Tommaso D'Orsi

Research Interests

Semidefinite Programming, Spectral Methods, Random Matrices, Robust Statistics, High Dimensional Statistics, Differential Privacy, Augmented-Learning.

Recent & Upcoming Events

• [Sep. 2025] Theory Seminar, Rutgers
• [Sep. 2025] Workshop on Combinatorial Optimization, Cargese
• [Apr. 2025] Charles River Symposium on Privacy, Harvard
• [Mar. 2025] Theory Seminar, University of Milan
• [Oct. 2024] LucaFest, Simons Institute, Berkeley
• [Sep. 2024] Google Research

Recent & Representative Papers [All Papers]

• Tight Differentially Private PCA via Matrix Coherence
  with Gleb Novikov,
  SODA 2026.
• Sparsest cut and eigenvalue multiplicities on low degree Abelian Cayley graphs [arXiv]
  with Chris Jones, Jake Ruotolo, Salil Vadhan and Jiyu Zhang,
  APPROX 2025, invited to the special issue of Theory of Computing.
• Private graphon estimation via sum-of-squares [arXiv]
  with Hongjie Chen, Jingqiu Ding, Yiding Hua, Chih-Hung Liu and David Steurer,
  STOC 2024.
• Private estimation algorithms for stochastic block models and mixture models [arXiv]
  with Hongjie Chen, Vincent Cohen-Addad, Alessandro Epasto, Jacob Imola, David Steurer, and Stefan Tiegel,
  NeurIPS 2023 (spotlight).
• Higher degree sum-of-squares relaxations robust against oblivious outliers [arXiv]
  with Rajai Nasser, Gleb Novikov and David Steurer,
  SODA 2023.
• Fast algorithm for overcomplete order-3 tensor decomposition [arXiv]
  with Jingqiu Ding, Chih-Hung Liu, David Steurer and Stefan Tiegel,
  COLT 2022.
• Robust Recovery for Stochastic Block Models [arXiv]
  with Jingqiu Ding, Rajai Nasser and David Steurer,
  FOCS 2021.
• Sparse PCA: Algorithms, Adversarial Perturbations and Certificates [arXiv]
  with Pravesh Kothari, Gleb Novikov and David Steurer,
  FOCS 2020.