Model Agnostic Differentially Private Causal Inference
The Correlated Gaussian Sparse Histogram Mechanism - FORC 2025
Testing Identity of Distributions under Kolmogorov Distance in Polylogarithmic Space - SOSA25
Better Gaussian Mechanism using Correlated Noise - SOSA25
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition - SaTML 2025
PLAN: Variance-Aware Differentially Private Mean Estimation - PETS 2024
Correlated-Output Differential Privacy and Applications to Dark Pools - AFT 2023
Better Differentially Private Approximate Histograms and Heavy Hitters using the Misra-Gries Sketch - PODS 2023, Distinguished paper, selected for 2023 ACM SIGMOD Research Highlight Awards
Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access - CCS 2021, Poster accepted at TPDP 2021, full version published in the Journal of Privacy and Confidentiality
Research Experience
Was a PhD student and postdoc in the Algorithms Group at the IT University of Copenhagen; also affiliated with the Basic Algorithms Research Copenhagen center and the Providentia Project.
Education
PhD: IT University of Copenhagen, Algorithms Group, supervised by Rasmus Pagh and Martin Aumüller.
Background
Research interest: Design and analysis of differentially private algorithms and data structures. Currently a postdoc in the PreMeDICaL Team at Inria Montpellier, France, working with Aurélien Bellet.
Miscellany
Teaching experience: Fall 2023 - Foundations of Probability; Spring 2021 & 2022 - Algorithmic Problem Solving.