Area of research
Cognitive Neuroscience · Artificial Intelligence
Research interest
Research interests include Neural dynamics and brain function, Neural Networks and Applications, Neural Networks and Reservoir Computing, and Advanced Memory and Neural Computing.
Computation-through-Dynamics Benchmark: Simulated datasets and quality metrics for dynamical models of neural activity
Flexible multitask computation in recurrent networks utilizes shared dynamical motifs
Individual variability of neural computations underlying flexible decisions
Catalyzing next-generation Artificial Intelligence through NeuroAI
The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks
One dimensional approximations of neuronal dynamics reveal computational strategy
Cell-type-specific population dynamics of diverse reward computations
Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition
Computation Through Neural Population Dynamics
Organizing recurrent network dynamics by task-computation to enable continual learning
UCL Discovery (University College London) 2020cited by 51position: last
Inferring single-trial neural population dynamics using sequential auto-encoders
Task-driven convolutional recurrent models of the visual system
Lirias (KU Leuven) 2018cited by 36position: middle
The Largest Response Component in the Motor Cortex Reflects Movement Timing but Not Movement Type
Making brain–machine interfaces robust to future neural variability
Context-dependent computation by recurrent dynamics in prefrontal cortex