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Staff

Giuseppe Fanuli

Ph.D. candidate in Ingegneria Informatica E Dei Sistemi , 41st cycle (2025-2028)
Department of Control and Computer Engineering (DAUIN)

Adjunct lecturer/Adjunct instructor
Department of Control and Computer Engineering (DAUIN)

Profile

PhD

Research topic

Designing a cloud-based heterogeneous prototyping platform for the development of AIoT apps

Tutors

Keywords

Controls and system engineering
Parallel and distributed systems, Quantum computing

Biography


Giuseppe Fanuli is a PhD candidate at the Politecnico di Torino, where he conducts research in the field of distributed systems and software engineering for heterogeneous infrastructures. He obtained both his Bachelor’s and Master’s degrees in Computer Engineering from the same institution, specializing in Computer Networks and Cloud Computing. During his academic career, he developed solid expertise in cloud systems, microservices design, and orchestration technologies, with a particular interest in the integration of modern software infrastructures with heterogeneous hardware.

His PhD project lies at the intersection of cloud computing, distributed systems, and emerging hardware architectures. In particular, his research focuses on the design and development of a Heterogeneous Prototyping Platform (HPP), a platform that enables software developers to design, test, and validate complex solutions on heterogeneous systems including CPUs, GPUs, FPGAs, and neuromorphic hardware. The main objective is to reduce the technological and operational barriers that currently limit the adoption of non-conventional architectures, especially in the context of AIoT and industrial applications.

His research is strongly rooted in the modern cloud computing paradigm. In particular, he investigates how technologies such as Kubernetes and microservices can be extended or adapted to support the orchestration of workloads across heterogeneous and distributed hardware. In this context, the cloud system under development integrates MLOps and Neuromorphic MLOps (NMLOps) solutions, with the goal of supporting the full lifecycle of machine learning applications, from prototyping to deployment on heterogeneous infrastructures. This approach involves the study of new scheduling models, efficient resource management strategies, and the integration of advanced monitoring systems, including metrics tailored for ML and neuromorphic workloads. A key contribution of his work is the development of a hardware sharing system that enables controlled and shared access to heterogeneous computational resources, improving efficiency and reducing operational costs.

His research activity is carried out in collaboration with the inNuCE – Neuromorphic Computing and Engineering Lab at the Politecnico di Torino, part of the EDA Group @ Polito, contributing to the development of innovative solutions in the field of neuromorphic computing.

Teaching

Teachings

Master of Science

Bachelor of Science

  • Informatica. A.A. 2025/26, INGEGNERIA AEROSPAZIALE. Collaboratore del corso

Research

Research groups

Publications

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