Fred (Farbod) Roosta
School of Mathematics and Physics
University of Queensland, Brisbane, Australia
International Computer Science Institute, Berkeley, USA

Email: fred.roostauq.edu.au


Research Interests

  • Machine Learning
  • Numerical Optimization
  • Randomized Algorithms
  • Computational Statistics
  • Numerical Analysis and Scientific Computing
  • Numerical Linear Algebra
  • Image Processing and Inverse Problems



  • Feb, 2018:  Our paper on "Out-of-sample extension of graph adjacency spectral embedding" is available on arXiv now.
  • Feb, 2018:  We just posted a paper on arXiv, in which we extend our prior results on non-convex Newton-type methods with inexact Hessian (i.e., this paper), to allow for gradient approximation as well.
  • Feb, 2018:  The code for our paper on GPU-accelerated sub-sampled Newton methods is available here.
  • Feb, 2018:  The code for distributed convex optimization using GIANT is available here.
  • Feb, 2018:  The code for sub-sampled Trust-Region/ARC for large scale non-convex problems is available here.
  • Dec, 2017:  Our paper on accelerated-adaptive gradient based methods, called Flag n' Flare, has been accepted to AISTATS 2018.
  • Dec, 2017:  A short review on different optimization methods for inverse problems is available on arXiv.
  • Nov, 2017:  We just posted a paper on arXiv in which we study some theoretical properties of Rectified MLPs, viewed as kernels, including the invariance of weight distributions as well as some interesting fixed point results.
  • Nov, 2017:  Our paper on establishing a relationship between optimization and local graph clustering just got accepted to Mathematical Programming!


  • Robert Salomone (PhD)
  • Russell (Susumu) Tsuchida (PhD)
  • Rixon Crane (PhD)
  • Yang Liu (MPhil)


I always look for enthusiastic MSc/MPhil/PhD students...
(a) your research interests lie anywhere in the union of Numerical Optimization, Machine Learning, Randomized Algorithms, Computational Statistics, Scientific Computing, or Numerical Linear Algebra,
(b) you are looking to do a MSc/PhD degree in one of the world's leading and highly ranked research universities in beautiful Australia,
then feel free to drop me a line with your current CV and a few words regarding your research/background.

Preprints and Publications




  • Parallel Local Graph Clustering
    Julian Shun, Farbod Roosta-Khorasani, Kimon Fountoulakis and Michael W. Mahoney
    Proceedings of the VLDB Endowment, 9(12), pp. 1041-1052, 2016.



Research Grants

  • Efficient Second-Order Optimisation Algorithms for Learning From Big Data
    Program: Discovery Early Career Researcher Award (DECRA)
    Agency: Australian Research Council (ARC)
    Award Period: Starting in 2018 for 3 years
    Role: PI
  • Robust, Efficient, and Local Machine Learning Primitives
    Program: Data Driven Discovery of Models (D3M)
    Agency: DARPA
    Award Period: Starting in 2017 for 4 years
    Role: coPI

Selected Talks


  • SIAM Annual Meeting

    Pittsburgh, Pennsylvania, July, 2017

  • Matrix Program on Computational Inverse Problems

    Creswick, Australia, June, 2017

  • SIAM Conference on Optimization

    Vancouver, Canada, May, 2017

  • SIAM Conference on Computational Science and Engineering

    Atlanta, Georgia, February, 2017

  • Computational and Methodological Statistics (CMStatistics)

    Seville, Spain, December, 2016

  • Pacific Institute for the Mathematical Sciences (SCAIM Seminar)

    Vancouver, British Columbia, September, 2016

  • Institute of Applied Mathematics (IAM)

    Vancouver, British Columbia, September, 2016

  • Virginia Tech Math Colloquium

    Blacksburg, Virginia, September, 2016

  • SAMSI Program on Optimization (Invited Plenary Talk)

    Research Triangle Park, North Carolina, August, 2016

  • Recent Advances in Randomized Numerical Linear Algebra

    National Institute of Informatics, Shonan Village Center, Japan, July, 2016

  • Workshop on Algorithms for Modern Massive Data Sets (MMDS)

    Berkeley, California, June, 2016

  • SIAM Conference on Uncertainty Quantification

    EPFL, Lausanne, Switzerland, April, 2016

  • Matrix Computations and Scientific Computing Seminar

    Berkeley, California, March, 2016

  • AMPLab (All Hands Meeting)

    Berkeley, California, September, 2015

  • Sparse Representations, Numerical Linear Algebra, and Optimization

    BIRS, Alberta, October, 2014

  • SIAM Conference on Optimization

    San Diego, California, May, 2014

  • Pacific Institute for the Mathematical Sciences (SCAIM Seminar)

    Vancouver, British Columbia, November, 2013