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Davide Pilati

Ph.D. candidate in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 39th cycle (2023-2026)
Department of Applied Science and Technology (DISAT)

Adjunct lecturer/Adjunct instructor
Department of Electronics and Telecommunications (DET)

Profile

PhD

Research topic

Unconventional computing with neuromorphic nanowire networks

Tutors

Keywords

Big Data, Machine Learning, Neural Networks and Data Science
Electronic devices: modeling and characterization
Micro- and nanotechnologies, devices, systems and applications

Awards and Honors

  • Best Talk by an Early Career Researcher Prize - MEMRISYS 2025 (2025)

Teaching

Teachings

Master of Science

MostraNascondi A.A. passati

Research

Other activities and projects related to research

The main objective of the PhD work is the experimental implementation of unconventional computing paradigms and neuromorphic functionalities in multiterminal devices based on memristive nanowire networks.The aim is the development of a hardware computing architectures able to solve a wide range of computing tasks such as pattern recognition and time series prediction with reduced training cost and energy consumption.


Publications

Latest publications View all publications in Porto@Iris