Publications

• Differentially Private Quasi-Concave Optimization: Bypassing the Lower Bound and Application to Geometric Problems
  with Kobbi Nissim and Chao Yan.
  TPDP 2025
  [arXiv]

• Mildly Accurate Computationally Differentially Private Inner Product Protocols Imply Oblivious Transfer
  with Iftach Haitner, Noam Mazor, Jad Silbak, and Chao Yan.
  Crypto 2025, TPDP 2025 (Oral presentation)
  [arXiv]

• Data Reconstruction: When You See It and When You Don't
  with Edith Cohen, Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim and Uri Stemmer.
  ITCS 2025
  [arxiv], [Video]

• On Differentially Private Subspace Estimation in a Distribution-Free Setting
  NeurIPS 2024,  TPDP 2024
  [arxiv], [Video]

• Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes
  with Naty Peter and Jonathan Ullman.
  COLT 2024,  TPDP 2023
  [arxiv]

• Adaptive Data Analysis in a Balanced Adversarial Model
  with Kobbi Nissim and Uri Stemmer.
  NeurIPS 2023 (Spotlight), FORC 2024
  [arxiv], [Video]

• FriendlyCore: Practical  Differentially Private Aggregation
  with Edith Cohen, Haim Kaplan, Yishay Mansour and Uri Stemmer.
  ICML 2022,  TPDP 2022
  [arXiv], [Slides], [Video], [Google Blog], [Code]

• Highly Efficient OT-Based Multiplication Protocols
  with Iftach Haitner, Nikolaos Makriyannis and Samuel Ranellucci.
  Eurocrypt 2022
  [ePrint]
  
  

• On the Complexity of Two-Party Differential Privacy
  with Iftach Haitner, Noam Mazor and Jad Silbak.
  STOC 2022,  TPDP 2022
  [arXiv], [Slides], [Video]

• Differentially-Private Clustering of Easy Instances
  with Edith Cohen, Haim Kaplan, Yishay Mansour and Uri Stemmer.
  ICML 2021
  [arXiv], [Slides], [Video], [Code]

• Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity
  with Haim Kaplan, Yishay Mansour and Uri Stemmer.
  NeurIPS 2020
  [arXiv], [Slides], [Video]
  
  

• A Tight Parallel Repetition Theorem for Partially Simulatable Interactive Arguments via Smooth KL-Divergence  
  with Itay Berman and Iftach Haitner.
  Crypto 2020
  [arXiv], [Slides], [Video]

• Fair Coin Flipping: Tighter Analysis and the Many-Party Case
  with Niv Buchbinder, Iftach Haitner and Nissan Levi.
  SODA 2017
  [arXiv], [Slides]

• An Almost-Optimally Fair Three-Party Coin-Flipping Protocol
  with Iftach Haitner.
  M.Sc. Thesis
  STOC 2014,  SIAM Journal on Computing  2017
  [arXiv], [Slides], [Video]

Other Works:

• Length preserving compression: marrying encryption with compression
  with Doron Chen, Michael Factor, Danny Harnik and Ronen Kat.
  SYSTOR 2021
  [Patent]

• It Takes Two to #MeToo - Using SGX Enclaves to Build Autonomous Trusted Systems
  with Danny Harnik and Paula Ta-Shma.
  [arXiv], 2018.

• Securing the Storage Data Path with SGX Enclaves
  with Danny Harnik, Doron Chen and Ronen Kat.
  [arXiv], [GitHub], [Blog], 2018.
  
  

• Linux SGX Trust Management Framework
  with Gidon Gershinsky and Danny Harnik.
  [GitHub], [Blog], 2018.

See also my DBLP page and Google Scholar page.