Analyzing Political Echo Chambers and Misinformation Dynamics on Truth SocialContact person
FRANCESCO PIERRIEmail:
francesco.pierri@polimi.itStudy course: Automation Engineering, Computer Science and Engineering, Telecommunications Engineering
Web page:
https://pierri.faculty.polimi.itDescription
Description:
This study investigates the formation and behavior of political echo chambers and the spread of misinformation on Truth Social, a platform known for its alignment with right-wing discourse. Using computational social science methods, including network analysis and natural language processing (NLP), the research examines how information circulates within ideologically homogeneous communities and how narratives evolve in response to political events. The goal is to deepen our understanding of alternative social media ecosystems and their impact on political polarization and information integrity in the digital public sphere.
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Digital Twin Framework for Intrabody RF Wireless CommunicationsContact person
SILVIA MURA, FRANCESCO LINSALATAEmail:
silvia.mura@polimi.it, francesco.linsalata@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Maurizio MagariniDescription
Description:
This thesis presents a digital twin framework for modeling and optimizing intrabody RF wireless communications across frequencies including millimeter-wave (mmWave) and terahertz (THz) bands. By integrating detailed anatomical and physiological data, the framework accurately replicates the complex electromagnetic environment within the human body. This enables predictive simulations of signal propagation, addressing key challenges such as attenuation, scattering, and absorption. The digital twin provides a non-invasive platform for designing and optimizing intrabody wireless systems, facilitating the advancement of high-performance networks for biomedical applications like implantable devices and real-time health monitoring.
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Contributions to the development of a 5G snifferContact person
EUGENIO MOROEmail:
eugenio.moro@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Marco MezzavillaDescription
Description:
We are looking for a master student interested in pursuing their thesis on the topic of 5G networks. More specifically, the thesis is about contributing to the development of a 5G sniffer. In broad terms, a 5G sniffer is a device capable of decoding the transmissions between gNB and UEs.
The ideal candidate has the following skills:
- Proficient with C/C++
- Familiar with CMake
- Knowledgeable about wireless communication systems, specifically mobile radio networks
Bonus points if you have:
- experience with SDR
- experience with OpenAirInterface
This thesis will be carried out in collaboration with a team from KAIST university, but it does not require you to move to Korea.
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Examining the Dynamics of Online Hate Speech in the Context of the Israel-Palestine ConflictContact person
FRANCESCO PIERRIEmail:
francesco.pierri@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Web page:
pierri.faculty.polimi.itDescription
Description:
This study investigates the dynamics of online hate speech related to the Israel-Palestine conflict by analyzing social media discourse across major platforms. Using NLP and discourse analysis, it explores how hate speech fluctuates in response to key events and assesses the effectiveness of platform moderation. The goal is to better understand digital polarization in geopolitical conflicts.
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Personalized LLM answers with IoT input data sourcesContact person
MATTIA BRAMBILLAEmail:
mattia.brambilla@polimi.itStudy course: Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Prof. Capone AntonioDescription
Description:
Following the raising trend of AI, this thesis aims to integrate IoT sensor data into LLM prompts to enrich the input information and provide personalized answers. IoT sensors available in the IoTLab will be used as data sources, with their integration into a hub platform, and later embeddings into LLM prompts. LLM models accessible through API or locally installed will be compared and analyzed.
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Wi-Fi Systems for Sport Racing CommunicationContact person
LUCA REGGIANIEmail:
luca.reggiani@polimi.itStudy course: Telecommunications Engineering
Description
Description:
Wi-Fi is the well-known family of wireless local area network protocols based on the IEEE 802.11 standard. The recent releases 6 and 7 have reached peak data rates around 10 and 46 Gbps respectively in bands at 2.4, 5, 6 GHz and they are widely deployed for short-medium range communication in indoor and outdoor environments. In cooperation with Marelli Motorsport, this thesis explores the use of Wi-Fi 6 for sport racing communication applications, in outdoor scenarios with medium-range data transfer and affected by interference of concurrent wireless systems. The study involves simulative and experimental activities.
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Signal Processing and Learning for Near-Field 6G SystemsContact person
MAROUAN MIZMIZIEmail:
marouan.mizmizi@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Description
Description:
As 6G networks evolve to use higher frequencies and larger MIMO arrays, communication will increasingly occur in the near-field, unlike today’s far-field systems. This shift has significant implications for how channels are modeled, estimated, and how communication systems are designed. Near-field communication introduces unique challenges, such as the need for new channel models that account for spatial variations over short distances and more complex, yet critical, channel estimation techniques. Precoding and equalization strategies must also be reimagined to address the non-uniform distribution of signals and the potential for increased interference in dense network environments.
This thesis will explore these challenges by developing advanced signal processing techniques tailored for near-field conditions in 6G networks. It will focus on improving channel modeling, estimation, precoding, and equalization for high-frequency, dense scenarios. Additionally, the research will investigate the use of machine learning to enhance these techniques, offering more adaptive and robust solutions. The goal is to make a significant contribution to 6G technology by addressing the critical challenges of near-field communication with both traditional and machine learning-based approaches.
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Shaping the Future of 6G Networks: Digital Twins, AI, and Advanced Wireless EmulationContact person
FRANCESCO LINSALATAEmail:
francesco.linsalata@polimi.itStudy course: Automation Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Eugenio MoroDescription
Description:
The increasing complexity of 6G networks requires advanced tools for accurate modeling, real-time optimization, and intelligent management. Digital Network Twins (DNTs) represent a transformative approach, providing precise digital replicas of physical networks to enable predictive analysis, performance optimization, and risk-free experimentation.
This thesis will explore the integration of AI and Machine Learning (ML) techniques with ray-based channel modeling to enhance the accuracy and adaptability of DNTs. By leveraging data-driven methodologies, the research aims to develop a framework capable of dynamically simulating and optimizing next-generation wireless networks.
This project is suitable for students with a strong interest in AI-driven network management, wireless communications, and the evolution of 6G technologies. While prior experience in simulation, emulation, or optimization is beneficial, it is not a prerequisite, making this an excellent opportunity to develop expertise in these areas.
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5G-V2X positioning of a vehicle in a tunnelContact person
MATTIA BRAMBILLAEmail:
mattia.brambilla@polimi.itStudy course: Telecommunications Engineering
Other members of the research group:
Monica NicoliDescription
Description:
This thesis aims to investigate signal processing and learning algorithm to localize a vehicle traveling inside a tunnel without GPS coverage, using an on-site infrastructure of 5G V2X MIMO antennas.
First, the student will consider a ray tracing software tool for modeling the propagation of a wireless signal in the tunnel. Then, the student will develop algorithms exploiting the features of the received signal for positioning. At the end, if possible, the student should evaluate the feasibility of applying the "simulated-data-driven algorithm" on real measurements, assessing the portability from simulation to the real world of the algorithm.
The thesis is framed within a project with Movyon - Autostrade per l'Italia.
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Intrabody Communication: Exploring different technologies for Biomedical Data TransmissionContact person
SILVIA MURAEmail:
silvia.mura@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Maurizio MagariniDescription
Description:
Intrabody communication (IBC) is a promising technique for secure and energy-efficient data transmission within the human body, with applications in biomedical devices, wearable sensors, and implantable systems. The exploration of different transmission methods, including terahertz (THz) waves, galvanic coupling, and ultrasounds, presents an opportunity to optimize performance for diverse medical and health monitoring applications. This research seeks to analyze the feasibility and efficiency of these communication techniques through a combination of simulations and experimental validation.
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UAV Trajectory Planning and Synchronization for Efficient Search and Rescue OperationsContact person
SILVIA MURAEmail:
silvia.mura@polimi.itStudy course: Automation Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Maurizio Magarini, Francesco Linsalata, Davide ScazzoliDescription
Description:
This research focuses on advanced trajectory planning and synchronization techniques for Unmanned Aerial Vehicles (UAVs), commonly known as drones, in search and rescue operations. By optimizing flight paths, real-time communication, and coordinated movement, the study aims to enhance efficiency in locating and assisting individuals in distress. The thesis aims to integrate path optimization algorithms, obstacle avoidance mechanisms, and cooperative control strategies to ensure seamless multi-drone collaboration, even in complex and unpredictable environments. The findings will contribute to improving autonomous drone operations for emergency response and disaster management.
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5G Non-Terrestrial Networks With OpenAirInterfaceContact person
MATTIA BRAMBILLAEmail:
mattia.brambilla@polimi.itStudy course: Telecommunications Engineering
Description
Description:
This thesis aims to implement a 5G physical layer emulation in software defined radios (SDR) such as the Ettus x310 of the non-terrestrial network. By considering at least one SDR acting as satellite in a lab environment, and another one acting as user termina, it is goal of the thesis to evaluate the properties of 5G communication with the recently-defined non-terrestrial implementation. The following reference for approaching the research topic is suggested: https://ieeexplore.ieee.org/abstract/document/10723292
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Auditing social media platforms for Teen usage via sockpuppet accountsContact person
FRANCESCO PIERRIEmail:
francesco.pierri@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Web page:
pierri.faculty.polimi.itDescription
Description:
This thesis explores the use of automated and human-operated sockpuppet accounts to audit social media platforms’ policies and practices regarding teen users. It proposes a methodology for systematically testing age verification, exposure to harmful content, and engagement-driven algorithmic biases. By combining experimental digital ethnography with LLM-assisted content analysis, the research evaluates platform compliance, risk factors, and potential regulatory gaps.
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Opportunistic positioning with STARLINK satellitesContact person
MATTIA BRAMBILLAEmail:
mattia.brambilla@polimi.itStudy course: Telecommunications Engineering
Other members of the research group:
Prof. Monica NicoliDescription
Description:
This thesis aims to decode broadcast signals from STARLINK LEO satellites and use them to perform opportunistic positioning. Opportunistic means to passively detect (in a passive way) signals that are used for communication purposes and use them for positioning. Literature works have demonstrated the feasibility of this approach, reaching an accuracy better than 5 m. The MSc student should is requested to carry out an experimal activity with Software Defined Radio hardware for the simultaneous detection of 100+ STARLINK satellites, record data, and perform signal processing algorithms for improving the detection and appropriately estimate the position of the receiver.
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Impact of dataset reuse in web and data miningContact person
FRANCESCO PIERRIEmail:
francesco.pierri@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Web page:
pierri.faculty.polimi.itDescription
Description:
Publicly shared datasets are crucial for research in web and data mining, yet their reuse remains understudied. Many conferences now feature dataset or resource tracks, highlighting the growing importance of data sharing. This project seeks to quantify dataset reuse by analyzing research papers, tracking dataset mentions, and identifying key trends in adoption. We aim to determine which datasets are most influential and what factors impact their reuse, such as accessibility and documentation. Understanding these patterns will inform best practices for dataset sharing and encourage greater transparency in research.
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Real-Time Heart Signal Anomaly Detection and Prevention Using Radar TechnologyContact person
SILVIA MURAEmail:
silvia.mura@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Francesco LinsalataDescription
Description:
This thesis focuses on developing algorithms to detect anomalies in heartbeat signals captured by radar, with an emphasis on decoupling cardiac signals from respiration to enhance detection accuracy. The research incorporates Integrated Sensing and Communication (ISAC), enabling radar systems to seamlessly combine physiological monitoring with communication functionality.
The student will design and implement methods for detecting or preventing heart rate anomalies, such as arrhythmias, and validate their performance through measurement campaigns using real radar data. The ultimate goal is to deliver a low-complexity, real-time solution for healthcare applications and preventative monitoring.
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Semantic Signal Reconstruction for Restoring Nerve Signal PropagationContact person
SILVIA MURAEmail:
silvia.mura@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Maurizio MagariniDescription
Description:
This thesis explores a novel approach to restoring nerve function through semantic signal reconstruction, designed to act as a relay system for damaged nerves. By focusing on the "semantic meaning" of neural signals—the critical information necessary for physiological responses—this method bypasses the need to replicate the entire signal, enabling efficient and targeted signal propagation across injured sections. The work emphasizes low-complexity algorithms and real-time processing, making the approach suitable for implantable devices like cuff electrodes. These devices capture, interpret, and regenerate nerve signals, ensuring seamless communication despite nerve damage.
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Simulating social media platforms with LLMsContact person
FRANCESCO PIERRIEmail:
francesco.pierri@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Web page:
pierri.faculty.polimi.itDescription
Description:
This thesis explores using LLMs to simulate social media interactions, enabling controlled studies of digital discourse, misinformation, and user behavior. It proposes a framework for generating artificial social media environments, analyzing emergent behaviors, and assessing realism. The research applies reinforcement learning and network analysis to model interactions, offering insights for policy-making, marketing, and cybersecurity. The study aims to enhance understanding of algorithmic influence, misinformation spread, and engagement patterns in online communities.
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Communication beam alignment and tracking for motorsport applicationsContact person
MATTIA BRAMBILLAEmail:
mattia.brambilla@polimi.itStudy course: Automation Engineering, Telecommunications Engineering
Description
Description:
The thesis focuses on the design and assessment of a beam alignment and tracking technique (e.g. for 6G communication systems) to guarantee an optimal V2X communication between a motorbike and a base station. The challenges to be addressed include the compensation of motorbike tilting (especially while turning) and the estimate of the beam pointing direction. An approach based on retrieving the information from on-board sensors is to be preferred. The activity is partially in cooperation with the automation group of DEIB.
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Signal processing for 6G - MSc thesis in collaboration with Universitat de ValènciaContact person
MATTIA BRAMBILLAEmail:
mattia.brambilla@polimi.itStudy course: Telecommunications Engineering
Description
Description:
This thesis should be carried out in collaboration with the Universitat de València.
The research topic should be jointly agreed with the candidate and the abroad professor.
The student is requested to have signal processing skills.
Preference is given to the following topics: positioning, channel estimation, integrated sensing and communication
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Joint positioning and synchronization in 5G and beyond networksContact person
MATTIA BRAMBILLAEmail:
mattia.brambilla@polimi.itStudy course: Telecommunications Engineering
Other members of the research group:
Monica NicoliDescription
Description:
The inter-base station (BS) and BS-user synchronization errors pose a serious challenge to highly accurate positioning using5G cellular network. The objective of this thesis is to review state of the art approach on the topic, compare them from an implementation point of view and simulate the impact of synch errors. It is primary objective to use a Matlab-based simulator, however it is also possible to evaluate the algorithms with real 5G network data.
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5G-enabled passive radar for detecting unauthorized dronesContact person
MAURIZIO MAGARINIEmail:
maurizio.magarini@polimi.itStudy course: Automation Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Davide ScazzoliDescription
Description:
The goal of the proposed master's thesis is to investigate the detection of unauthorized drones using a passive bistatic radar (PBR) system that leverages a 5G base station as the transmitter. This method utilizes existing infrastructure, making it a cost-effective solution for drone surveillance. The detection process involves modeling the communication environment between the 5G base station and the drone, and analyzing the signals reflected from the drone. A crucial aspect of the study is calculating the Radar Cross Section (RCS) to measure how the drone scatters radar signals. By combining signal analysis with RCS calculations, the system can detect small, agile drones in complex environments. The thesis evaluates the system's performance with a specific drone model under various conditions, demonstrating that integrating PBR with 5G networks can effectively detect and track unauthorized drones, enhancing security in critical areas.
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Cellular infrastructure for weather monitoringContact person
DARIO TAGLIAFERRIEmail:
dario.tagliaferri@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Description
Description:
The thesis aims at studying the potential of the cellular infrastructure for the retrieval and monitoring of rain.
The goal of the work is to investigate the potential of the cellular network to be use for weather forecasting, towards greener environments.
The student will learn how to model and process the cellular signals to estimate the rain precipitation rate, and validate the simulations on experimental data acquired with a 5G cellular base station.
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LEO satellites for communication and environment monitoringContact person
DARIO TAGLIAFERRIEmail:
dario.tagliaferri@polimi.itStudy course: Automation Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Francesco LinsalataDescription
Description:
Low Earth orbit (LEO) satellites, e.g., Starlink, will be a keystone in future 6G non-terrestrial wireless networks. In addition to the communication functionality, LEO fleets can also serve for accurate Earth monitoring, with applications ranging from infrastucture monitoring, public security, surveillance and environmental reconstruction.
The thesis consists of exploring the use of LEO satellites to jointly ensure broadcast connectivity while obtain an accurate environment mapping.
The work will involve practical activities within the framework of the PNRR project "RESTART".
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AI for Cooperative Perception in Vehicular Radar NetworksContact person
DARIO TAGLIAFERRIEmail:
dario.tagliaferri@polimi.itStudy course: Automation Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Description
Description:
The road towards autonomous driving expects vehicles will be equipped with more and more heterogeneous sensors (cameras, lidars, radars, sonars) to perceive the surroundings. Cameras and lidars are the golden standard for autonomous driving, providing high-resolution representations of the environment, but they are sensitive to illumination levels and weather conditions (fog, rain,etc).
Radars, instead, are robust to adverse weather conditions, but are typically characterized by low spatial resolution in the description of the environment and they are currently used for limited purpose (emergency braking).
To improve the reliability of the perception of the environment, future autonomous vehicles are expected to mutually cooperate, exchanging local measurements and features to augment perception.
The thesis aims at using artificial intelligence for cooperative perception based on radars. In particular, the goal of the thesis is to investigate novel AI architectures for aligning, synchronizing and fusing radar images generated at the single vehicles. The proposed thesis can be specialized to generic distributed radar networks, e.g., made of drones.
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Integrated sensing and communication for future 6G wireless systems in the upper mid-bandContact person
DARIO TAGLIAFERRIEmail:
dario.tagliaferri@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Marco MezzavillaWeb page:
Pi-Radio website: https://www.pi-rad.io/homeDescription
Description:
Integrated Sensing and Communication (ISAC) systems combine wireless communication and radar sensing capabilities within the same infrastructure. These systems leverage shared hardware, spectrum, and signal processing techniques to perform tasks like data transmission and environmental sensing simultaneously. ISAC enables applications such as autonomous driving, smart cities, publoc safety and surveillance. It is acquainted that the next generation (6G) of wireless systems will use the so-called upper mid-band (6-24 GHz), currently not used for communication systems. The upper mid-band that offer large bandwidth over a wide range of frequencies, opening the striking possibility of centimeter-level environment sensing and unprecedented .
The thesis aims at addressing the innovative design of an ISAC systems in the future 6G frequencies. The student can choose to address the 6G ISAC from the methodological perspective , finding new ways to integrate communication and sensing over multiple disaggregated bandwidths, or developing custom signal processing algorithms that can be validated with in-lab experimental measurements with the Pi-Radio hardware.
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DEFINIZIONE DI UN PROTOCOLLO PER PRODURRE UNA INTERFACCIA NEURALEContact person
MAURIZIO MAGARINIEmail:
maurizio.magarini@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electronics Engineering, Telecommunications Engineering
Other members of the research group:
Antonio CovielloDescription
Description:
La tesi si concentra sulla progettazione e la manifattura di una cuff electrode, un’interfaccia neurale da posizionare attorno a un nervo periferico per il campionamento del segnale nervoso. Lo studente sarà coinvolto in attività pratiche di laboratorio, con focus su biomateriali avanzati, tecniche di produzione, parziale progettazione circuitale e aspetti normativi. L’obiettivo è sviluppare un protocollo e un metodo di produzione che garantiscano un campionamento stabile ed efficace del segnale nel tempo.
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REALIZZAZIONE HARDWARE DI UN CHIP IMPIANTABILE PER APPLICAZIONI MEDICALIContact person
MAURIZIO MAGARINIEmail:
maurizio.magarini@polimi.itStudy course: Biomedical Engineering, Electrical Engineering, Electronics Engineering, Telecommunications Engineering
Other members of the research group:
Antonio CovielloDescription
Description:
La tesi si concentra sulla progettazione e sviluppo hardware di un chip impiantabile, con focus sull’acquisizione e trasferimento dei segnali biomedicali. Lo studente sarà coinvolto nella scelta, configurazione e integrazione delle componenti elettroniche per la realizzazione del dispositivo. L’ottimizzazione si orienterà verso applicazioni mediche future sull’uomo, puntando a miniaturizzazione del segnale medicale, efficienza energetica e affidabilità a lungo termine.
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Design of an eye tracking device exploiting mmWaves radarContact person
MAURIZIO MAGARINIEmail:
maurizio.magarini@polimi.itStudy course: Biomedical Engineering, Electrical Engineering, Electronics Engineering, Telecommunications Engineering
Other members of the research group:
Davide ScazzoliDescription
Description:
Eye-tracking capabilities have applications across a wide range of fields, including entertainment, medicine, and security. This thesis proposes the development of novel algorithms and devices that exploit mmWave radars for visual gaze analysis. The candidate will focus on both the practical aspects and the more abstract algorithmic components of the problem. The work includes an experimental phase involving the design of PCBs using commercial sensors to validate the developed algorithms. Additional extensions of this thesis will explore integrated sensing and communication using the same device.
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Predictive Smart Irrigation Systems for Optimizing Plant Health Using Electrophysiological and Environmental Sensors with Deep LearningContact person
IMEN BEKKARIEmail:
imen.bekkari@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Imen BekkariDescription
Description:
This thesis aims to develop a predictive smart irrigation system by integrating electrophysiological sensors, electronic noses, and environmental sensors to monitor and analyze plant health. The model will optimize irrigation practices through neural networks to enhance water efficiency and promote sustainable agriculture in controlled and natural environments.
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Integrated Sensing and Communication for Vehicle to Anything (V2X) CommunicationContact person
MAROUAN MIZMIZIEmail:
marouan.mizmizi@polimi.itStudy course: Telecommunications Engineering
Description
Description:
As 6G networks advance, integrating sensing and communication in vehicular scenarios is critical for the development of autonomous driving. In these environments, vehicles must not only communicate with each other and with infrastructure but also sense and interpret their surroundings in real-time. This dual functionality introduces significant challenges in how communication and sensing are managed, especially in fast-moving, complex vehicular environments.
This thesis will focus on the challenges of enabling effective communication and sensing in vehicular scenarios to support autonomous driving. Key research areas will include developing strategies for real-time data exchange between vehicles and infrastructure, ensuring that both sensing and communication tasks can be performed reliably at high speeds. The research will explore how to optimize the sharing of sensor data among vehicles, enabling them to interpret their environment and make driving decisions collaboratively. Additionally, the study will address the limits of current technologies in handling the vast amount of data generated in these scenarios, exploring ways to enhance both the bandwidth and reliability of vehicular communication networks.
The ultimate goal of this thesis is to contribute to the development of 6G-enabled vehicular networks by addressing the technical challenges of integrating communication and sensing for autonomous driving. This involves creating new models, protocols, and algorithms that ensure vehicles can effectively collaborate, sense their environment, and communicate critical information in real-time, all within the dynamic and demanding context of autonomous driving scenarios.
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Enhancing Spatial Audio with Advanced Neural Network Models for Sound field reconstructionContact person
MIRCO PEZZOLIEmail:
mirco.pezzoli@polimi.itStudy course: Telecommunications Engineering
Description
Description:
This thesis proposal focuses on advancing the field of spatial audio by addressing the challenges of sound field reconstruction. Central to many 3D audio and virtual reality applications, accurate sound field reconstruction enhances the immersive experience by providing realistic auditory environments. The research aims to integrate innovative neural network models, including advanced kernel interpolation techniques, to overcome existing limitations in the field.
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