Morteza Zadimoghaddam

Morteza Zadimoghaddam

I am a staff research scientist (L6) at Google Zurich office in Switzerland. Previously, I spent 4 years in Google Cambridge, two years in the same Zurich office and 4 years in the New York office where I started my career at Google in January 2014. Prior to Google, I did my PhD in computer science at MIT (CSAIL) under supervision of Professor Erik D. Demaine. I work on applying optimization techniques to various practical problems in order to find provably efficient algorithms. In particular, I apply infrastructure optimization methods to save computational resources at scale. On the mathematical and research side, I am interested in Submodular Optimization and its applications in large scale data mining and machine learning problems.
Authored Publications
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    Google
The Cost of Consistency: Submodular Maximization with Constant Recourse
Paul Duetting
Federico Fusco
Ashkan Norouzi Fard
Ola Svensson
Proceedings of the 57th Annual ACM Symposium on Theory of Computing (2025), 1406–1417
Deletion Robust Non-Monotone Submodular Maximization over Matroids
Paul Duetting
Federico Fusco
Ashkan Norouzi Fard
Journal of Machine Learning Research, 26 (2025), pp. 1-28
Consistent Submodular Maximization
Paul Duetting
Federico Fusco
Ashkan Norouzi Fard
Proceedings of the 41st International Conference on Machine Learning (2024)
Consistent Submodular Maximization
Paul Duetting
Federico Fusco
Ashkan Norouzi Fard
Proceedings of the 41st International Conference on Machine Learning, PMLR (2024), pp. 11979-11991
Consistent Submodular Maximization
Paul Duetting
Federico Fusco
Ashkan Norouzi Fard
Proceedings of the 41st International Conference on Machine Learning, PMLR (2024), pp. 11979-11991
Consistent Submodular Maximization
Paul Duetting
Federico Fusco
Ashkan Norouzi Fard
Proceedings of the 41st International Conference on Machine Learning (2024), pp. 11979-11991
Edge-Weighted Online Bipartite Matching
Runzhou Tao
Zhiyi Huang
Journal of the ACM, 69 (2022), 45:1-45:35
Distributed load balancing: a new framework and improved guarantees
Allen Liu
Binghui Peng
Innovations in Theoretical Computer Science (2021)
Fully Dynamic Algorithm for Constrained Submodular Optimization
Ashkan Norouzi Fard
Jakub Tarnawski
Slobodan Mitrović
NeurIPS 2020 (to appear)