Juliana Ankomah

The researcher focuses on identifying how neural networks learn efficiently under temporal processing conditions, leveraging spiking dynamics while maintaining biological plausibility. Their approach emphasizes analyzing these models computationally, enabling broader exploration of learning principles without requiring extensive human intervention. By bridging the gap between computational and biological systems, their work contributes to a deeper understanding of neural function across scales.