Erik Waingarten

Erik Waingarten is an assistant professor at the University of Pennsylvania in the Computer and Information Science department. His research focuses on algorithms for massive datasets, including similarity search, streaming/sketching, property testing, and distribution testing.

• Former postdoctoral researcher at Stanford's CS Department under Moses Charikar
• PhD from Columbia University advised by Xi Chen and Rocco Servedio

Key research areas:

• High-dimensional geometry
• Streaming algorithms
• Property testing
• Sketching techniques
• Clustering and metric optimization

Recent article trends show expertise in:

• 2025 publications on monotonicity testing and metric property analysis
• 2024 work on Earth Mover's Distance and kernel evaluations
• 2023 papers on clustering, optimal transport, and MST algorithms
• 2022-2020 foundations in sublinear algorithms and entropy estimation

Scientific recognition:

• NSF CAREER Award (2023)
• CCC Best Paper Award (2017)
• Invited to Journal of the ACM (2017)

Academic advising includes PhD students:

• Ashwin Padaki
• Tian Zhang
• Nicolas Menand
• Krish Singal
• Junkai Song