Tesi disponibili

Descrizione:
Future Cooperative, Connected and Automated Mobility (CCAM) systems will operate in highly dynamic urban environments characterized by heterogeneous connectivity, partial observability, and stringent safety requirements. In these scenarios, communication, sensing, and coordination mechanisms cannot be designed independently, as the availability and quality of information directly affect cooperative decision-making and traffic safety. This thesis investigates the use of Agentic Artificial Intelligence (Agentic AI) for predictive and cooperative V2X communication systems. The objective is to design distributed AI agents capable of perceiving the communication and environmental context, reasoning on network conditions and sensing information, and autonomously adapting communication and coordination strategies in real time. Particular attention will be devoted to predictive communication techniques exploiting digital-twin information, sensing-aware representations, and multi-frequency vehicular communication models. The activity will focus on urban scenarios involving connected and non-connected vehicles, roadside infrastructure, and vulnerable road users under heterogeneous communication conditions. The student will investigate how AI-driven agents can support adaptive information dissemination, cooperative perception, task orchestration, and communication-aware coordination while accounting for latency, reliability, and observability constraints. The work will combine simulation and experimental activities using advanced vehicular networking and digital-twin frameworks, including tools such as NS-3, SUMO, Sionna, and ray-tracing-based communication models. Depending on the thesis scope and student interests, the work may also include the integration of sensing data, distributed learning approaches, and experimental validation on real communication platforms. The thesis is part of ongoing research activities at Politecnico di Milano with Institute of Science Tokyo formerly Tokyo Tech on next-generation V2X systems, digital twins, and AI-driven wireless communication for future CCAM and 6G vehicular networks.

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(Thesis-oriented internship at OHB Italia) Small and micro satellites present a significant challenge for radio-frequency compatibility verification by analysis, a fundamental step that must be performed within the design loop long before verification by test, which usually occurs at a much later stage of the spacecraft production cycle. The compact size of these platforms results in very limited distances between antennas, typically far smaller than the separation required to remain within the validity limits of the analytical methodologies commonly used for larger spacecraft. In this context, the aim of the thesis is to develop an analytical approach to address this challenge, specifically: To use FEKO to develop antenna models typically employed on small and micro platforms (e.g., patch antennas). To use the FEKO optimization tools to tune and fit these antenna models using information provided by the antenna suppliers. To use the developed antenna models to derive coupling factors between different antennas at both in band and out of band frequencies in real case scenarios.

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This thesis explores the use of autonomous unmanned aerial vehicles (UAVs) as passive sensing platforms for multi-user identification and localization in 5G cellular networks. Building on recent advances in UAV-based signal intelligence, the work aims to enhance the accuracy, robustness, and efficiency of user localization by combining advanced signal processing techniques with adaptive UAV mission planning. The research will investigate methods for extracting spatial information from uplink reference signals, addressing challenges such as multi-user interference, multipath propagation, and limited sensing time. In addition, the thesis will study intelligent trajectory optimization strategies that allow the UAV to dynamically adapt its flight path based on real-time signal measurements, balancing localization performance and energy consumption. The expected outcome is a scalable and infrastructure-independent framework for reliable user localization, with strong potential impact in emergency response, disaster recovery, and next-generation wireless network monitoring.

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The Photonic Devices group of Politecnico di Milano, leaded by Proff. Andrea Melloni and Francesco Morichetti has many openings for master thesis.
The group is involved in fundamental as well as applied research in photonics, from waveguide technology to circuit design, from industry applications to new concepts in the field of communication (fiber and free space), sensing, circuit control, testing and photonic computing.

Activities range from numerical analysis to experimental characterizations to fabrication in clean room. The group works in a multidisciplinary scenario merging photonics with electronics, control systems, computer science, machine learning, ….

We have different open positions for master thesis on various topics:
- Programmable Photonic Circuits
- Photonic computing
- Wireless optics and microwave photonics
- Photonic sensors and LIDAR
- Photonic MEMS
- Photonics for quantum systems
- Silicon (oxy)carbide technology, waveguides and passive/active devices conception and fabrication
- Testing techniques and tools for volume and on-wafer level
- Electronics and algorithms for circuit control
- Micro and nano fabrication in clean room (Polifab)

Students interested in a thesis activity with us should have some background in one of the following areas: photonics, telecommunication, electronics, RF systems, electromagnetism and physics, material science, engineering, control systems, computer science.

About us
https://photonics.deib.polimi.it
https://www.polifab.polimi.it

If you are interested or require more information contact andrea.melloni@polimi.it and francesco.morichetti@polimi.it.

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