Mark Bun
About
Mark Bun focuses on theoretical computer science, including data privacy, computational complexity, cryptography, and the foundations of machine learning. He uses polynomials (continuous functions) to investigate fundamental properties of Boolean (discrete) functions and has also developed new algorithms and lower bound techniques for differentially private data analysis. He spent the 2018–2019 academic year at the Simons Institute for the Theory of Computing at UC Berkeley and joined BU as a tenure-track assistant professor in July 2019.
Research Performance Summary
First Recorded Paper
Weighted Polynomial Approximations: Limits for Learning and Pseudorandomness
Year: 2014
Citations: 7
Venue: arXiv preprint arXiv:1412.2457
Latest Recorded Paper
Enforcing Demographic Coherence: A Harms Aware Framework for Reasoning about Private Data Release
Year: 2025
Citations: 0
Venue: arXiv preprint arXiv:2502.02709
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.