- "Approximating High-Dimensional Earth Mover's Distance as Fast as Closest Pair" (FOCS 2025)
- "Faster Estimation of the Average Degree of a Graph Using Random Edges and Structural Queries" (SODA 2026)
- "Feature Selection and Junta Testing are Statistically Equivalent" (SODA 2026)
- "Approximate Earth Mover's Distance in Truly-Subquadratic Time" (STOC 2024)
- "Better Sum Estimation via Weighted Sampling" (SODA 2022), Best Student Paper Award
- More publications available in the detailed list
Research Experience
Herman Goldstine postdoctoral fellow at IBM Cambridge, MA, hosted by Kenneth Clarkson; spent a year at UC Santa Cruz hosted by Vaggos Chatziafratis.
Education
PhD: BARC, University of Copenhagen, supervised by Mikkel Thorup and Mikkel Abrahamsen; Undergraduate: Scuola Normale Superiore, Pisa.
Background
Research interests: Designing efficient algorithms for processing large and high-dimensional datasets. Specializations: Sublinear algorithms, high-dimensional geometry.