What I look like   Staff Research Scientist


New York, NY

Email: adityakmenon followed by google.com


I'm a Staff Research Scientist at Google. I work on machine learning and its applications.

I completed my honours in Computer Science from the University of Sydney in 2006 under Sanjay Chawla. I completed my PhD in Computer Science from UC San Diego in 2013 under Charles Elkan. From 2013 - 2018, I held positions at NICTA, CSIRO Data61, and the Australian National University, working with Bob Williamson and other inimitable colleagues.

Here is a copy of my CV.

Research interests

I am broadly interested in the design and analysis of machine learning algorithms for (weakly) supervised learning problems occurring in practice. Specific areas of interest include:

Selected publications

Below are a few representative publications. For a full list, see here.

Inspired by Bernard Chazelle's wonderful idea of "liner notes" for his papers, I've included some of my own for a few papers. (Liner notes are not peer-, or even coauthor-reviewed.)
  • Long-tail learning via logit adjustment.
    Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, and Sanjiv Kumar.
    In International Conference on Learning Representations (ICLR), 2021.

  • Can gradient clipping mitigate label noise?
    Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, and Sanjiv Kumar.
    In International Conference on Learning Representations (ICLR), Addis Ababa 2020.

  • Fairness risk measures.
    Robert C. Williamson and Aditya Krishna Menon.
    In International Conference on Machine Learning (ICML), Long Beach, 2019.

  • Bipartite ranking: a risk-theoretic perspective.
    Aditya Krishna Menon and Robert C. Williamson.
    In Journal of Machine Learning Research (JMLR), Volume 17, Issue 195. 2016.
    [pdf] [liner notes]

  • Linking losses for density ratio and class-probability estimation.
    Aditya Krishna Menon and Cheng Soon Ong.
    In International Conference on Machine Learning (ICML), New York City, 2016.
    [pdf] [slides] [poster] [code] [liner notes]