Desi R. Ivanova

Desi R. Ivanova

DPhil Student in Statistics

University of Oxford

I’m interested in machine learning and statistics more broadly, particularly Bayesian. Currently, I’m on the StatML programme at the University of Oxford, working with Tom Rainforth and Yee Whye Teh. I spent 2022 on two research internships: first one was at Microsoft Reseach Cambridge, where I focused on causal machine learning; the second one was at Meta AI (FAIR Labs) NYC, where I worked on neural data compression.

Before joining the StatML CDT, I spent four years in quant finance – first in quantitative equity research at UBS and later in cross-asset systematic trading strategies structuring at Goldman Sachs.

For more about my work, see my talks and publications.

  • Probabilistic machine learning, deep generative models
  • Information theory, optimal experimental design, neural compression
  • Statistics and data science
  • Sports
  • DPhil Statistics (StatML programme), 2020-2024

    Univeristy of Oxford

  • Master of Mathematics, Operational Research, Statistics and Economics (MMORSE), 2011-2016

    University of Warwick

  • Mathematics (Erasmus programme), 2014-2015

    LMU Munich

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