Tom George Grigg

I am broadly interested in developing intelligent technology to benefit people, including (but not limited to) applications of AI/ML in environment science, healthcare & medicine, personal robotics, virtual assistants, and driverless vehicles. To this end, I’m motivated to contribute to both foundational research into machine intelligence, as well as to the ongoing efforts by innovators to turn research into cutting-edge technology.

A brief note on my research interests: I strongly believe that the reinforcement learning paradigm, made sample-efficient and safe by advances in neurosymbolic reasoning and probabilistic learning/uncertainty quantification, will lead us to the robust, continual, and dynamic intelligent systems of the future. As such, my primary interests are in the research and application of:

• Reinforcement learning
• (Neurosymbolic) representation learning
• Probabilistic learning
• Self-supervised learning