Piotr Indyk

Laboratoire d'Informatique de Paris-Nord

Papers

Total Citations

H-Index

About

Piotr Indyk is a pioneering computer scientist whose research spans computational geometry, high-dimensional algorithms, and data stream processing. He is best known for co-inventing Locality-Sensitive Hashing (LSH), a breakthrough technique that revolutionized approximate nearest neighbor search in high-dimensional spaces, enabling efficient similarity search in massive datasets. His work on sketching and streaming algorithms has fundamentally shaped how we process and query large-scale data, with profound implications for databases, machine learning, and network analysis. Indyk’s contributions are highly influential, with his most-cited papers—such as those on LSH and sublinear-time algorithms—garnering tens of thousands of citations. Among his notable achievements, he received the ACM Doctoral Dissertation Award and the Packard Fellowship, and he is a Fellow of the ACM and the Simons Institute. His early work on geometric pattern matching, including algorithms for segment collections, laid the groundwork for robust geometric data analysis. Indyk’s research continues to inspire new generations of computer scientists, offering elegant solutions to fundamental problems in data-intensive computing.