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🍊 Hi, I’m @ClementineDomine 🍊

I am pursuing a Ph.D. program at The Gatsby Computational Neuroscience Unit under the supervision of Andrew SAXE and Caswell Barry my ambition is to embrace a research career in computational neuroscience. I have a master's degree in Theoretical Physics from the University of Manchester (UK).

🗞️ Publications and Posters

  • 2023 - Cognitive Computational Neuroscience (CCN) Talk (Top 5%) Clémentine C. J. Dominé*, Rodrigo Carrasco* et al, ‘NeuralPlayground: A Standardised Environment for evaluation of Hippocampus and Entorhinal Cortex Models'

  • 2023 - Pre-Print Clémentine C. J. Dominé*, Marco Pegoraro* et al, ‘Geometric Epitope and Paratope Prediction’

  • 2023 - Accepted Talk Cosyne Implement an unsupervised point process model for replay detection of motor sequences in the dorsolateral striatum. Revealed first evidence for off-line consolidation of procedural memory in the dorsolateral striatum. Poster: https://drive.google.com/file/d/1lrTJrj3aGA_D3qDV4HNQCPv8NswaA2Qt/view?usp=sharing

  • 2023 - Accepted Poster Cosyne Clémentine C. J. Dominé, Rodrigo Carrasco* et al, 'NeuralPlayground: A Standardised Environment for evaluation of Hippocampus and Entorhinal Cortex Models'

  • 2022 - Accepted Neurips Exact learning dynamics of in Deep Linear Neural Network with Prior Knowledge. Paper: https://openreview.net/forum?id=58ohTfbDth

👀 I’m interested in ...

I am passionate and fascinated by the complex, flexible and optimized functioning of the brain that is yet left to be understood and characterized. I am particularly interested in studying the neural computational theories at the basis of information processing, learning and memory formation in neuronal networks. I am interested in answering questions such as: How is information from the environment represented by ensembles of neurons? How do the neural networks evolve with learning? How does the brain create, store, and update memories for places and events? I am looking forward to making advances in answering these questions, working at the intersection between theoretical neuroscience research and machine learning. It is my conviction that working on both artificial and biological neural networks in parallel will enable us to move forward faster in the general understanding of their mechanisms.

🌱 I’m currently learning ...

Geometric deep learning, Graph learning.

🌐 Get to know more about me links ...

Google Scholar https://scholar.google.com/citations?user=oVZ0fSYAAAAJ&hl=en

Linkdin https://www.linkedin.com/in/clementine-domine-75a6a2150/

Site web https://clementinedomine.github.io

Twitter https://twitter.com/ClementineDomi6

Art loves science Web https://artlovessciences.github.io

📫 How to reach me

Email [email protected] /[email protected]

Phone +33782510189

Clementine Domine's Projects

awesome-neural-geometry icon awesome-neural-geometry

A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond

neuralplayground icon neuralplayground

The standardised environment for the hippocampus and entorhinal cortex models

ppseq.jl icon ppseq.jl

Neyman-Scott point process model to identify sequential firing patterns in high-dimensional spike trains

seqnmf icon seqnmf

An algorithm for unsupervised discovery of sequential structure

the-turing-way icon the-turing-way

Host repository for The Turing Way: a how to guide for reproducible data science

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