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Jan Dubiński is currently pursuing a PhD degree in deep learning at the Warsaw University of Technology. He is a member of the ALICE Collaboration at LHC CERN. Jan has been working on fast simulation methods for High Energy Physics experiments at the Large Hadron Collider at CERN. The methods developed in this research leverage generative deep learning models such as GANs to provide a computationally efficient alternative to existing Monte Carlo-based methods. More recently, he has focused on issues related to the security of machine learning models and data privacy. His latest efforts aim to improve the security of self-supervised and generative methods, which are often overlooked compared to supervised models.

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