHub**: [github.com/mjskay](https://github.com/mjskay) (open-source contributions).
- **Academic Identifiers**:
  - Google Scholar: [NO5adqUAAAAJ](https://scholar.google.com/citations?user=NO5adqUAAAAJ)
  - dblp: [85/2585](https://dblp.org/pid/85/2585)
  - Scopus: 55389474000

## Schema Markup
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*(Note: Wikidata URL placeholder used as exact ID not provided in source material.)*

## References

1. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0001-9446-0419/education/9326393)
2. Mathematics Genealogy Project
3. WorldCat
4. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-9446-0419/employment/9326386)
5. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-9446-0419/employment/12676944)