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Antonio Orvieto

Antonio Orvieto

Antonio studied Control Engineering in Italy and Switzerland. He holds a PhD in Computer Science from ETH Zürich and spent time at Google DeepMind (UK), Meta (US), MILA (CA), INRIA (FR), and HILTI (LI). He is currently a Hector Endowed Fellow and Principal Investigator (PI) at the ELLIS Institute Tübingen and Independent Group Leader of the MPI for Intelligent Systems, where he leads the Deep Models and Optimization group. He received the ETH medal for outstanding doctoral theses and the Schmidt Sciences AI2050 Early Career Fellowship.

In his research, Antonio strives to improve the efficiency of deep learning technologies by pioneering new architectures and training techniques grounded in theoretical knowledge. His work encompasses two main areas: understanding the intricacies of large-scale optimization dynamics and designing innovative architectures and powerful optimizers capable of handling complex data. Central to his studies is the exploration of innovative techniques for decoding patterns in sequential data, with implications for biology, neuroscience, natural language processing, and music generation.

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