Machine Learning for Quantum ComputingContact person
MAURIZIO FERRARI DACREMAEmail:
maurizio.ferrari@polimi.itStudy course: Computer Science and Engineering
Other members of the research group:
Riccardo Nembrini; Riccardo Pellini; Gloria Turati; Paolo CremonesiWeb page:
https://mauriziofd.github.io/Description
Description:
Quantum Computing (QC) has the potential to shape the future of high performance computing and Machine Learning (ML) applications thanks to the speed-ups it promises for certain tasks. However, ML techniques can also help to overcome some of QC's current technological limitations. This research aims to study how QC and ML can be best combined in practice and how they can be of help to each other. Examples of topics are the development of ML methods to design and optimize quantum circuits for specific architectures.
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Good graphs versus bad graphs in 3D reconstructionContact person
FEDERICA ARRIGONIEmail:
federica.arrigoni@polimi.itStudy course: Computer Science and Engineering
Description
Description:
A powerful tool to study and solve relevant problems in Computer Vision (and, more precisely, in the sub-field of multi-view geometry) is representing cameras/images and their pairwise relations as vertices and edges of a graph. In this context, a prominent problem is 3D reconstruction from images and a relevant question is the following: which graphs are good and which graphs are bad for 3D reconstruction? This thesis will develop novel methods aimed at answering this question. A strong mathematical background is preferred but not mandatory. Reference: F. Arrigoni, A. Fusiello, T. Pajdla. A direct approach to viewing graph solvability. ECCV 2024
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Music Deepfake DetectionContact person
LUCA COMANDUCCIEmail:
luca.comanducci@polimi.itStudy course: Telecommunications Engineering
Description
Description:
Deep learning-based music generation has been recently revolutionized by the introduction of Text-To-Music models.
These models are characterized by being good in terms of performance and also simple to use, lowering the technical proficiency needed to successfully interact with them. This combination of factors has made them extremely appetible to the general public and of interest by private industries.
In Fact several commercial TTMs have been proposed, which recently have been sued by major record companies and have consecutively admitted to copyright infringement, by training their respective models also using unlicensed music. As both the capabilities and the commercial interest of these models grow it is becoming increasingly necessary to try to develop forensic approaches to detect and analyze music generated via TTMs.
In this thesis we aim at exploring the problem of: can we detect if some music is AI-generated or not?
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Fast simulation of a CPU+FPGA system through open-source toolsContact person
SERENA CURZELEmail:
serena.curzel@polimi.itStudy course: Computer Science and Engineering
Description
Description:
The goal of this thesis is to improve the design of FPGA-accelerated systems by building a faster simulation environment than the one provided by AMD/Xilinx, building upon existing open-source tools such as gem5 and Bambu HLS. Knowledge of hardware design is not required (but it could help).
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Development of Novel Transient Execution Attacks (TEAs): Exploiting Microarchitectural VulnerabilitiesContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis investigates the development of new transient execution attacks (TEAs) that exploit microarchitectural vulnerabilities in modern processors. The research will focus on identifying weaknesses in the execution pipeline, speculative execution mechanisms, and related hardware features, demonstrating how these can be leveraged to bypass traditional security measures. Additionally, the thesis will aim to propose countermeasures and mitigations to defend against these emerging threats, enhancing the security of future processor architectures.
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Development of Novel Trusted Execution Environments (TEEs)Contact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis focuses on the design and development of new Trusted Execution Environments (TEEs) to enhance the security of computing systems. The research will explore innovative TEE architectures that provide improved protection for sensitive data and operations, particularly in embedded systems, ensuring that security is maintained even in the presence of malicious attacks (Transient Execution Attacks like Spectre and Meltdown, for example) or software vulnerabilities.
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Design of Integrated GPU Architectures for RISC-V System-on-Chip (SoC) PlatformsContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis explores the development of new integrated GPU architectures within RISC-V SoC platforms. By designing GPU modules that are seamlessly integrated with the RISC-V architecture, the research will focus on improving graphical processing efficiency and enabling more powerful and energy-efficient SoC solutions for diverse applications.
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Analysis and Improvement of RISC-V Memory Models: Performance Limitations and BottlenecksContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis will conduct a comprehensive study of the RISC-V memory models, identifying potential performance limitations and bottlenecks. The research will aim to propose improvements that can enhance memory management, consistency, and overall system performance, with a focus on scalability and reliability in complex computing environments.
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Development of Machine Learning for Real-Time Error Detection and Attack Prevention in RISC-V Processors Based on System MeasurementsContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis focuses on developing a machine learning (ML) system for detecting errors and potential attacks in real-time by analyzing various system measurements, including microarchitectural data. The research will explore which system metrics are most effective for accurate detection and how the ML system can interact directly with hardware to perform error correction, reconfiguration, or deactivation in response to detected issues.
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Leveraging Large Language Models (ChatGPT et al.) to counter online misinformation and hate speechContact person
FRANCESCO PIERRIEmail:
francesco.pierri@polimi.itStudy course: Computer Science and Engineering
Web page:
https://pierri.faculty.polimi.itDescription
Description:
This thesis explores the potential of large language models, such as ChatGPT, to identify, flag, and mitigate online misinformation and hate speech. It aims to evaluate their effectiveness in real-time monitoring, content moderation, and counter-messaging, while addressing ethical considerations such as bias and free speech.
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Studying human behavior in Online Multiplayer Games (e.g., League of Legends, DOTA)Contact person
FRANCESCO PIERRIEmail:
francesco.pierri@polimi.itStudy course: Computer Science and Engineering
Other members of the research group:
Francesco CorsoWeb page:
https://pierri.faculty.polimi.itDescription
Description:
This thesis focuses on analyzing patterns of human behavior in online multiplayer games like League of Legends and DOTA. By examining player interactions, cooperation, competition, and toxic behavior,we want to understand how game mechanics and community dynamics influence player psychology and social engagement.
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Analyzing political targeted advertising on Meta (Facebook, Instagram) platformsContact person
FRANCESCO PIERRIEmail:
francesco.pierri@polimi.itStudy course: Computer Science and Engineering
Web page:
https://pierri.faculty.polimi.itDescription
Description:
This research aims to investigate the dynamics of political targeted advertising on Meta platforms. The objective is to understand how user data is leveraged for political campaigns, the impact on voter behavior, and the ethical implications of micro-targeting in democratic processes.
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Computational approaches for investigating conspiracy theories on TikTok and YouTubeContact person
FRANCESCO PIERRIEmail:
francesco.pierri@polimi.itStudy course: Computer Science and Engineering
Other members of the research group:
Francesco CorsoWeb page:
https://pierri.faculty.polimi.itDescription
Description:
This research explores the spread and impact of conspiracy theories on TikTok and YouTube. The idea is finalyzed to analyze content creation, and user engagement to understand how conspiracy-based content spreads on these platforms. Specifically:
- Study the prevalence of conspiracy theories using novel LLMs and V-LLMs
- Study correlation between conspiracy theories and political activity
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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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Perceptive 6G Wireless Cellular NetworkContact person
MAROUAN MIZMIZIEmail:
marouan.mizmizi@polimi.itStudy course: Telecommunications Engineering
Description
Description:
As 6G networks evolve into perceptive mobile networks that integrate sensing and communication, a key challenge lies in enabling distributed nodes to collaborate effectively. These networks aim not only to transmit data but also to sense and interpret the environment, which requires new approaches to both communication and sensing. The shift to a perceptive network model introduces significant challenges in how these distributed nodes interact, share information, and operate cohesively to achieve both sensing and communication goals.
This thesis will focus on the critical challenges of making 6G networks capable of sensing and communication using distributed nodes. A major area of investigation will be how to enable these nodes to collaborate efficiently, ensuring that sensing tasks do not compromise communication performance and vice versa. The research will explore strategies for distributed sensing, cooperative communication, and the coordination mechanisms needed to manage these dual functions across the network. Additionally, the study will address the limitations of current technologies in supporting such a collaborative, multi-functional network, identifying potential bottlenecks and proposing innovative solutions.
The ultimate goal of this thesis is to contribute to the development of 6G perceptive mobile networks by addressing the technical challenges of distributed sensing and communication. This involves creating new models and algorithms that allow for efficient collaboration among distributed nodes, ensuring that the network can operate effectively within the constraints of real-world environments.
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Signal Processing for Near-Field 6G SystemsContact person
MAROUAN MIZMIZIEmail:
marouan.mizmizi@polimi.itStudy course: Telecommunications Engineering
Other members of the research group:
Umberto SpagnoliniDescription
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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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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Compiler-assisted real-time schedulingContact person
FEDERICO REGHENZANIEmail:
federico.reghenzani@polimi.itStudy course: Computer Science and Engineering
Description
Description:
This thesis wants to explore the possibility to use the compiler to provide scheduling hints to the real-time operating system, especially on the Worst-Case Execution Time (WCET). This thesis aims at modying the open source LLVM compiler to instrument the final code with proper mechanisms.
Please contact me for further details.
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Real-time scheduling for SIHFT approachesContact person
FEDERICO REGHENZANIEmail:
federico.reghenzani@polimi.itStudy course: Computer Science and Engineering
Description
Description:
This thesis aims at studying novel scheduling approaches for real-time operating systems that run Software-Implemented Hardware Fault Tolerance (SIHFT) mechanisms. SIHFT are a set of techniques that detect and recover from hardware faults by using software methods. However, their computational overhead is huge and novel scheduling algorithms must be invented to efficiently schedule the real-time tasks.
The thesis is highly innovative and composed of both theoretical and practical parts. The scheduling algorithm will be implemented and tested on a real system.
No particular pre-requisites exist other than being self-motivated: the background of any POLIMI student will be sufficient. The programming language that will be used to implement the scheduler is C.
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[Tesi senza Controrelatore] Analysis and comparison of real-time performance of GPGPU librariesContact person
FEDERICO REGHENZANIEmail:
federico.reghenzani@polimi.itStudy course: Computer Science and Engineering
Other members of the research group:
Tomas Antonio LopezDescription
Description:
Using the GPU for general-purpose computing (GPGPU) has become common in many fields thanks to the parallelism of GPU and the emerging of novel applications. Some systems are, however, safety-critical systems with strict timing and functional correctness requirements to be satisfied. This thesis will analyse the available libraries for GPGPU in terms of real-time performance with a special focus to open source safety-critical libraries.
Please contact me for further details.
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INTERACTION DESIGN FOR LIVE PERFORMANCE OF ACOUSMATIC MUSIC (In collaboration with Fondazione Culturale San Fedele)Contact person
LUCA COMANDUCCIEmail:
luca.comanducci@polimi.itStudy course: Telecommunications Engineering
Other members of the research group:
Francesca RonchiniDescription
Description:
Experimental music and technology developments have always went hand in hand, from the development of the synthesizer to the recent introduction of artificial intelligence in music production practices. INNER SPACES is a series of events related to experimental electronic music and audiovisual arts realized in the exclusive context of the San Fedele Auditorium, in Milan. The objective of the thesis is to develop tools for augmented performance in the context of acousmatic/electronic music, with the possibility of including the developed software in the second season of INNER SPACES (spring). While the project will be focused on scientific developments related to audio and programming, a keen interest and motivation for art and experimental music is highly desired. For any information please contact: luca.comanducci@polimi.it or francesca.ronchini@polimi.it
Preferred Requirements:
Experience in python/supercollider/MaxMsp
Interest for acousmatic/experimental electronic music
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Design fault recovery strategies for FreeRTOSContact person
FEDERICO REGHENZANIEmail:
federico.reghenzani@polimi.itStudy course: Computer Science and Engineering
Web page:
https://reghenzani.faculty.polimi.it/Description
Description:
Embedded systems are often subject to reliability requirements against transient faults that usually occur due to high-energy particles striking memory cells and causing data corruption. This is a problem in space applications, where the atmosphere and the magnetic field of the Earth have a lower shield effect, but it is also a problem on Earth for safety-critical applications. In current research projects, we developed a mechanism to detect faults occurring not only in the application but also in the operating system, specifically FreeRTOS. The objective of this thesis would be to implement novel mechanisms to perform the recovery of such faults occurring in the operating systems.
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Sviluppo software di generazione e acquisizione di trame 5G per strumentazione da laboratorioContact person
DAVIDE SCAZZOLIEmail:
davide.scazzoli@polimi.itStudy course: Telecommunications Engineering
Other members of the research group:
Maurizio Magarini, Umberto Spagnolini, Christian MazzuccoDescription
Description:
Questa tesi verterà principalmente sullo sviluppo di codice per l'acquisizione, la sincronizzazione e la decodifica di trame 5G acquisite tramite oscilloscopi Lecroy di ultimissima generazione. Nella tesi sarà inclusa anche la parte duale sulla generazione di suddette trame mediante generatori arbitrari Tektronix. Lo sviluppo del codice avverrà principalmente in MATLAB, con l'ausilio dei toolbox 5G per la generazione e decodifica delle trame standard compliant. Questo codice MATLAB verrà quindi caricato sull'oscilloscopio ed eseguito in tempo reale dalla macchina su segnali reali.
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Deep Learning-based attack detection in RISC-V microprocessorsContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
Modern microprocessors have advanced features like cache hierarchies, acceleration units, out-of-order and speculative execution: on the one hand, all these features dramatically increase systems performance but, on the other hand, they expose the system to a new menace: the so-called Microarchitectural Side-Channel Attacks (MSCAs), such as Spectre and Meltdown. Protecting a system from these attacks is extremely challenging, and this becomes even harder in the embedded scenario, where Operating System support and multiple cores may be unavailable.
This thesis aims at exploring the feasibility of adopting hardware performance counters (HPCs) monitoring and deep learning (DL)-based anomaly detection (for example Recurrent Neural Networks) to identify the execution of MSCAs in embedded microprocessors. The basic idea is to add a Security Checking module between the microprocessor and the main memory to observe the fetching activity and the HPCs. The introduced checker shal neither interferes with the nominal activity of the microprocessor nor requires any modification of the microprocessor itself. Existing RISC-V microprocessors could be considered as a target hardware platform.
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Enhancing Space Launcher Safety with Telemetry Anomaly Detection (in collaboration with the European Space Agency)Contact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Other members of the research group:
Marco Ottavi (University of Twente, The Netherlands)Web page:
https://cassano.faculty.polimi.itDescription
Description:
The Imperative for Anomaly Detection in Space Applications, particularly in launcher systems, is critical. Space missions represent high-stakes endeavors where even minor anomalies can lead to mission failure, causing significant financial losses and scientific setbacks. Furthermore, anomalies within launcher systems pose substantial safety hazards, potentially leading to catastrophic events.
Within the domain of launchers, telemetry data serves as a cornerstone, providing real-time insights into the vehicle's operational status. The Avio telemetry avionics, meticulously designed to capture crucial data, can transmit to ground stations by monitoring the communication bus or acquiring I/O signals. This setup ensures comprehensive data retrieval, addressing both software and hardware elements of aircraft systems.
Anomalies within this data stream can indicate potential issues, ranging from equipment malfunctions to trajectory deviations or unforeseen complications. Timely identifying these anomalies allows for proactive intervention, mitigating the risk of mission failure or catastrophic incidents.
Integrating Artificial Intelligence (AI) into Anomaly Detection presents a promising avenue for overcoming these challenges. AI algorithms can analyze vast quantities of telemetry data in real time, identifying patterns and anomalies that may elude human operators. This capability not only enhances the safety and success rate of space missions but also propels advancements in space exploration technology. This proposal outlines a project to harness AI for telemetry anomaly detection in Space Transportation systems, focusing on both the identification of suitable AI models and the hardware implementation on platforms.
This proposal outlines a two-part project to detect launcher telemetry anomalies using Artificial Intelligence (AI). The first part involves the identification of the most suitable AI model and the consequent design and development of an AI-based engine for anomaly detection. The second part focuses on the hardware implementation of the previously designed AI-based engine on an embedded architecture, e.g., a RISC-V platform.
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Advanced communications for autonomous systems (vehicle-vehicle, drone-vehicle) in emergency situations.Contact person
FRANCESCO LINSALATAEmail:
francesco.linsalata@polimi.itStudy course: Automation Engineering, Computer Science and Engineering, Telecommunications Engineering
Description
Description:
The thesis entails the study and analysis of vehicular communications utilization in emergency scenarios. This research is a component of the RESTART project and is conducted in partnership with an Italian company specializing in the field.
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Design and implementation of a unifying FAIR repository for genomic tracksContact person
ANNA BERNASCONIEmail:
anna.bernasconi@polimi.itStudy course: Computer Science and Engineering
Web page:
https://annabernasconi.faculty.polimi.it/theses/Description
Description:
FAIR is an acronym that describes the characteristics of a data resource of being Findable, Accessible, Interoperable, and Reusable. In this thesis, you are going to deal with FAIR genomic annotations, a specific data type that is very useful in genomic research. First, we are going to design a minimal FAIR metadata schema for genomic annotations that builds on the existing FAIRtracks metadata schema, further harmonized with relevant data models such as from the Genomic Conceptual Model.
We will then build 1) an actual infrastructure that adopts the schema, which should support scalable and maintainable data flows for transforming existing metadata sources to support the minimal schema (exploiting the Omnipy Python library) and 2) a standardized API for downstream search and discovery that works independently of a particular implementation of a search service.
This thesis will be run in the context of the FAIRification of Genomic Annotations Working Group of the Research Data Alliance, collaborating with scientists from many institutions.
Resources: https://f1000research.com/articles/10-268, https://doi.org/10.1007/978-3-319-69904-2_26, https://doi.org/10.1109/TCBB.2020.2998954, https://doi.org/10.1093/database/baz132
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Programming and testing real-life 5G networks within the O-RAN architectureContact person
EUGENIO MOROEmail:
eugenio.moro@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Viola Bernazzoli, Ilario Filippini, Antonio CaponeDescription
Description:
Open-RAN (O-RAN) is an architectural overhaul of the traditional Radio Access Network (RAN) that promises to bring flexibility and programmability to 5G and beyond. The work of this thesis proposal focuses on the development of so called xApps and rApps: network microservices of the O-RAN architecture that implement arbitrary network optimization solutions. Master students working on this thesis can expect to modify and write full stack 5G code and test it over real equipment in the private 5G network of Antlab. Prerequisites: basic programming knowledge in C, Python - basic communication network knowledge
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A data-driven approach for storing and analyzing Causal Loop DiagramsContact person
ANNA BERNASCONIEmail:
anna.bernasconi@polimi.itStudy course: Computer Science and Engineering
Other members of the research group:
Stefano Ceri, Chiara LeonardiWeb page:
https://annabernasconi.faculty.polimi.it/theses/Description
Description:
Systemic Design aims to grasp the intricate behavior of socio-technical systems; their hidden patterns are unveiled by making use of Causal Loop Diagrams (CLDs), which visually represent systems' behaviors at an abstract level. In these diagrams, nodes represent variables shaping a system's dynamics, while edges highlight causal relationships, emphasizing the interplay between nodes. Loops, as cyclic paths from one variable back to itself, are categorized as either balancing (B) or reinforcing (R), shedding light on the system's inherent dynamics. CLDs find applications across various domains, from urban planning and environmental sustainability to organizational management and public health.
Our step forward in the study of CLDs is the recent design of an innovative metamodel, which serves as the foundation for a systematic approach to understanding CLDs. In your thesis, your task will be to create a dynamic repository that not only houses our metamodel but also enables systematic analysis of any given system. By documenting nodes and edges, extracting loops, and categorizing them, you will exploit data-driven methods for discovering critical aspects of socio-technical systems.
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Designing reliable DL applications against hardware faultsContact person
CRISTIANA BOLCHINIEmail:
cristiana.bolchini@polimi.itStudy course: Computer Science and Engineering
Other members of the research group:
Antonio Miele, Luca CassanoWeb page:
https://bolchini.faculty.polimi.it/Description
Description:
Hardware faults are either permanent or transient faults that affect the hardware platform running (Deep Learning as a case study) applications so that the output differs from the expected, fault-free one. The nature of the effects of the faults depend on i) the hardware architecture, ii) the kind of fault, and iii) the running application. The specific nature of DL applications allows to leverage their inherent tolerance to tailor both analysis and hardening solutions.
The goal of this thesis is to develop methods and tools to make the overall system resilient to hardware faults; techniques can work either at software or hardware level, and can take into consideration different hardware platforms.
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GALVANIC CURRENT INTRABODY COMMUNICATION FOR ENHANCED DEVICE CONNECTIVITYContact person
MAURIZIO MAGARINIEmail:
maurizio.magarini@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Ing. Antonio CovielloDescription
Description:
La tesi si propone di definire un protocollo di comunicazione ottimale per far comunicare due dispositivi impiantati all'interno del corpo umano in modo sicuro e veloce. Due microcontrollori impiantati dopo aver compresso i dati mediante il metodo "spiking", comunicheranno tra loro tramite l'utilizzo di correnti galvaniche, un approccio innovativo e sicuro che risolve problematiche associate all’invasività dei dispositivi medicali. Oltre alla ricerca sperimentale e test in laboratorio, verranno svolte simulazioni in COMSOL per studiare un modello che descriva il movimento delle correnti all'interno del corpo umano. La durata della tesi sarà di 9-12 mesi, è possibile fare la tesi di coppia, sono previste collaborazioni con altri gruppi di ricerca, aziende e università (Pavia).
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Unveiling Security Vulnerabilities of RISC-V Microprocessors (in collaboration with the European Space Agency)Contact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
RISC-V Microprocessors are becoming more and more popular due to their openess and extendability. On the other hand, no extensive security assessment of such computing platform has been carried out. In particular, we aim at studying whether popular Microarchitectural Side-Channel Attacks (MSCAs) like Spectre, Meltdown and similar attacks, can represent potential threats for RISC-V processors. Indeed, MSCAs have been demonstrated to be very effective against x86 and ARM processors, while few studies have been conducted to evaluate their dangerousness against RISC-V.
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Designing Secure RISC-V Microprocessors (in collaboration with the European Space Agency)Contact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
Modern integrated circuits for are produced following a distributed design-flow where will modules designed in-house are integrated with other modules coming from third party entities, either
in the form of Third-Party IP cores (3PIPs) or in the form of Commercial Off-the-Shelf (COTS) components. Moreover, the final fabrication of the silicon device will rely on outsourced foundries. While ensuring high-performance and reduced cost, such globalized design process exposes the obtained system to several security threats both at design time and at runtime. Integrated circuits (ICs) may be overproduced by the foundry and sold in the black market, defective or dismissed ICs may be delivered as good ones, IP core licenses may be violated, and IP cores may be overused, designs may be maliciously modified to insert stealthy unwanted functionalities in the final product, the so-called Hardware Trojan Horses (HTHs). We envision to integrate Intelligent Security Checkers (ISCs), based on embedded machinelearning and probabilistic data structures, within a SoC where several microprocessors and HW accelerators interact. The goal of such ISCs is to monitor the activity carried out at runtime by the components in the SoC to prevent the activation of HTHs and to limit their dangerousness once they have been activated. The overall goal of this thesis is to enable trusted execution over a system composed of both trusted and untrusted components. As a beneficial additional side-effect, such ISCs would also allow to detect anomalous behaviors due to random faults (e.g. Soft Errors in memories, SEUs in registers) instead of malicious attacks. Of course, it is mandatory for the introduced security checker not to interfere with the nominal functioning of the system, i.e., not to introduce working frequency slow-down, and to bring the smallest possible silicon area and power consumption overhead.
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Analysis of the Effects of Single Event Upset (SEU) Faults in Deep Neural Networks Accelerated on RISC-V CoresContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Other members of the research group:
Antonio MieleWeb page:
https://cassano.faculty.polimi.it/Description
Description:
The great quest for adopting Deep Learning-based computations for safety-/mission-critical applications motivates the interest towards methods for assessing the robustness of the application w.r.t. not only its training/tuning but also errors due to faults, in particular soft errors, affecting the underlying hardware. The RISC-V open source Instruction Set Architecture is nowadays gaining more and more interest due to its openess, extendability and flexibility; indeed, there is great interest in employing RISC-V accelerators to run Deep Learning Applications in embedded systems. The thesis will focus on analysing how SEU fauilts occurring in the HW architecture of the RISC-V microprocessor would affect the accuracy of the Deep Learning application under execution.
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Optimization strategies for resilient multi-core optical networksContact person
MASSIMO TORNATOREEmail:
massimo.tornatore@polimi.itStudy course: Telecommunications Engineering
Description
Description:
Spatial Division Multiplexing (SDM), and in particular Multi-Core Fiber (MCF) technology is emerging as the next generation scaling approach to face the so-called capacity crunch. While MCF appears as as a promising and practical solution to address this problem, it increases network complexity and poses new challenges to network resilience. The thesis goal is to investigate and implement optimization approaches that ensure survivability in the context of MCF networks while ensuring some energy efficiency constraints. The student is expected to develop ILP models and/or (meta) heuristics while accounting for the physical layer impairments in MCF networks.
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ML-based approaches for distributed Raman amplification configuration in C+L+S optical networksContact person
MASSIMO TORNATOREEmail:
massimo.tornatore@polimi.itStudy course: Telecommunications Engineering
Description
Description:
Multiband transmission is becoming a go-to solution for capacity scaling in optical networks. Transmitting in multiband optical networks leads to severe physical layer impairments that must be addressed to ensure lightpath feasibility. A promising approach to reach this goal is introducing distributed Raman amplification on top of the traditional EDFA amplification. However, the impact of introducing Raman amplification to a multiband network may vary depending on the working point of the Raman pumps (in terms of the pumps’ launch power and frequency). For example, if the launch power and frequency of the Raman pumps are not optimized, network resources can be utilized in a sub-optimal fashion due to severe degradation of the lightpaths' signal-to-noise ratio. Therefore, the objective of the thesis is to develop Machine Learning – based approaches (such as DRL) to set the working point of Raman pumps in order to maximize network resources. Currently, we have an in-house tool (Raman solver developed in C++) that models accurately the behaviour of the Raman pumps depending on the input parameters, i.e., configuration. Seeing that the working point of the Raman pump depends on several input parameters (power, frequency, span characteristics, channel power, channel spacing), it is necessary to develop DRL-based approaches to find the optimal working point of Raman pumps. The student will be provided the tool that models the Raman solver and will be tasked to develop ML-based approaches to set the optimal working point of the Raman pumps such that lightpath feasibility is guaranteed while maximizing network throughput.
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Electric Vehicle charging strategies evaluation and its effects on the electrical grid operation.Contact person
GIAMBATTISTA GRUOSSOEmail:
giambattista.gruosso@polimi.itStudy course: Automation Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering
Description
Description:
As part of the research activities of the simlab40 group, this thesis is concerned with working on several complementary aspects ranging from optimization, demand response to reinforcement learning.
The thesis has a part of modeling combined with a part of algorithms for operations research, optimization, AI .
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Electromagnetic design and topological optimization of electromagnetic devices for additive printingContact person
GIAMBATTISTA GRUOSSOEmail:
giambattista.gruosso@polimi.itStudy course: Automation Engineering, Electrical Engineering, Electronics Engineering
Description
Description:
The thesis aims to design and use optimization techniques to prototype and test an electromechanical device suitable for 3D printing.
In a context where the digital manufacturing of electromagnetic components can benefit from additive printing techniques, it is essential to study new design and characterization rules.
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Experimental Radio Access Networks architectures in HFCLContact person
MARCELLO MORINIEmail:
marcello.morini@polimi.itStudy course: Telecommunications Engineering
Other members of the research group:
Eugenio Moro, Ilario Filippini, Antonio CaponeDescription
Description:
Cellular networks are progressing toward higher frequencies. To unleash their full potential, new Radio Access Network architectures are currently being developed. Integrated Access and Backhaul (IAB) can provide the required network densification without incurring prohibitive costs. The scope of this thesis is to deploy a real IAB architecture, leveraging on O-RAN and the facilities of High-Frequency Campus Lab, the first commercial millimeter-wave 5G network dedicated to academic research. This type of work will provide important insights and data that can be a turning point for millimeter-wave deployment.
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Smart Radio Environments testing and characterization in HFCLContact person
MARCELLO MORINIEmail:
marcello.morini@polimi.itStudy course: Telecommunications Engineering
Other members of the research group:
Eugenio Moro, Ilario Filippini, Antonio CaponeDescription
Description:
The evolution of cellular networks is moving towards higher frequencies. To obtain the maximum from them, the optimization of the transmitters and receivers is no longer enough: the channel has to be modified. Reflective Intelligent Surfaces, Smart skins and reflectors can do the job. The scope of this thesis is to study, model and deploy a real smart radio environment in the context of the High-Frequency Campus Lab (HFCL): the first commercial millimeter-wave 5G network dedicated to academic research. This thesis, with a strong experimental slant, will produce original results, precious for academic research and commercial world
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Sviiluppo di un modello non lineare nel dominio del tempo per la compensazione dei trasformatori di misuraContact person
CHRISTIAN LAURANOEmail:
christian.laurano@polimi.itStudy course: Automation Engineering, Electrical Engineering, Electronics Engineering
Other members of the research group:
Sergio ToscaniDescription
Description:
Per poter modellare la non linearità del nucleo ferromagnetico del trasformatore, si possono utilizzare modelli non lineari nel dominio del tempo (modelli di Hammerstein-Weiner). Lo studente sarà quindi coinvolto nella fase di studio e modellazione tramite i modelli sopracitati dei trasformatori di misura.
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Caratterizzazione innovativa di trasformatori di tensione e corrente per misure di power qualityContact person
CHRISTIAN LAURANOEmail:
christian.laurano@polimi.itStudy course: Electrical Engineering
Other members of the research group:
Sergio ToscaniDescription
Description:
Il sistema elettrico non è più puramente sinusoidale, per questo motivo è necessario il monitoraggio della qualità della fornitura elettrica (in termini di distorsione armonica di tensione e corrente). Si valuterà perciò come poter modellare i trasformatori di misura per il monitoraggio delle armoniche di rete.
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Modellazione dell'andamento della capacità di batteria in funzione di invecchiamento e temperaturaContact person
CHRISTIAN LAURANOEmail:
christian.laurano@polimi.itStudy course: Automation Engineering, Electrical Engineering, Electronics Engineering
Other members of the research group:
Simone Barcellona, Marco FaiferDescription
Description:
La tesi prevede uno studio preliminare dello stato dell'arte dei modelli di invecchiamento e di andamento di capacità di batteria in funzione della temperatura. Dopodichè, si valuterà la coerenza tra gli algoritmi proposti e le prove effettuate in laboratorio.
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Sviluppo di un sistema per caratterizzazione di batterie in temperaturaContact person
CHRISTIAN LAURANOEmail:
christian.laurano@polimi.itStudy course: Automation Engineering, Electrical Engineering, Electronics Engineering
Other members of the research group:
Simone Barcellona, Marco FaiferDescription
Description:
Lo studente sarà inserito nel gruppo di ricerca che si occupa di modellazione delle batterie; in particolare, nella presente tesi si propone lo sviluppo di un sistema automatico per invecchiamento di batterie e misura dei relativi parametri caratteristici (e.g. capacità).
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Leveraging Large Language Models for Second Language Conversational Practice in Human-Agent InteractionContact person
MICOL SPITALEEmail:
micol.spitale@polimi.itStudy course: Computer Science and Engineering
Description
Description:
Second language acquisition poses several challenges given the cost and accessibility barriers associated with conversational practice (e.g., hiring an English mother tongue teacher for practising speaking skills).
This thesis aims at leveraging Large Language Models (LLMs) as valuable tools to embed in embodied agents (e.g., virtual agents, robots) for enhancing conversational practice in second language acquisition, such as learning English for Italian mother tongue speakers. By examining the implications of incorporating LLM into embodied agents for second language acquisition, this thesis will shed light on the innovative ways in which technology can contribute to effective conversational practice strategies.The ultimate goal will be to foster proficiency and confidence in real-life communication scenarios.
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