ANDREA CESCHINI

Dottorando

ciclo: XXXVII
email: andrea.ceschini@uniroma1.it, andrea@ceschini.it
telefono: 3387655663
edificio: San Pietro in Vincoli - RM032
stanza: 1° piano (floor), stanza n. 111




relatore: prof. Massimo Panella

Argomento di Ricerca: Quantum Machine Learning on NISQ devices
Curriculum: Ingegneria dell'Informazione e della Comunicazione

Inizio Dottorato di Ricerca: Novembre 2021
Commissione di affiancamento: prof. Fabio Sciarrino, prof. Stefan Wabnitz, prof. Giuseppe Scotti


Produzione scientifica

11573/1675690 - 2023 - Analysis of Logic Schemes for the Optical Implementation of Pointwise Operations in Gated Recurrent Unit Cells
Alam, Badrul; Ceschini, Andrea; Rosato, Antonello; Panella, Massimo; Asquini, Rita - 02a Capitolo o Articolo
libro: Sensors and Microsystems - (978-3-031-25705-6; 978-3-031-25706-3)

11573/1686456 - 2023 - Modular quantum circuits for secure communication
Ceschini, A.; Rosato, A.; Panella, M. - 01a Articolo in rivista
rivista: IET QUANTUM COMMUNICATION (Receiving publisher (01/01/2021) : Wiley Stevenage: Institution of Engineering and Technology, 2020-) pp. 208-217 - issn: 2632-8925 - wos: WOS:001117992800006 (0) - scopus: 2-s2.0-85168259862 (0)

11573/1690651 - 2023 - Resource saving via ensemble techniques for quantum neural networks
Incudini, M.; Grossi, M.; Ceschini, A.; Mandarino, A.; Panella, M.; Vallecorsa, S.; Windridge, D. - 01a Articolo in rivista
rivista: QUANTUM MACHINE INTELLIGENCE (Cham: Springer International Publishing) pp. 1-24 - issn: 2524-4906 - wos: WOS:001079309800002 (0) - scopus: 2-s2.0-85173578065 (0)

11573/1696640 - 2023 - A general approach to dropout in quantum neural networks
Scala, Francesco; Ceschini, Andrea; Panella, Massimo; Gerace, Dario - 01a Articolo in rivista
rivista: ADVANCED QUANTUM TECHNOLOGIES (Weinheim: Wiley-VCH Verlag) pp. 1-18 - issn: 2511-9044 - wos: WOS:001118464600001 (0) - scopus: 2-s2.0-85179328285 (0)

11573/1664101 - 2022 - All-optical logic gates based on semiconductor optical amplifiers for implementing deep recurrent neural networks
Alam, B.; Ceschini, A.; Rosato, A.; Panella, M.; Asquini, R. - 04d Abstract in atti di convegno
congresso: 53.ma Riunione Annuale dell’Associazione Società Italiana di Elettronica (SIE) (Pizzo (VV), Italia)
libro: Atti della 53.ma Riunione Annuale dell’Associazione Società Italiana di Elettronica (SIE) - ()

11573/1655649 - 2022 - All-optical and logic gate based on semiconductor optical amplifiers for implementing deep recurrent neural networks
Alam, Badrul; Ceschini, Andrea; Rosato, Antonello; Panella, Massimo; Asquini, Rita - 04b Atto di convegno in volume
congresso: International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD) (Torino (ITA))
libro: 2022 International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD) - (978-1-6654-7898-4; 978-1-6654-7899-1)

11573/1658031 - 2022 - Hybrid Quantum-Classical Recurrent Neural Networks for Time Series Prediction
Ceschini, A.; Rosato, A.; Panella, M. - 04b Atto di convegno in volume
congresso: 2022 International Joint Conference on Neural Networks, IJCNN 2022 (Padova, Italy)
libro: Proceedings of the International Joint Conference on Neural Networks - (978-1-7281-8671-9)

11573/1655500 - 2022 - Multivariate time series analysis for electrical power theft detection in the distribution grid
Ceschini, A.; Rosato, A.; Succetti, F.; Araneo, R.; Panella, M. - 04b Atto di convegno in volume
congresso: 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2022 (Prague; Czech Republic)
libro: 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2022 - (978-1-6654-8537-1)

11573/1584748 - 2022 - Design of an LSTM cell on a quantum hardware
Ceschini, Andrea; Rosato, Antonello; Panella, Massimo - 01a Articolo in rivista
rivista: IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS. II, EXPRESS BRIEFS (Piscataway, NJ : Institute of Electrical and Electronics Engineers, c2004-) pp. 1822-1826 - issn: 1549-7747 - wos: WOS:000770045800235 (3) - scopus: 2-s2.0-85127912184 (5)

11573/1664099 - 2022 - Ensembling Techniques for Quantum Neural Networks
Incudini, M.; Grossi, M.; Ceschini, A.; Mandarino, A.; Panella, M.; Vallecorsa, S.; Windridge, D.; Di Pierro, A. - 04d Abstract in atti di convegno
congresso: Quantum Techniques in Machine Learning (QTML 2022) (Napoli, Italia)
libro: Proceedings of Quantum Techniques in Machine Learning (QTML 2022) - ()

11573/1657000 - 2022 - A Fast Deep Learning Technique for Wi-Fi-Based Human Activity Recognition
Succetti, F.; Rosato, A.; Di Luzio, F.; Ceschini, A.; Panella, M. - 01a Articolo in rivista
rivista: ELECTROMAGNETIC WAVES (EMW Publishing:PO Box 425517:Cambridge, MA 02142:(617)354-9597, INTERNET: http://www.emwave.com, Fax: (617)547-3137) pp. 127-141 - issn: 1070-4698 - wos: WOS:000824736600001 (6) - scopus: 2-s2.0-85134012948 (7)

11573/1630054 - 2021 - Deep Neural Networks for Electric Energy Theft and Anomaly Detection in the Distribution Grid
Ceschini, A.; Rosato, A.; Succetti, F.; Di Luzio, F.; Mitolo, M.; Araneo, R.; Panella, M. - 04b Atto di convegno in volume
congresso: 21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 (Bari; Italy)
libro: 21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedings - (978-1-6654-3613-7)

11573/1630052 - 2021 - Multivariate Prediction of Energy Time Series by Autoencoded LSTM Networks
Succetti, F.; Di Luzio, F.; Ceschini, A.; Rosato, A.; Araneo, R.; Panella, M. - 04b Atto di convegno in volume
congresso: 21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 (Bari; Italy)
libro: 21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedings - (978-1-6654-3613-7)

11573/1566169 - 2021 - Time series prediction with autoencoding LSTM networks
Succetti, Federico; Ceschini, Andrea; Di Luzio, Francesco; Rosato, Antonello; Panella, Massimo - 04b Atto di convegno in volume
congresso: 6th International Work-Conference on Artificial Neural Networks, IWANN 2021 (Virtual, Online)
libro: Lecture Notes in Computer Science - (978-3-030-85098-2; 978-3-030-85099-9)

© Università degli Studi di Roma "La Sapienza" - Piazzale Aldo Moro 5, 00185 Roma