CV

Work experience

  • Research Scientist in AI alignment, DeepMind (2016-present)
    • Research on ensuring that advanced AI systems that try to do what we want them to do
  • Software Engineering Intern, Google (2015)
    • Developed and implemented machine learning algorithms for the Knowledge Graph
  • Decision Support Engineering Intern, Google (2013)
    • Built statistical models of the impact of ads quality on click-through rate in R
  • Teaching Fellow in Statistics, Harvard University (2012-2013)
  • Quantitative Analyst Intern, D.E.Shaw & Co (2012)
    • Developed and tested risk modeling algorithms using statistical and numerical optimization methods in Python
  • Summer Research Analyst in Computer Science, University of Toronto (2009)
  • Teaching Assistant in Mathematics, University of Toronto (2007-2011)

Education

  • Harvard University, PhD, Statistics (2016)
  • University of Toronto, MS, Statistics (2011)
  • University of Toronto, Honors BS with High Distinction (GPA 3.76/4.00), Statistics / Mathematics (2010)

Service

Organizing

Reviewing

  • ICML conference (2023)
  • NeurIPS conference (2022)
  • ICLR conference (2022)
  • NeurIPS conference (2021)
  • NeurIPS conference (2020)
  • JMLR (2020)
  • ICML conference (2019)
  • NeurIPS conference, top 30% of reviewers (2018)
  • ICML conference (2018)
  • AI, Ethics & Society (AIES) conference (2018)
  • Women in ML (WiML) workshop (2016-2017)

Other

Competitions

  • IMO Silver medal, International Mathematical Olympiad (2006)
  • Elizabeth Lowell Putnam Prize (2008)
    • Highest ranking woman in the Putnam mathematics competition in North America
  • University of Toronto Putnam mathematics competition team (2006-2009)
    • 3-person team consistently ranked in top 10 in North America
  • ACM programming competition team (2007-2008)
    • 3-person team competed on the regional level in North America