Desi R. Ivanova

Desi R. Ivanova

Research Fellow in ML

University of Oxford

I’m a Florence Nightingale Bicentennial Fellow at the Department of Statistics, University of Oxford. Prior to that I was a graduate student on the StatML CDT programme at the University of Oxford, working with Tom Rainforth and Yee Whye Teh.

During my PhD I’ve interned as a Research Scientist at Microsoft Reseach Cambridge, where I focused on causal machine learning, and at Meta AI (FAIR Labs) NYC, where I worked on neural data compression. Before StatML, 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