Martha White
Co-Founder and CEO
Martha is an Associate Professor of Computing Science at the University of Alberta. She is a principal investigator at Amii---the Alberta Machine Intelligence Institute---which is one of the top machine learning centres in the world, and a director of RLAI---the Reinforcement Learning and Artificial Intelligence Lab at the University of Alberta. She has authored more than 65 papers in top journals and conferences, with a focus on developing practical algorithms with both theoretical and empirical support. Martha holds a Canada CIFAR AI Chair and received AIs 10 to Watch in 2020 from the Institute of Electrical and Electronics Engineers (IEEE), the world's largest technical professional organization.
Alden Christianson
Co-Founder
Alden has spent his career scaling organizations and leading teams to tackle complex, enterprise-scale problems. Over a decade within Google’s internal supply chain organization, he managed the introduction and production of a complex array of custom-designed compute, networking, and infrastructure products which power Google’s services. He joined DeepMind in 2017, where he grew and led teams of world class scientists, engineers, and managers to produce impactful novel research. He holds a BCom from the University of Alberta, an MS in Industrial and Operations Engineering from the University of Michigan, and an Advanced Project Management Diploma from Stanford University. He will soon complete a BSc in Computing Science at the University of Alberta.
Adam White
Co-Founder
Adam is an Assistant Professor at the University of Alberta. He is the Director of the Alberta Machine Intelligence Institute, a Principle Investigator of the Reinforcement Learning and Artificial Intelligence Lab at the University of Alberta and holds a Canada CIFAR AI Chair. Previously, Adam was a Staff Research Scientist at DeepMind, from 2017 to 2023. Adam's research is focused on understanding the fundamental principles of learning in young humans, animals, and agents. In addition, Adam's group is deeply passionate about good empirical practices to assess if algorithms are ready for deployment in the real world.
