Surbhit Wagle

I am a computational neuroscientist and research scientist with a PhD in Neuroscience, working at the intersection of recurrent and oscillatory neural dynamics, synaptic and intrinsic plasticity, memory, and machine learning. I develop mathematically grounded models of neural and molecular dynamics and translate them into scalable Python and PyTorch simulations.

I am currently a Postdoctoral Research Associate in Prof. Claudia Clopath’s group at Imperial College London. My research includes multi-region recurrent neural networks, Hebbian learning, activity-dependent intrinsic plasticity, representational drift, memory consolidation, and neural population dynamics. I also work on learning-evoked oscillatory dynamics and offline memory reactivation.

My doctoral research, supervised by Prof. Tatjana Tchumatchenko, combined computational models of molecular transport and receptor trafficking with experimental measurements to study mechanisms of synaptic plasticity. I also co-developed SpyDen, an open-source platform for reproducible molecular and structural analysis of neuronal images.

My broader experience spans numerical simulation, statistical modelling, computer vision, high-performance computing, and reproducible research software. Before my PhD, I developed distributed optimisation pipelines and scientific web applications at the National Centre for Biological Sciences and the Institute for Stem Cell Science and Regenerative Medicine in India.