Dottorando in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 38o ciclo (2022-2025)
Dipartimento di Elettronica e Telecomunicazioni (DET)
Profilo
Dottorato di ricerca
Argomento di ricerca
Advanced Studies in Photonic Integrated Circuits
Tutori
Interessi di ricerca
Biografia
Andrea Marchisio was born in Alba (CN) in 1998. He received his Bachelor's Degree in Physics Engineering at Politecnico di Torino in October 2020. In the same year, he enrolled in the Electronic Engineering Master's Degree course at Politecnico di Torino, "Devices and Technologies for Integrated Electronics and Optoelectronics" curriculum. He received the Master's Degree cum laude in October 2022, with his thesis "Analysis of Quantum Dot-based optical amplifiers: a time-domain traveling-wave approach", supervised by professor P. Bardella. In September 2022, he obtained the Ph.D. scolarship in "Advanced Studies in Photonic Integrated Circuits".
His research interests are the design and simulation of passive and active photonic devices in the context of Photonic Integrated Circuits (PICs).
Pubblicazioni
Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris
- Marchisio, Andrea; Curri, Vittorio; Carena, Andrea; Bardella, Paolo (2023)
Deep Learning-Driven Extraction of Superluminescent Diodes Parameters. In: International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD), Torino (ITALY), 18-21 September 2023. ISBN: 979-8-3503-1429-8
Contributo in Atti di Convegno (Proceeding) - Marchisio, Andrea; Tunesi, Lorenzo; Forrest, Adam F.; Cataluna, Maria Ana; Krakowski, ... (2023)
Time-Domain Travelling-Wave Analysis of Semiconductor Optical Amplifiers based on Chirped Quantum Dot Materials. In: CLEO: Applications and Technology 2023, San Jose, CA, USA, 7-12 May 2023, pp. 1-2. ISBN: 978-1-957171-25-8
Contributo in Atti di Convegno (Proceeding) - Khan, Ihtesham; Marchisio, Andrea; Tunesi, Lorenzo; Masood, MUHAMMAD UMAR; Ghillino, ... (2023)
A Machine Learning-Based Model for Characterizing Stationary-and-Dynamic Behavior of VCSEL. In: CLEO: Science and Innovations, San Jose, CA, United States, 7-12 May 2023, pp. 1-2. ISBN: 978-1-957171-25-8
Contributo in Atti di Convegno (Proceeding) - Tunesi, Lorenzo; Khan, Ihtesham; Masood, MUHAMMAD UMAR; Marchisio, Andrea; Ghillino, ... (2023)
Machine Learning Aided Prediction of Fabrication Uncertainties in Integrated Multi-Ring Filters. In: CLEO: Science and Innovations, San Jose, CA, United States, 7-12 May 2023, pp. 1-2. ISBN: 978-1-957171-25-8
Contributo in Atti di Convegno (Proceeding) - Marchisio, Andrea; Khan, Ihtesham; Tunesi, Lorenzo; Masood, Muhammad Umar; Ghillino, ... (2023)
Automated model for characterization of VCSEL circuit-level parameters using machine learning. In: European Conference on Integrated Optics, Enschede, Paesi Bassi, 19-21 Aprile 2023, pp. 264-266
Contributo in Atti di Convegno (Proceeding)