James Atlas

My research interests are artificial intelligence, machine learning, constraint optimization, distributed and high performance computing, scientific computing, and computer science education. I explore applications in medical data, earth and space exploration, and multi-agent and mobile systems.

My current projects include machine learning models for prediction of health conditions and treatment efficacy, improved optimization for designing and training deep learning networks, adaptive sampling for scientific simulation, uncertainty reasoning for dynamic agent systems, improved curriculum and policies for primary and secondary professional development, service learning partnerships between students and community educators, and gamification of threshold concepts in computer science.

  • Artificial Intelligence: constraint optimization, multi-agent systems
  • CS Education: teacher professional development, service learning
  • Data Science: learning and optimization algorithms for deep networks
  • Scientific Computing: heterogeneous computing, monte carlo tree search
  • Medical Applications: machine learning for imaging and clinical data, smart apps
  • Space Exploration: simulation of trajectories, autonomous agents

For more information about James’s research please visit his University of Canterbury research page.