Winners of a Sapienza Research Call 2024-2025
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@NESYA Andrea Ceschini and I have won a ~5k€ Sapienza Research Call “AQUA-QLEAR: Achieving Quantum Utility and Advantage through Quantum Learning for Enhanced and Accelerated Results”.
I'm a mathematician specialized in Data Science currently pursuing a PhD in Quantum Computing
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Published:
@NESYA Andrea Ceschini and I have won a ~5k€ Sapienza Research Call “AQUA-QLEAR: Achieving Quantum Utility and Advantage through Quantum Learning for Enhanced and Accelerated Results”.
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As discussed in this previous post, the 2025 International Joint Conference on Neural Networks (IJCNN) took place in Rome and our group @NESYA organized a workshop and a special session:
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@NESYA we have have published an article about the impact of NISQ devices on encryption-decryption schemes. Check the associated blog post or the associated materials to know more about this article.
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I’ve presented our work at the 2025 IEEE International Symposium on Circuits and Systems and had very interesting discussions about post-quantum cryptography. Thanks to the orgaizers for the amazing work. You can chek my slides here and here you can find a blog post that summarizes the motivation and context of our results. In this repository you find all the implementations related to the project. As soon as the proceedings of the conference will be published I will also share more details about our findings.
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I have just published a simple educational project that should help the novice to get started with the Google Earth Engine API. The main steps of this project are summarized in the associated Github repository. As a byproduct of the project I have created a new dataset on Kaggle, check it here! This dataset provides geographic and environmental data on different islands from around the world, focusing on their potential for renewable energy generation. It includes information on solar irradiance, wind speeds, and other characteristics useful for sustainability studies and geographic analysis. Since there are not so many public cleaned dataset of this kind I hope it will be usefull.