Mihail Stoian

"The open problems in computer science are my daily bread."

I am first-year PhD student in the UTN Data Systems Lab, advised by Andreas Kipf. My main interest is in query optimization for cloud databases.

Previously, I worked as a student research assistant in the TUM database group (Prof. Thomas Neumann) and in the DAML group (Prof. Stephan Günnemann).

During my studies I did two industry internships at Oracle Labs and Amazon Redshift.

Whenever I see a problem in other areas that is similar to a database problem, I cannot leave it unsolved (see my blog).

news

No news so far...

latest posts

Apr 23, 2022 Displaying External Posts on Your al-folio Blog

selected publications

  1. Group Privacy Amplification and Unified Amplification by Subsampling for Rényi Differential Privacy
    Jan Schuchardt , Mihail Stoian , Arthur Kosmala , and 1 more author
    2024
    arXiv
  2. On the Optimal Linear Contraction Order of Tree Tensor Networks, and Beyond
    Mihail Stoian , Richard M. Milbradt , and Christian B. Mendl
    2023
    arXiv Code
  3. VLDB
    Benchmarking learned indexes
    Ryan Marcus , Andreas Kipf , Alexander Renen , and 5 more authors
    Proceedings of the VLDB Endowment, 2020
    arXiv HTML Code
  4. ML4Systems @ NeurIPS
    SOSD: A Benchmark for Learned Indexes
    2019
    arXiv Code
  5. SIGMOD
    Concurrent Link-Cut Trees
    Mihail Stoian
    In Proceedings of the 2022 International Conference on Management of Data , 2022
    HTML Code
  6. SIGMOD
    Faster FFT-based Wildcard Pattern Matching
    Mihail Stoian
    In Companion of the 2023 International Conference on Management of Data , 2023
    HTML Code
  7. SIGMOD
    Fast Joint Shapley Values
    Mihail Stoian
    In Companion of the 2023 International Conference on Management of Data , 2023
    HTML Code
  8. aiDM
    RadixSpline: A Single-Pass Learned Index
    2020
    arXiv Code
  9. AIDB
    Towards Practical Learned Indexing
    2021
    arXiv Code