Postdoctoral Researcher
BARC
University of Copenhagen
Email: andersaamanda@gmail.com
Hi! I'm a postdoc at the University of Copenhagen at BARC (Basic Algorithms Research Copenhagen). I am on the job market this year!
Before arriving here, I was a postdoc at MIT where I was fortunate to be working with Piotr Indyk and his clever students. I completed my PhD at the University of Copenhagen under the supervision of Mikkel Abrahamsen and Mikkel Thorup .
Below you will find an overview of my research interest as well as a list of publications

Research Interests
I'm broadly interested in theoretical computer science. Lately, I've been occupied with problems within differential privacy, learning-augmented algorithms, distribution testing, and hashing. I also enjoy working on various problems within graph theory and computational geometry.
What's New?
Below are preprints of some of my recent papers in submission.
- Differentially Private Gomory-Hu Trees
Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrović, Yuriy Nevmyvaka,
Sandeep Silwal, Yinzhan Xu
In Submission
- Near-Optimal Trace Reconstruction for Mildly Separated Strings
Anders Aamand, Allen Liu, Shyam Narayanan
In Submission
- Hashing for Sampling-Based Estimation
Anders Aamand, Ioana O. Bercea, Jakob Bæk Tejs Houen, Jonas Klausen, Mikkel Thorup
In Submission
Publications
A list of my publications can also be found on DBLP and Google Scholar.
Machine Learning and Learning-Augmented Algorithms
- Improved Frequency Estimation Algorithms with and without Predictions
Anders Aamand, Justin Y. Chen, Huy Lê Nguyễn, Sandeep Silwal, Ali Vakilian
Spotlight presentation at NeurIPS 2023
- Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with
Graph Neural Networks
Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld,
Nicholas Schiefer, Sandeep Silwal, Tal Wagner
NeurIPS 2022
- (Optimal) Online Bipartite Matching with Degree Information
Anders Aamand, Justin Y. Chen, Piotr Indyk
NeurIPS 2022
Hashing-Based Algorithms and Data Structures
- Statistical-Computational Trade-offs for Density Estimation
Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Haike Xu
NeurIPS 2024
- Data Structures for Density Estimation
Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal
ICML 2023
- No Repetition: Fast and Reliable Sampling with Highly Concentrated Hashing
Anders Aamand, Debarati Das, Evangelos Kipouridis, Jakob B. T. Houen, Peter M. R. Rasmussen, Mikkel Thorup
PVLDB 2022
- Load Balancing with Dynamic Set of Balls and Bins
Anders Aamand, Jakob B. T. Houen, Mikkel Thorup
STOC 2021
- Fast hashing with Strong Concentration Bounds
Anders Aamand, Jakob B. T. Houen, Mathias B. T. Knudsen, Peter M. R. Rasmussen, Mikkel Thorup
STOC 2020
- Non-Empty Bins with Simple Tabulation Hashing
Anders Aamand, Mikkel Thorup
SODA 2019
- Power of d Choices with Simple Tabulation
Anders Aamand, Mathias B. T. Knudsen, Mikkel Thorup
ICALP 2018
(Computational) Geometry
- Tiling with Squares and Packing Dominos in Polynomial Time
Anders Aamand, Mikkel Abrahamsen, Thomas Ahle, Peter M. R. Rasmussen
Transactions on Algorithms 2023 (appeared at SoCG 2022)
- Online Sorting and Translational Packing of Convex Polygons
Anders Aamand, Mikkel Abrahamsen, Lorenzo Beretta, Linda Kleist
SODA 2023
- Classifying Convex Bodies by their Contact and Intersection Graphs
Anders Aamand, Mikkel Abrahamsen, Jakob B. T. Houen, Peter M. R. Rasmussen
SoCG 2021
- Disks in Curves of Bounded Convex Curvature
Anders Aamand, Mikkel Abrahamsen, Mikkel Thorup
American Mathematical Monthly 2020
Graph Algorithms
- Optimal Decremental Connectivity in Non-Sparse Graphs
Anders Aamand, Adam Karczmarz, Jakub Łącki, Nikos Parotsidis, Peter M. R. Rasmussen, Mikkel Thorup
ICALP 2023 - One-Way Trail Orientations
Anders Aamand, Niklas Hjuler, Jacob Holm, Eva Rotenberg
ICALP 2018
Broader Algorithmic Research
- A Constant-Factor Approximation for Individual Preference Stable Clustering
Anders Aamand, Justin Y. Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert, Ali Vakilian, Fred Zhang
Spotlight presentation at NeurIPS 2023
Miscellaneous
- Improved Space Bounds for Learning with Experts
Anders Aamand, Justin Y. Chen, Huy Lê Nguyễn, Sandeep Silwal
ACDA 2023 (poster) - On Sums of Monotone Random Integer Variables
Anders Aamand, Noga Alon, Jakob Bæk Tejs Knudsen, Mikkel Thorup
Electronic Communications of Probability 2022