I am broadly interested in learning and intelligence, both algorithmic and biological. My current research interest focuses on understanding the principles of scalability through the following questions:

• What properties does an algorithm need to have to scale in terms of task performance and energy consumption?
• Why do the current deep learning architectures work so well?
• How can we design algorithms that can take scaling to the next level, approaching biological levels of intelligence?
• How can we learn from biology about principles of scalability and use them?

Much of my work derives inspiration from neuroscience and biology in the quest to build a better and more general artificial intelligence.