Google Research

Francois Belletti


Sequential modeling has been my focus and passion for some years and now that I am done with grad school I am very excited about working on related real world problems as part of SIR. After a first MSc on stochastic calculus at Ecole Polytechnique in Paris, I studied distributed systems as part of a MSc at Imperial College London before my PhD in CS at Berkeley. Throughout all of this, my main preoccupation has been how to use continuous time modeling for time series to account for asynchronous observations while enabling scalability. I am particularly focused on alternate representations such as frequency domain or time/frequency and how these can be used as part of large scale ML and deep learning for time series analysis and control.

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