I'm a mathematician specialized in Data Science currently pursuing a PhD in Quantum Computing
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A new app about quantum optimization is available! I have developed a simple tool to solve the MaxCut problem with QAOA. Check the companion repository: github.com/leonardoLavagna/qaoa. To use the app visit quantum-optimization-app.streamlit.app
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Acoording to tradition, also this year we are hosting the Open DIET event where highschool students can join for one day the research teams in our Department in innovative projects and see with their own eyes cutting edge technologies and curren trends in modern electronics, artificial intelligence and quantum computing. This year I will propose a (hopefully fun) project where a student can simulate Classical and Quantum Walks with an Arduino-Based LED System. All the details are in this repository. If you happen to be in Rome in that period, let me know!
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I’m going to present a work on Quantum Cryptography at the 2025 IEEE International Symposium on Circuits and Systems (ISCAS 2025). The title of the talk is “Trade-Offs in Cryptosystems by Boolean and Quantum Circuits” where we have analized the security of cryptosystems based on trapdoor permutations against NISQ attacks. The materials will be available soon, and a preliminary schedule is available here.
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I’ve just joined the Open Sicence Platform Qeios. It is an open-access, open peer review, academic publishing platform. Publishing on Qeios is free and doesn’t rely on editors to accept or reject papers. Instead, reviewers openly evaluate papers after publication, offering feedback to improve the work and guide readers on its quality. This post-publication peer review system allows broad participation, highlighting strong research and limiting the spread of flawed studies, and I believe it to be a kind of alternative to the many flaws current academic publishing has displayed over and over. If you are interested you can check my first contribution on Qeios here.
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The proceedings of the 2024 International Conference on Quantum Techniques in Machine Learning are up! Check here, here and here for the materials related to our presentations.