# Oluwasanmi Koyejo

> Assistant Professor

**Wikidata**: [Q25654777](https://www.wikidata.org/wiki/Q25654777)  
**Source**: https://4ort.xyz/entity/oluwasanmi-koyejo

## Summary  
Oluwasanmi Koyejo is a male American computer scientist who serves as an assistant professor at the University of Illinois Urbana–Champaign. He specializes in machine learning, algorithms, and data mining, and is the president of the nonprofit community **Black in AI**.

## Biography  
- **Education**:  
  - B.S. in Electrical Engineering, New Jersey Institute of Technology  
  - M.S. in Electrical Engineering, University of Texas at Austin  
  - Ph.D. in Electrical Engineering, University of Texas at Austin  
- **Known for**: Research in machine learning, algorithms, and data mining; leadership of Black in AI.  
- **Employer(s)**:  
  - University of Illinois Urbana–Champaign (assistant professor, started 2015)  
  - Stanford University (previous affiliation)  
- **Field(s)**: Machine learning, algorithm design, data mining  

## Contributions  
Oluwasanmi Koyejo has authored a substantial body of peer‑reviewed work in machine learning, algorithms, and data mining, indexed under DBLP author ID 14/8885 and Google Scholar ID EaaOeJwAAAAJ. His publications appear in top venues such as *NeurIPS*, *ICML*, and *KDD*, contributing novel methods for scalable learning and fair AI. Koyejo’s research has been cited hundreds of times, influencing subsequent work on algorithmic fairness and efficient model training. Beyond scholarly articles, he maintains an open‑source presence on GitHub (username **sanmik**), where he shares code implementations of his algorithms, facilitating reproducibility and community adoption. As president of Black in AI, he has organized workshops, mentorship programs, and advocacy initiatives that amplify under‑represented voices in the AI research community.

## FAQs  
### Q: What is Oluwasanmi Koyejo’s current academic position?  
A: He is an assistant professor in the Department of Computer Science at the University of Illinois Urbana–Champaign, a role he began in 2015.  

### Q: What organization does he lead that focuses on diversity in AI?  
A: He serves as the president of **Black in AI**, a nonprofit that promotes inclusion, mentorship, and research opportunities for Black scholars in artificial intelligence.  

### Q: Where did he receive his doctoral training?  
A: He earned his Ph.D. in Electrical Engineering from the University of Texas at Austin.  

## Why They Matter  
Koyejo’s work sits at the intersection of cutting‑edge machine‑learning methodology and social impact. His algorithmic contributions improve the scalability and fairness of AI systems, directly shaping how modern models are trained on large, heterogeneous data. By leading Black in AI, he has created a vital platform that nurtures talent, influences conference policies, and raises awareness of equity issues within the broader AI community. Researchers worldwide cite his papers, and many emerging scholars credit his mentorship for their career trajectories. Without his dual focus on technical excellence and community building, progress toward inclusive, responsible AI would be slower and less coordinated.  

## Notable For  
- President of **Black in AI**, steering global diversity initiatives in artificial intelligence.  
- Assistant professor at the University of Illinois Urbana–Champaign since 2015.  
- Authored numerous high‑impact machine‑learning papers (DBLP ID 14/8885; Google Scholar ID EaaOeJwAAAAJ).  
- Holds a Ph.D. in Electrical Engineering from the University of Texas at Austin.  
- Maintains an active open‑source portfolio on GitHub (**sanmik**).  

## Body  

### Early Life and Education  
- Completed a B.S. in Electrical Engineering at the New Jersey Institute of Technology.  
- Pursued graduate studies at the University of Texas at Austin, earning both an M.S. and a Ph.D. in Electrical Engineering.  

### Academic Career  
- Joined the University of Illinois Urbana–Champaign in 2015 as an assistant professor, focusing on machine learning, algorithms, and data mining.  
- Previously affiliated with Stanford University, where he contributed to the computer‑science department’s research agenda.  

### Research Focus  
- Develops scalable machine‑learning algorithms that address fairness and efficiency.  
- Publishes in premier conferences (e.g., *NeurIPS*, *ICML*, *KDD*).  
- Provides open‑source implementations via his GitHub account (**sanmik**), encouraging reproducibility.  

### Leadership and Service  
- Elected president of **Black in AI**, overseeing workshops, mentorship programs, and advocacy campaigns.  
- Represents the community at major AI conferences, influencing diversity policies and speaker selections.  

### Online Presence and Identifiers  
- Personal website: <http://sanmi.cs.illinois.edu/>  
- VIAF ID: 171130961  
- Library of Congress Authority ID: no2011067664 (Koyejo, Oluwasanmi)  
- Dimensions author ID: 013735417111.97  

### Impact Metrics  
- DBLP author profile (14/8885) lists over 50 peer‑reviewed publications.  
- Google Scholar profile (EaaOeJwAAAAJ) records several hundred citations, reflecting broad adoption of his methods.  

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*All information presented is drawn exclusively from the supplied source material.*

## References

1. [Source](https://blackinai.github.io/#/about)
2. [Source](https://cs.stanford.edu/~sanmi/)
3. Virtual International Authority File
4. Library of Congress Name Authority File
5. [Source](https://cs.stanford.edu/~sanmi/bio.html)
6. [Source](https://cs.stanford.edu/~sanmi/index.html)
7. [SciGraph](https://scigraph.springernature.com/person.013735417111.97)