Beinan Wang: Data Access Patterns in AI and Analytics

Join us for the USF Data Science Speaker Series featuring Dr. Beinan Wang on Friday, November 17th at 12:30 PM. 📆

Dr. Beinan Wang is a Senior Staff Software Engineer at Alluxio and a TSC of PrestoDB. Prior to Alluxio, he was the Tech Lead of the Presto team at Twitter, and he built large-scale distributed SQL systems for Twitter’s data platform. He has twelve years of experience working on performance optimization, distributed caching, and volume data processing. He received his Ph.D. in computer engineering from Syracuse University on the symbolic model checking and runtime verification of distributed systems.

The increasing popularity of AI and analytics has led to a dramatic increase in the volume of data used in these fields, creating a growing need for enhanced computational capability. It is important to note that AI and analytics workloads have different data access patterns, requiring different cache strategies.
In this talk, Beinan will share his observations on data access patterns in the AI and analytics domains based on practical experience with large-scale systems in open source. He will also discuss the evaluation results of various caching strategies for AI and analytics and provide caching recommendations for different use cases.

• Data access patterns for analytics workloads
• Data access patterns for AI workloads
• Caching strategies to address different data access patterns
• Adaptive caching admission and eviction policies
• Best practices from big internet companies, including Uber, Meta and Tiktok

Mark your calendars and get ready to explore the world of data science! 📊👨‍💻

#USFDataScienceSpeakerSeries #DataScience #MSDS #DataInstitute #AI #Analytics