• The University of Western Australia (M468), 35 Stirling Highway, Room 1.48, 7 Fairway, Crawley campus

    6009 Perth


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Personal profile


Over the last 25 years, I have been investigating the formation and evolution of galaxies and star clusters using my original astrophysical computer simulations. I have led many small and medium-sized theoretical astrophysics  projects (e.g., origins of the Magellanic Clouds, environmental effects on galaxies etc),  which have ended up with 130 first-author refereed publications so far.

I have been also involved in many national and international observational projects in order to compare my original simulations with these observations. Recently, I have started a new theoretical project that combines supercomputer simulations with the latest AI (artificial intelligence) technologies such as deep learning (``AIverse project'').

I have supervised many undergraduate, postgraduate, and international students at three universities in two countries over the last 20 years. Currently I am supervising postgraduate students from different departments,  i.e., not only astronomy and physics,  but also electric engineering, mechanical engineering, computer science, and data science, for the application of AI to astronomical research.

I have been collaborating with robotics companies and AI startups in order to make the most of the latest robotics and AI technologies in teaching and researching.


My research can be divided into the following three categories. First (most recent) is the application of AI (artificial intelligence) to astrophysical problems. Second is  to create star clusters and galaxies using the latest supercomputer simulations of these objects. Third is to provide theoretical predictions from my original simulations for ongoing and future observational projects.

Current projects

1. The AIverse project (AI + Universe):

This project aims to understand the physical properties of star clusters and galaxies through novel applications of AI (artificial intelligence) to astronomical data sets. One of the main goals is to derive the total masses of dark matter, morphological types, and stellar and gas kinematics using deep learning. Currently, 8 postgraduate students are working with me on this project.

2. Star-by-star computer simulations of globular cluster formation:

Using the latest supercomputer simulations of globular clusters (e.g., OzSTAR), I am now investigating how globular clusters consisting of millions of stars can be formed in the early universe. One of the major goals is to understand the key physical processes that govern the observed internal abundance spreads in globular clusters based on the results of the simulations.


3. Involvements in observational projects:

I am currently involved in several large national and international observational projects led by Australian and international (e.e., Europe, USA, UK, and Japan) astronomers. My job is to provide the latest theoretical predictions from the above theoretical works for the core memebers of the projects.

Teaching overview

Over the last 10 years,  I have been teaching galactic dynamics for postgraduate students.

Industrial relevance

1.  Astronomy with robotics

I have been collaborating a few world-leading robotics companies such as ST Solutions Australia and Softbank robotics in order to convert humanoid robots into "robot astronomers" that can teach astronomy to students and do some simple astronomy tasks.

2.  Computer simulations for animation in TV show

I have made a number of animations of galaxies that were used in science TV shows (e.g., Cosmic Front by NHK,  ABC news etc). These animations are created using the real simulation data from my research. I am still interested in creating these animations with industories.

Industry keywords

  • Space
  • Education

Research expertise keywords

  • Artificial intelligence
  • Robotics
  • Astronomy
  • Machine learning / deep learning
  • Supercomputer simulations and modelling


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