A subset of my research interests:
1) Neural Computation:
- Explore the computational capabilities of individual neurons and neural circuits.
- develop a coherent terminology for describing the assembly and integratian of neurons in constructing these circuits.
2) Deep Reinforcement Learning:
Leverage insights from psychology and neuroscience, with a specific emphasis on memory formation, memory consolidation, and learning, to enhance deep reinforcement learning.
3) Biologically-Inspired Algorithms:
Examine the biological underpinnings of learning and apply this knowledge to improve deep reinforcement learning and reinforcement learning algorithms.
See: "Bio-Inspired Hashing for Unsupervised Similarity Search" and "Neuronal Circuit Policies" and "Reinforcement Learning Fast and Slow"