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Tiberiu Teșileanu

Multi-level quantitative modeling of biological systems

I am interested in a variety of biological topics, with a particular emphasis on neuroscience. I study learning and the transfer of information between different brain areas at the circuits level, using models based on artificial neural networks. I use population dynamics models to investigate the adaptive immunity of bacteria against phage.

I have recently started working on understanding odor representations in the piriform cortex in mice. Another collaboration I recently joined focuses on analyzing the statistics of textures in visual scenes, and how these may differ between objects and non-objects.

In the past, I have worked on inferring functional and structural information about proteins by analyzing the statistics of multiple sequence alignments. I have also worked on modeling the transcriptional regulation of gene expression using thermodynamically-motivated models.

In a different life, I have worked in theoretical high-energy physics, focusing on various aspects of the AdS/CFT duality in string theory.

Neural net with nearest-neighbor interactions and STDP

each blob is a leaky integrate-and-fire neuron
redness indicates membrane voltage and spiking
neurons are noisy
there are synapses with all 8 neighbors
synapses are plastic with a timing-dependent rule
use mouse or touch to input a Gaussian-profile current into the net