Hi! I'm Yuan Yin 银元

My research focuses on machine learning and deep learning for spatiotemporal sequence modeling, prediction, and analysis of complex behaviors. I also explore methods to extend the generalization of data-driven models, particularly through model adaptation.

I have explored the following directions in the past few years, with a special emphasis on physical dynamical systems:

• physics dynamics modeling with neural networks,
• adaptation and out-of-distribution generalization of neural networks, and
• handling free-form data and predicting phenomena continuously in time and space.

I successfully defended my PhD thesis in June 2023 at Sorbonne Université, supervised by Prof. Patrick Gallinari and Assoc. Prof. Nicolas Baskiotis.

Prior to that, I earned my BSc in Computer Science from Beihang University back in 2016, followed by an MSc in Computer Science from Université Paris Cité (M1 MPRI) and Sorbonne Université (M2 DAC) in 2019.