PhD in Computer Science from Universidade Estadual Paulista (Unesp), under the supervision of Prof. Felipe Fanchini, with an abroad period at the University of Rochester, in New York, USA. During his PhD, he also worked as a visiting researcher at the Universidad de Chile and Bahcesehir University, in Turkey. He holds a Bachelor's degree in Physics and a Bachelor's degree in Materials Physics, both from Unesp. His research interests include Classical and Quantum Machine Learning, with a focus on their applications to Quantum Information Science, as well as Generative Artificial Intelligence. (Source: Lattes Curriculum)
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Quantum computing and machine learning have emerged as promising technologies capable of transforming various sectors of society. The fusion of these disciplines has given rise to the field of Quantum Machine Learning (QML), which aims to explore the synergies between quantum theory and machine learning methods to solve complex problems more efficiently. Specifically, anomaly detection, e…
This project aims to work a methodology that can quickly and efficiently bring information about the quantum phase transitions considering arbitrary models. We will focus on various artificial intelligence techniques. One of our objectives is to determine if classifiers trained in simplistic models are able to detect the transitions of more complex models. In addition, through characteris…
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