Moe Amanzadeh

Moe Amanzadeh

Professional Background

Professor Moe Amanzedeh is an award-winning data scientist with over 15 years of experience in technology development and automation. Moe is an expert in statistical modeling, Machine Learning (ML), and Artificial Intelligence (AI) methods in data analysis to develop predictive algorithms, optimization, and decision-making models of complex systems with a track record of commercialized technologies and software packages. He currently works as a Data Scientist in one of the top global companies in the resources industry.

Moe has a Master’s in Electrical Engineering and a Master of Philosophy in Mining Engineering from The University of Queensland in 2011 and 2013; where he finished as a top 1% graduate in all categories. He is currently finalizing his Ph.D. in artificial intelligence applications in mechanical and mining engineering at The University of Queensland; developing revolutionary robotic algorithms for shape sensing using optimization and statistical methods to increase drilling accuracy in mining. Moe was previously a visiting researcher at Max Planck Institute in Germany and San Jose State University.

Moe has been a seasonal academic and project leader at the University of Queensland, Australia, and has extensive public speaking and teaching experience in various engineering courses and international conferences in AI, data science, robotics, and the resources industry.

Academic Degrees

  • Ph.D., Artificial Intelligence Applications in Mechanical and Mining Engineering, The University of Queensland, present
  • M.Phil., Mining Engineering, The University of Queensland, 2013
  • M.E., Electrical Engineering, The University of Queensland, 2011