{"query":"software repositories","hops":1,"type":null,"search_terms":"software repositories","graph_context":[{"type":"Software","score":3.541187286376953,"summary":"Java software for extracting and exporting interesting subgraphs for analysis .","entity":{"related_publication_ids":["pub_bachelor_thesis_berti"],"name":"VisualBlock","description":"Java software for extracting and exporting interesting subgraphs for analysis .","id":"sw_7_visualblock","type":"Software","repository":"https://github.com/Brotherhood94/VisualBlock"},"context":[{"neighborType":"Person","distance":1,"path_rels":["DEVELOPED"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}},{"neighborType":"Publication","distance":1,"path_rels":["IMPLEMENTS"],"neighbor":{"address":"Università di Pisa","year":"Dicembre 2017","bibtex_key":"bachelor_thesis_berti","keyword_tag":"t","id":"pub_bachelor_thesis_berti","type":"Publication","author_ids":["person_alessandro_berti"],"title":"Sviluppo di un plugin per visualizzazione ed analisi della blockchain di Bitcoin","entry_type":"misc","category":"thesis","venue_id":""}}]},{"type":"ReviewActivity","score":2.062807559967041,"summary":"Building Quantum Software with Python","entity":{"year":"2024","publisher":"Manning Publications","id":"review_book_1_building_quantum_software_with","title":"Building Quantum Software with Python","type":"ReviewActivity","review_type":"book","authors":"Constantin Gonciulea (Wells Fargo), Charlee Stefanski (Wells Fargo)"},"context":[{"neighborType":"Person","distance":1,"path_rels":["BOOK_REVIEWED"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}}]},{"type":"Software","score":1.6091392040252686,"summary":"Python code that evaluates the performance of the variational circuit for state-preparation compression, as presented in .","entity":{"related_publication_ids":["pub_berti2024compression"],"name":"Variational Learning of Compressed Quantum Data","description":"Python code that evaluates the performance of the variational circuit for state-preparation compression, as presented in .","id":"sw_1_variational_learning_of_compre","type":"Software","repository":"https://github.com/Brotherhood94/VariationalLearningCompressedQData"},"context":[{"neighborType":"Person","distance":1,"path_rels":["DEVELOPED"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}},{"neighborType":"Publication","distance":1,"path_rels":["IMPLEMENTS"],"neighbor":{"year":"2024","title":"Variational Compression of Circuits for State Preparation","author_ids":["person_alessandro_berti","person_giacomo_antonioli","person_anna_bernasconi","person_gianna_maria_del_corso","person_riccardo_guidotti","person_alessandro_poggiali"],"type":"Publication","volume":"02","pages":"44-48","keyword_tag":"c","bibtex_key":"berti2024compression","id":"pub_berti2024compression","category":"conference","entry_type":"inproceedings","venue_id":"venue_2024_ieee_international_conference_on_quantum_computing_and_engineering_qce","doi":"10.1109/QCE60285.2024.10250"}}]},{"type":"Software","score":1.6091392040252686,"summary":"PyPI package providing a quantum KNN algorithm based on amplitude encoding.","entity":{"name":"QkNN package","description":"PyPI package providing a quantum KNN algorithm based on amplitude encoding.","id":"sw_3_qknn_package","type":"Software","repository":"https://pypi.org/project/quantum-distance-based-classifier/0.0.4/"},"context":[{"neighborType":"Person","distance":1,"path_rels":["DEVELOPED"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}}]},{"type":"Software","score":1.6091392040252686,"summary":"Python code that analyzes Grover's algorithm and the Quantum Fourier Transform performance on different quantum architectures.","entity":{"name":"Green QC","description":"Python code that analyzes Grover's algorithm and the Quantum Fourier Transform performance on different quantum architectures.","id":"sw_4_green_qc","type":"Software","repository":"https://github.com/Brotherhood94/Green_QC/blob/main/green_qc.py"},"context":[{"neighborType":"Person","distance":1,"path_rels":["DEVELOPED"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}}]},{"type":"Software","score":1.6091392040252686,"summary":"Python code implementing the quantum forking technique described in .","entity":{"related_publication_ids":["pub_poster2023bertiforking","pub_berti2023forking"],"name":"Logarithmic Quantum Forking","description":"Python code implementing the quantum forking technique described in .","id":"sw_5_logarithmic_quantum_forking","type":"Software","repository":"https://github.com/Brotherhood94/logarithmic_quantum_forking"},"context":[{"neighborType":"Person","distance":1,"path_rels":["DEVELOPED"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}},{"neighborType":"Publication","distance":1,"path_rels":["IMPLEMENTS"],"neighbor":{"year":"2023","bibtex_key":"poster2023bertiforking","keyword_tag":"p","id":"pub_poster2023bertiforking","title":"Logarithmic Quantum Forking","type":"Publication","author_ids":["person_alessandro_berti"],"entry_type":"misc","category":"poster","venue_id":"venue_quantum_infomation_processing_qip_ghent_belgium"}},{"neighborType":"Publication","distance":1,"path_rels":["IMPLEMENTS"],"neighbor":{"pages":"251-256","year":"2023","bibtex_key":"berti2023forking","keyword_tag":"c","id":"pub_berti2023forking","title":"Logarithmic Quantum Forking","type":"Publication","author_ids":["person_alessandro_berti"],"entry_type":"inproceedings","category":"conference","venue_id":"venue_proceedings_of_esann","doi":"10.14428/esann/2023.ES2023-93"}}]},{"type":"Software","score":1.6091392040252686,"summary":"Python code for two quantum KNN variants introduced in .","entity":{"related_publication_ids":["pub_poster2023bertieffect","pub_BBCG22","pub_berti2024role"],"name":"Quantum Instance-based Classifiers","description":"Python code for two quantum KNN variants introduced in .","id":"sw_6_quantum_instance_based_classif","type":"Software","repository":"https://github.com/Brotherhood94/exploring_different_encoding_and_distance_metrics_for_a_quantum_instance_based_classifier"},"context":[{"neighborType":"Person","distance":1,"path_rels":["DEVELOPED"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}},{"neighborType":"Publication","distance":1,"path_rels":["IMPLEMENTS"],"neighbor":{"address":"Cham","year":"2022","title":"Effect of Different Encodings and Distance Functions on Quantum Instance-Based Classifiers","author_ids":["person_alessandro_berti","person_anna_bernasconi","person_gianna_maria_del_corso","person_riccardo_guidotti"],"type":"Publication","pages":"96--108","publisher":"Springer International Publishing","keyword_tag":"c","bibtex_key":"BBCG22","id":"pub_BBCG22","category":"conference","entry_type":"inproceedings","venue_id":"venue_advances_in_knowledge_discovery_and_data_mining","doi":"10.1007/978-3-031-05936-0_8"}},{"neighborType":"Publication","distance":1,"path_rels":["IMPLEMENTS"],"neighbor":{"year":"2024","type":"Publication","author_ids":["person_alessandro_berti","person_anna_bernasconi","person_gianna_maria_del_corso","person_riccardo_guidotti"],"title":"The role of encodings and distance metrics for the quantum nearest neighbor","volume":"6","number":"2","pages":"62","publisher":"Springer","bibtex_key":"berti2024role","keyword_tag":"j","id":"pub_berti2024role","entry_type":"article","category":"journal","venue_id":"venue_quantum_machine_intelligence","doi":"10.1007/s42484-024-00197-6"}},{"neighborType":"Publication","distance":1,"path_rels":["IMPLEMENTS"],"neighbor":{"year":"2021","bibtex_key":"poster2023bertieffect","keyword_tag":"p","id":"pub_poster2023bertieffect","type":"Publication","title":"Effects of Different Encodings and Distance Functions on Quantum Instance-based Classifiers","author_ids":["person_alessandro_berti","person_anna_bernasconi","person_gianna_maria_del_corso","person_riccardo_guidotti"],"entry_type":"misc","category":"poster","venue_id":"venue_quantum_techniques_on_machine_learning_qtml_tokyo_japan_online_attendance"}}]},{"type":"Software","score":1.6091392040252686,"summary":"Python code implementing the quantum variance algorithm for computing the variance of a dataset .","entity":{"related_publication_ids":["pub_poggiali2023quantum","pub_bernasconi2024quantumVAR"],"name":"Quantum Variance","description":"Python code implementing the quantum variance algorithm for computing the variance of a dataset .","id":"sw_2_quantum_variance","type":"Software","repository":"https://github.com/AlessandroPoggiali/QVAR"},"context":[{"neighborType":"Person","distance":1,"path_rels":["DEVELOPED"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}},{"neighborType":"Publication","distance":1,"path_rels":["IMPLEMENTS"],"neighbor":{"year":"2023","bibtex_key":"poggiali2023quantum","keyword_tag":"c","id":"pub_poggiali2023quantum","type":"Publication","title":"Quantum feature selection with variance estimation","author_ids":["person_alessandro_poggiali","person_anna_bernasconi","person_alessandro_berti","person_gianna_maria_del_corso","person_riccardo_guidotti"],"entry_type":"inproceedings","category":"conference","venue_id":"venue_proceedings_of_esann","doi":"10.14428/esann/2023.ES2023-99"}},{"neighborType":"Publication","distance":1,"path_rels":["IMPLEMENTS"],"neighbor":{"year":"2024","author_ids":["person_anna_bernasconi","person_alessandro_berti","person_gianna_maria_del_corso","person_riccardo_guidotti","person_alessandro_poggiali"],"type":"Publication","title":"Quantum subroutine for variance estimation: algorithmic design and applications","volume":"6","number":"2","pages":"78","publisher":"Springer","keyword_tag":"j","bibtex_key":"bernasconi2024quantumVAR","id":"pub_bernasconi2024quantumVAR","category":"journal","entry_type":"article","venue_id":"venue_quantum_machine_intelligence","doi":"doi.org/10.1007/s42484-024-00213-9"}}]},{"type":"Software","score":1.6091392040252686,"summary":"A Gephi plugin written in Java that uses the Webgraph library to visually explore interesting subgraphs in large graphs .","entity":{"related_publication_ids":["pub_bachelor_thesis_berti"],"name":"VisualBiGraph","description":"A Gephi plugin written in Java that uses the Webgraph library to visually explore interesting subgraphs in large graphs .","id":"sw_8_visualbigraph","type":"Software","repository":"https://github.com/Brotherhood94/VisualBiGraph"},"context":[{"neighborType":"Person","distance":1,"path_rels":["DEVELOPED"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}},{"neighborType":"Publication","distance":1,"path_rels":["IMPLEMENTS"],"neighbor":{"address":"Università di Pisa","year":"Dicembre 2017","bibtex_key":"bachelor_thesis_berti","keyword_tag":"t","id":"pub_bachelor_thesis_berti","type":"Publication","author_ids":["person_alessandro_berti"],"title":"Sviluppo di un plugin per visualizzazione ed analisi della blockchain di Bitcoin","entry_type":"misc","category":"thesis","venue_id":""}}]},{"type":"ResearchGroup","score":1.321803331375122,"summary":"Coordinated by Norm Tubman, it focuses on algorithms for simulating LHC physics and the early universe, exploring superconductivity and quantum materials, producing software for quantum processors, and investigating applications in finance, MRI data analysis, and strongly entangled systems.","entity":{"name":"Algorithms Thrust","description":"Coordinated by Norm Tubman, it focuses on algorithms for simulating LHC physics and the early universe, exploring superconductivity and quantum materials, producing software for quantum processors, and investigating applications in finance, MRI data analysis, and strongly entangled systems.","location":"Fermilab, Batavia, Illinois, USA","dates":"08/2022 -- present","id":"group_3_algorithms_thrust","type":"ResearchGroup","institution_id":"inst_sqms"},"context":[{"neighborType":"Person","distance":1,"path_rels":["MEMBER_OF_GROUP"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}},{"neighborType":"Institution","distance":1,"path_rels":["GROUP_AT"],"neighbor":{"name":"SQMS","id":"inst_sqms","type":"Institution"}}]},{"type":"TrainingActivity","score":0.9065942764282227,"summary":"This event highlighted the latest progress in the IBM Quantum roadmap, focusing on advanced software tools such as Qiskit and the new IBM Heron R2 processor. The conference introduced leading-edge quantum technologies, including services like Qiskit Transpiler Service and Qiskit Code Assistant, and proposed strategies for optimizing large-scale quantum circuits in industrial contexts. This init…","entity":{"website":"https://www.ibm.com/events/reg/flow/ibm/q7e1efmb/landing/page/landing","organizer":"IBM Watson Research Center","organizer_id":"inst_ibm_watson_research_center","name":"IBM Quantum Developer Conference","description":"This event highlighted the latest progress in the IBM Quantum roadmap, focusing on advanced software tools such as Qiskit and the new IBM Heron R2 processor. The conference introduced leading-edge quantum technologies, including services like Qiskit Transpiler Service and Qiskit Code Assistant, and proposed strategies for optimizing large-scale quantum circuits in industrial contexts. This initiative offered a chance to examine practical quantum technology applications and collaborate with international experts, strengthening quantum development expertise.","dates":"11/13/2024 -- 11/15/2024","location":"{\"venue\":\"IBM Watson Research Center\",\"city\":\"Yorktown Heights\",\"country\":\"New York\"}","id":"training_1_ibm_quantum_developer_conferen","type":"TrainingActivity"},"context":[{"neighborType":"Person","distance":1,"path_rels":["ATTENDED_TRAINING"],"neighbor":{"skills":"{\"agentic_coding\":[\"Roo Code\",\"Claude Code\"],\"programming\":[\"Python\",\"Java\",\"C\",\"C++\"],\"quantum_libraries\":[\"Qiskit\",\"Pennylane\"],\"ide\":[\"Visual Studio Code\"],\"os\":[\"Mac OS X\",\"GNU/Linux\",\"Windows\"],\"analytics\":[\"Jupyter\"]}","qualification":"Ph.D. in Computer Science","research_interests":"Alessandro Berti's research spans three main topics: quantum algorithms for AI (Quantum AI), techniques for quantum state preparation, and variational quantum circuits. Regarding Quantum AI, he focuses on classification , clustering , and outlier detection . He investigates their complexity and accuracy, emphasizing how quantum input loading affects performance, especially when transforming classical data into quantum states. Efficient data loading shapes the viability of running quantum algorithms on large datasets. He also studies variational quantum circuits to mitigate noise in current quantum architectures. Specifically, these circuits form a quantum reservoir computing model that learns quantum gates with error tolerance for superconducting qubits . Moreover, Alessandro explores quantum data compression methods that reduce the number of gates needed to encode classical data into quantum states and limit noise effects of certain architectures .","languages":"[{\"language\":\"Italian\",\"level\":\"Native Speaker\",\"certification\":null},{\"language\":\"English\",\"level\":\"Advanced\",\"certification\":\"Certification: English for Research Publication and Presentation Purposes - C1 (University of Pisa, 2021)\"}]","is_primary":true,"identifiers":"{\"orcid\":\"https://orcid.org/0000-0001-9144-9572\"}","citizenship":"Italian","name":"Alessandro Berti","biography":"Alessandro Berti is currently a postdoctoral researcher at the Department of Physics, University of Pisa, where he focuses on quantum algorithms. He also serves as a subject expert in quantum computing at the Department of Computer Science. In 2019, he launched an entrepreneurial project by starting a startup that taught him valuable skills in business dynamics. At the same time, he created a podcasting project that promotes scientific and technical knowledge and helps him connect with prominent international experts. Later, in 2020, Alessandro founded a community that fosters dialogue between university students and Big Tech. This community now counts more than 2300 members and receives support from more than 8 Italian universities. Subsequently, Alessandro decided to devote himself to academic research, winning a Ph.D. scholarship at the Department of Computer Science of the University of Pisa in the same year and completing his doctorate in 2024. His research revolves around quantum algorithms, especially those oriented toward artificial intelligence and efficient techniques for quantum state preparation. He also patented a quantum state preparation technique with the support of the University of Pisa. During a period of study abroad at Fermilab's SQMS center in the United States, Alessandro collaborated with NASA, USRA, and Fermilab on the development of a quantum reservoir computing model that learns quantum gates. Throughout his Ph.D., Alessandro also worked on teaching activities in both Bachelor's and Master's degrees in Computer Science, including laboratory lectures for the course Introduction to Quantum Computing. He actively spreads scientific knowledge through events such as Bright Night and university initiatives that promote the Department of Computer Science's research. Alessandro Berti has authored 16 scientific contributions in peer-reviewed journals and international conferences, workshops, and poster presentations. He also served as a program committee member at several international conferences.","id":"person_alessandro_berti","type":"Person","personal_interests":"{\"personal_interests\":[\"Video and Audio Editing\",\"Visual Effects\",\"3D Modeling\"],\"software\":[\"Adobe Premiere\",\"Adobe Illustrator\",\"Adobe After Effects\",\"Autodesk 3ds Max\"],\"driving_license\":[\"Type B\"]}"}},{"neighborType":"Institution","distance":1,"path_rels":["ORGANIZED_BY"],"neighbor":{"name":"IBM Watson Research Center","id":"inst_ibm_watson_research_center","type":"Institution"}}]}],"total":11}