Brent Smith

Brent Smith is a prominent figure in the field of recommender systems and machine learning at Amazon. Here are some key details about his background and contributions:

Professional Experience

Brent Smith currently holds the position of Sr. Principal Applied Scientist at Amazon.4 He has been with the company for over two decades, playing a pivotal role in developing Amazon's recommendation systems.13

Expertise and Contributions

Recommender Systems:: Smith is renowned for his work on Amazon's item-to-item collaborative filtering algorithm, which revolutionized the company's product recommendations.13 This algorithm was designed to scale to Amazon's massive user base and product catalog, providing high-quality recommendations in real-time.

Research Interests:: His research interests encompass data mining, machine learning, and recommendation systems.36

Leadership Roles:: Throughout his tenure at Amazon, Smith has held various leadership positions:

• He led the Automated Merchandising team36
• He has been involved in applied science efforts at Amazon5

Academic Background

Smith holds a strong academic foundation:

• BS in Mathematics from the University of California, San Diego
• MS in Mathematics from the University of Washington, where he conducted graduate work in differential geometry3

Publications and Influence

Brent Smith has co-authored influential papers in the field of recommender systems:

• "Amazon.com recommendations: Item-to-item collaborative filtering" (2003), which has been cited over 8,800 times1
• "Two decades of recommender systems at Amazon.com" (2017), reflecting on the evolution of Amazon's recommendation technology1

Teaching and Academia

While primarily working in industry, Smith has maintained connections with academia:

• He has been involved in teaching and sharing his industry experience2
• His work has influenced both academic research and practical applications in the field of recommender systems

Brent Smith's contributions have significantly shaped the landscape of personalization and recommendation systems, particularly at Amazon, where his work has directly impacted millions of customers' shopping experiences.