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Computational and Mathematical Intelligence Group

About Us

The Computational and Mathematical Intelligence Group at The School of Mathematics and Statistics, University of Sydney consists of researchers interested in the foundations of machine learning, artificial intelligence and their interactions with other areas. We come from a wide range of backgrounds, and are interested in increasing interdisiplinary connections and collaborations across all research areas interested in computational and mathematical intelligence.

Research Areas

We work on a wide range of mathematical problems

Material

Physics guided Machine Learning

Investigating the combination of traditional Physical models with Machine Learning and AI based models.
Material

Probabilistic Machine Learning

Developing new methods for modelling uncertainty, performing probabilistic inference and making predictions, decisions in uncertain environment
Material

Natural Language Processing

Subfield of linguistics, computer science, information engineering and AI to process and analyse large amounts of natural language data
Material

Information Geometry and Machine Learning

Developing information geometric approaches to Machine Learning
Material

Topological Data Analysis and Machine Learning

Developing approaches for combining Topological Data Analysis and Machine Learning
Material

Time Series, Dynamical Systems and Machine Learnining

Developing Machine Learning models for time series and dynamical systems

Group Members

Our Current Members

  • Lamiae Azizi

    Dr. Lamiae Azizi (Group Leader)

    Research areas: Probabilistic Machine Learning
  • Simon Luo

    Simon Luo (PostDoc)

    Project Name: Probabilistic Graphical Models for Unsupervised Feature Learning
    Research areas: Information Geometry and Machine Learning, Probabilistic Machine Learning
  • Yossi Bokor

    Yossi Bokor (PhD Student)

    Project Name: Machine learning and stratified space learning
    Research areas: Topological Data Analysis, Information Geometry and Machine Learning
  • Nick Miltchinov

    Nick Miltchinov (PhD Student)

    Project Name: Machine Learning for High dimensional Partial differential equations in Micromagnetics
    Research areas: Time Series, Dynamical Systems and Machine Learnining
  • Nick James

    Nicholas James (PhD Student)

    Project Name: Statistical Signal Processing
    Research areas: Time Series, Dynamical Systems and Machine Learnining
  • Matthew Ma

    Matthew Ma (PhD Student)

    Project Name: Machine Learning for Large Scale Knowlege Graph Completion
    Research areas: Probabilistic Machine Learning
  • Alexey Vlaskin

    Alexey Vlaskin (PhD Student)

    Project Name: Semi-supervised learning methods for text classification
    Research areas: Natural Language Processing
  • James Chok

    James Chok (PhD Student)

    Project Name: Orthogonal Machine Learning
    Research areas: Machine Learning in Physical Systems
  • Jenny

    Jenny Dong (PhD Student)

    Project Name: Probabilistic Causal Discovery in Complex Systems
    Research areas: Probabilistic Machine Learning
  • Simon

    Steven Wong (PhD Student)

    Project Name: Machine Learning in Portfolio Management
    Research areas: Probabilistic Machine Learning, Time Series, Dynamical Systems and Machine Learnining.
  • Chris Hyland

    Chris Hyland (Honours Student)

    Project Name: Bayesian model selection and link prediction applied to text documents
    Research areas: Natural Language Processing
  • Tuo Zeng

    Tuo Zeng (Honours Student)

    Project Name: Neural network Gaussian process Inference
    Research areas: Probabilistic Machine Learning
  • Fariza Rashid

    Fariza Rashidy (Honours Student)

    Project Name: Image classification in the lens of Topological Data Analysis and Machine Learning
    Research areas: Probabilistic Machine Learning, Topological Data Analysis

Applications

Ensembling Anomaly Detection Algorithm by Simon Luo.

Collaborators

Katharine Turner

Topological Data Analysis

A/Prof Jennifer Chan

Statistical time series

Dr Jie Yin

Data mining and Machine Learning

A/Prof Eduardo Altmann

Networks and complex systems

Prof Stephan Tillmann

Computational Geometry

Prof Beniamin Goldys

Stochastic PDEs

Dr Geoffrey Vasil

Nonlinear dynamical system

Dr Lionel Ott

ML for autonomous systems

Dr Rafael dos Santos de Oliveira

Bayesian optimisation

Prof Fabio Ramos

ML and Robotics

Alumni

Weichang Yu

PostDoc, University of Melbourne

Contact Us

If you would like to contact us, please email: Lamiae Azizi