Elenco delle tesi del corso di laurea "Corso di laurea magistrale in Data Science And Engineering" nell'anno "2024"

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Luca Agnese. Analyzing Adolescent Emotional Concerns: An NLP Approach. Rel. Giuseppe Rizzo. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Lal Akin. Data-Driven Vehicle Performance Optimization for Formula Student Racing. Rel. Andrea Tonoli, Stefano Favelli, Dario Salza, Federico Oldani. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Qi An. Image Captioning Applied to Visual Artworks using Transformers. Rel. Giuseppe Rizzo, Angelica Urbanelli, Luca Barco. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Sergio Augusto Angelini. Generative AI for the Simulation of Autonomously Driven Vehicles. Rel. Claudio Ettore Casetti, Diego Gasco. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Dario Avalle. Machine Learning Model Online Deployment in Azure. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Reza Barati. Development of Automatic Technologies for Threat Intelligence and Identification of Indicators of Compromise (IoC) on Reddit. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Marcelo Bastos Lopes Ferreira. Correcting Geographic Data in Amazon’s EU and NA Networks: A Scalable Ad-hoc Regression-Based Solution. Rel. Guido Perboli, Filippo Velardocchia. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Bahareh Behrouzi. Enhancing Weed Detection and Segmentation with Advanced Deep Learning Algorithms leveraging RGB-NIR Imaging. Rel. Renato Ferrero, Nicola Dilillo. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Marina Benedetto. Investigating Deep Learning Generalization Capabilities for Non-Intrusive Load Monitoring from Synthetic to Real-World Datasets. Rel. Giuseppe Rizzo, Stefano Bergia. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Lorenzo Bergadano. From Quantum Quirks to Clear Skies: A Not-So-Dusty Road to Sensor Calibration. Rel. Bartolomeo Montrucchio, Edoardo Giusto, Pietro Chiavassa. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Matteo Berta. Towards a Gender Inclusive Neural Network for Automatic Gender Recognition. Rel. Tania Cerquitelli. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Federico Borra. In Silico Perturbation of Single Cells. Rel. Alfredo Benso, Francesca Buffa, Gianfranco Michele Maria Politano. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Jacopo Bracci. Language and Vision models for PET Assisted Reporting. Rel. Flavio Giobergia, Nicolo' Capobianco. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Allan Brunstein. Automatic web crawler for malicious websites classification. Rel. Marco Mellia, Rodolfo Vieira Valentim, Idilio Drago. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Davide Buoso. Select2Plan: Training-Free ICL-Based Planning through VQA and Memory Retrieval. Rel. Giuseppe Bruno Averta, Philipp Thorr, Daniele De Martini, Tim Franzmeyer. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Emanuel Buttaci. Does Perturbation Aid Convergence? An Alternative Approach to Federated Optimization Inspired by Spectral Graph Theory. Rel. Giuseppe Carlo Calafiore, Federico Della Croce Di Dojola. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Giovanni Cadau. Artificial Intelligence Algorithms for Electronic Component Recognition. Rel. Daniele Apiletti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Lorenzo Calosso. Mixing decomposition techniques and approximate dynamic programming for the Stochastic Electric Vehicle Routing Problem. Rel. Edoardo Fadda, Ornella Pisacane, Maurizio Bruglieri, Domenico Potena. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Andres Felipe Cardenas Meza. Robustness of Machine Learning algorithms applied to gas turbines. Rel. Danilo Giordano. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Alessandro Caruso. Deep Representation Learning for Sub-typing and Identification of Mental Health Symptoms via Multimodal Wearable Data. Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Alessandro Casella. Convolutional Autoencoder for Unsupervised Defect Detection in Brake Calipers. Rel. Vincenzo Randazzo, Eros Gian Alessandro Pasero, Marco Porrati, Edoardo Pareti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Luca Catalano. A Transformer-based approach to air quality prediction in Milan through satellite imagery combined with meteorological and morphological data. Rel. Giuseppe Rizzo, Giacomo Blanco. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Alberto Cavallo. Design and Deployment of a Metrics Store in a Data Warehouse: A Case Study on GitGuardian, a Cybersecurity Scale-Up. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Stefano Chiartano. Word Embedding applications for Anomaly Detection in financial data. Rel. Flavio Giobergia, Elena Maria Baralis, Danilo Giordano. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Gabriele Cirotto. Evaluating the Impact of AI-Generated Data on Training Keyword Spotting Models. Rel. Andrea Calimera, Valentino Peluso. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Simone Clemente. Cognitive Aware Incremental Knowledge Update of Large Language Models. Rel. Marco Mellia. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Ivan Dario Contreras Perez. Large Language Models for Ambiguity Detection and Resolution in Smart Homes. Rel. Luigi De Russis, Tommaso Calo'. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Giulia Cornara. Evaluating the entropy of physical systems using diffusion models. Rel. Paolo Garza, Pietro Michiardi. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Francesca Cossu. Optimizing deep learning models with feature engineering: a case study on crash detection with black box data. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Antonio Dal Maso. MID: A New Strategy for Learning Optimal Decision Trees on Continuous Data. Rel. Elena Maria Baralis, Siegfried Nijssen. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Marco Fabio De Souza Coelho. Efficiency improvement of Amazon’s logistic services using outline and simulation tools. Rel. Guido Perboli. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Giuseppe Desiderio. A Logic Tensor Network for Breast Cancer Detection in Mammography. Rel. Lia Morra. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Elena Di Felice. Computational Biases of Foundation Models for Speech Emotion Recognition: A Quantitative Analysis. Rel. Giuseppe Rizzo, Federico D'Asaro. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Niccolo' Dimonte. Centralized Monitoring Infrastructure on Cloud: An Open Source Approach. Rel. Daniele Apiletti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Matteo Donadio. Declarative Data Pipelines: implementing a logical model through automated code generation. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Mohammed El Dor. RICONOSCIMENTO AUTOMATICO DI TRACCE DI PARTICELLE NELLO SCATTERING NUCLEARE = AUTOMATIC RECOGNITION OF PARTICLE TRACES IN NUCLEAR SCATTERING. Rel. Lia Morra, Fabrizio Lamberti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Roya Esmaeilikorani. Comparative Analysis of Vector Databases for Real-Time Similarity Retrieval: Enhancing Large Language Model Performance. Rel. Giuseppe Rizzo. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Gaetano Salvatore Falco. TaskGraspNet: Object Detection and Task-Oriented Grasping in Cluttered Scenes. Rel. Giuseppe Bruno Averta, Luca Robbiano. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Khudayar Farmanli. Hierarchical Attention for Conversational Agents. Rel. Giuseppe Rizzo, Fabio Caffaro. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Umberto Fontana. Detection of Suspicious Behavior, through Machine Learning, on the applicative layer and data records. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Alberto Foresti. Towards more stable continuous-time functional diffusion processes. Rel. Tatiana Tommasi, Pietro Michiardi. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Arcangelo Frigiola. Supervised Contrastive Learning for Classification of Market Stock Series. Rel. Luca Cagliero, Jacopo Fior. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Matteo Garbarino. A Modern Solution for Big Data Management: the Data Lake. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Edgar Abraham Gaytan Quezada. Interacting Traceability Tool for R&D Prototyping. The Pirelli NEXT MIRS Case. Rel. Luca Settineri. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Giulia Gemesio. Comparative Analysis of Project Management Approaches: Fink's Case Studies and Critical Success Factors in Literature. Rel. Alberto De Marco, Filippo Maria Ottaviani. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Ali Ghasemi. Machine Learning Methods for Automated Z-Axis Calibration in Fluorescence Microscopy. Rel. Alessandro Savino, Roberta Bardini. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Francesco Grandi. Are spiking neural networks resilient to internal faults? A comparison with other neural network models and an analysis of possible solutions to increase resilience. Rel. Stefano Di Carlo, Alessandro Savino, Alessio Carpegna. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Jasmine Guglielmi. Demand Forecasting for Size Curve Optimisation in Luxury Retail. Rel. Daniele Apiletti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Gianluca Guzzetta. Mask2KAN: A Universal Image Segmentation Kolmogorov–Arnold Network Architecture. Rel. Carlo Masone, Shyam Nandan Rai. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Saeedeh Javadi. Knowledge Editing in Large Language Model. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Alessia Leclercq. scVEMO: Leveraging Single-cell Multiomics Data for Developmental Trajectory Reconstruction in the Embryonic Mouse Brain. Rel. Stefano Di Carlo, Alessandro Savino, Lorenzo Martini, Roberta Bardini. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Davide Leo. Federated Learning: Tackling Heterogeneous Network Challenges in Distributed Deep Learning. Rel. Barbara Caputo, Marco Ciccone, Eros Fani'. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Federica Lupo. Machine Learning-Driven Vision System for Detecting and Evaluating Compensatory Movements in Robot-Based Stroke Rehabilitation. Rel. Danilo Demarchi, Paolo Bonato, Giulia Corniani. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Aurora Maggiulli. Advanced Anomaly Detection in Structural Health Monitoring: A Case Study on Inclinometer Data from Italian Viaducts. Rel. Daniele Jahier Pagliari, Alessio Burrello, Luca Benfenati, Monica Longo, Fabio Tatti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Francesca Mangone. Autonomous Vehicle Integration: Pedestrian Behaviour Prediction. Rel. Andrea Bottino. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Edoardo Marchetti. 3DYogaSeg: A New Dataset and Benchmark for Skeleton-Based Action Recognition and Segmentation in yoga videos. Rel. Giuseppe Bruno Averta, Chiara Plizzari. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Francesco Marigioli. Real-Time Human Detection in World Rally Championship for danger recognition system. Rel. Flavio Giobergia, Andrea Avignone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Alessandro Masala. Deep Learning Analysis of ECG Signals for Early Myocardial Infarction Detection. Rel. Vincenzo Randazzo. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Valerio Mastrianni. Machine Learning in Renal Failure using voice as biomarker. Rel. Antonio Servetti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Carla Maria Medoro. Deep Learning-based Unsupervised Anomaly Detection on Energy Consumption Data. Rel. Paolo Garza, Marco Galatola. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Lorenzo Melchionna. Unsupervised Multivariate Time Series Segmentation: Driving Scene Identification Use Case. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Domenico Mereu. MARE-Graph: Multimodal Action Recognition in Egocentric video with Graph Neural Network. Rel. Giuseppe Bruno Averta, Simone Alberto Peirone, Francesca Pistilli, Antonio Alliegro. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Alessio Mongoli. The Use of LLMs in the Legal Field: Optimizing Contract Management with Generative Artificial Intelligence. Rel. Maurizio Morisio, Daniele Sabetta. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Sara Montese. Policy Graphs and Theory of Mind for Explainable Autonomous Driving. Rel. Carlo Masone, Ulises Cortés, Atia Cortés, Víctor Giménez �balos. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Roon Mullaaliu. Machine Learning Regression Model For Crowd-Monitoring Through WiFi Probe-Request Analysis. Rel. Claudio Ettore Casetti, Paolo Giaccone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Amirshayan Nasirimajd. Sequential Domain Generalisation for Egocentric Action Recognition. Rel. Giuseppe Bruno Averta, Chiara Plizzari, Simone Alberto Peirone, Marco Ciccone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Corrado Navilli. Multiparametric MRI and Deep Colorization: a Deep Learning framework for breast cancer pCR prediction. Rel. Lia Morra. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Alessandro Nicoli'. Non-Intrusive Load Disaggregation of Air Conditioning Systems. Rel. Edoardo Patti, Marco Castangia. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Shadi Nikneshan. AUTOMATED DATA ANALYSIS AND FUSION APPROACH FOR AUTONOMOUS VEHICLES IN MIXED URBAN TRAFFIC. Rel. Silvia Anna Chiusano, Brunella Roberta Daniela Caroleo, Andrea Avignone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Susanna Olivero. Surrogate Models for Parametric PDEs via Graph-Informed Neural Networks. Rel. Francesco Della Santa, Maria Strazzullo. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Michele Pacifico. Principles of Quantum Reinforcement Learning. Rel. Davide Girolami. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Dario Padovano. SpikExplorer: a tool for Design Space Exploration of Spiking Neural Network Architecture. Rel. Stefano Di Carlo, Alessandro Savino, Alessio Carpegna. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Francesco Pagano. Design and Analysis of Federated Learning Systems. Rel. Andrea Calimera, Valentino Peluso. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Alessio Paone. Addressing the Narrative Paradox: Leveraging Large Language Models to Enhance Users' Perception of Freedom in Interactive Narrative Systems. Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Emanuele Pinna. Applicazioni dell'Intelligenza Artificiale Generativa tramite Latent Diffusion per l'Explainability nella Geolocalizzazione = Applications of Generative AI via Latent Diffusion for Explainability in Geolocalization. Rel. Carlo Masone, Gabriele Moreno Berton, Barbara Caputo, Gabriele Trivigno. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Giovanni Poggio. Design and Development of a Multi-Agent System Environment to Monitor and Analyze Data Originating from Automated Test Equipment. Rel. Giovanni Squillero, Matteo Sonza Reorda. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Enrico Porcelli. Evaluation of the impact of the Multi-Head Attention algorithm in Music Source Separation. Rel. Eliana Pastor, Moreno La Quatra, Alkis Koudounas. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Oumaima Regragui. Auditing online software for bias: A controlled experiment in the domain of car insurance. Rel. Antonio Vetro', Riccardo Coppola. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Anam Ur Rehman. Artificial Intelligence based Information Provision in the Automotive Domain. Rel. Paolo Garza, Vincenzo Iaia. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Fabio Rizzi. Developing an Enterprise Chatbot using Machine Learning Models: A RAG and NLP based approach. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Micol Rosini. Unveiling Cognitive Decline and Sleep: Deep Learning for Alzheimer's Detection and Latent Representations' Exploration for Pattern-Specific Discovery. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Giacomo Rosso. Tecniche di Natural Language Processing per il monitoraggio di epidemie = Natural Language Processing techniques for epidemics monitoring. Rel. Giuseppe Rizzo, Sara De Luca. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Gaia Sabbatini. Advanced Data Management for Maintenance and Cost Optimization in the Heavy-Duty Mobility Sector. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Faezeh Saeedian. Design and Implementation of a Multilingual Conversational Chatbot for the HR Department. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Claudio Savelli. Bad Teaching in Machine Unlearning with Similarity-based Sampling. Rel. Flavio Giobergia, Elena Maria Baralis. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Luca Scalenghe. Vegetation index for crop monitoring from multi temporal SAR data. Rel. Maurizio Martina, Danilo Demarchi, Umberto Garlando, Luca Barco, Federico Oldani. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Luca Solaini. The value of collaborative logistics in the Electric Vehicle Routing Problem with Time Windows and Stochastic Waiting Times. Rel. Edoardo Fadda, Ornella Pisacane, Maurizio Bruglieri, Domenico Potena. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Marco Sorbi. Automated unit test creation based on Artificial Intelligence. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Gabriele Mario Antonio Spina. Automatic grouping of actions in user flow analytics. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Flavio Spuri. Optimizing Genome Representations for Cancer Type Classification. Rel. Alfredo Benso. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Sarina Takalloo. Water Stress Detection in Potato Crops Using Multispectral Imaging and Advanced Object Detection Models. Rel. Renato Ferrero, Nicola Dilillo. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Marco Tasca. Time-Robust and Energy-Efficient Decoder for Real-Time Neural Decoding of Primary Motor Cortex Activity. Rel. Stefano Di Carlo, Alessandro Savino, Alessio Carpegna, Paolo Viviani. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Fabio Tecco. Automatic detection of suspicious websites based on community detection algorithms in multi-graph context. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Chiara Van Der Putten. Transforming Data Flow: Generative AI in ETL Pipeline Automatization. Rel. Daniele Apiletti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Luca Viada. Machine and Deep Learning for Disease Mapping. Rel. Daniele Jahier Pagliari, Paola Berchialla. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

Luca Villani. Leveraging the Visual Capabilities of Transformers in Multimodal Machine Translation. Rel. Luca Cagliero, Lorenzo Vaiani. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Ali Yassine. Text-to-SQL for Fact Extraction and Verification Over Tabular Data. Rel. Luca Cagliero, Simone Papicchio. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024

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Luca Zilli. Development of a Deep Learning algorithm for biomedical image segmentation: study of metastatic Extracellular vesicles. Rel. Valentina Alice Cauda, Veronica Vighetto. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024