A

• Prima Acharjee. Development of an Automated System to Monitor Professional Mobility Using Web Scraping and Large Language Models = N/A. Rel. Daniele Apiletti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Fatemeh Ahmadpour. LLM-Driven Interface for Manufacturing Execution Systems. Rel. Giulia Bruno. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

B

• Davide Benotto. Automated Landslide Detection from InSAR Sentinel-1 Acquisitions using Advanced Deep Learning Architectures. Rel. Paolo Garza, Luca Barco, Lorenzo Innocenti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Bianca Bartoli. Deep Learning-Based Estimation of Regional Snow Water Equivalent and Snow Depth Variations from InSAR Sentinel-1 Observations. Rel. Paolo Garza, Luca Barco, Lorenzo Innocenti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Yegane Bagheri. Graph-Augmented Retrieval for Long-Form Video Question Answering. Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Samet Basaran. LLM-Based Hardware Design Generation: Disentangling Conceptual Timing and Implementation Failures. Rel. Daniele Jahier Pagliari. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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C

• Cagberk Cura. Automated Visual Inspection for the Fiat 500e Seat Assembly Line: A Deep Learning Case Study at Martur Srl Italy. Rel. Andrea Bottino, Mustafa Kayan. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Diletta Contarin. Automotive Diagnostics from Natural Speech: A Retrieval-Augmented Generation Approach. Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Andrea Cucchietti. Goal-Conditioned Reinforcement Learning for Autonomous Perceptive Earthworks in Particle-Based Soil Simulation. Rel. Raffaello Camoriano. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Andrea Cauda. Informational and operational support through proactive AI agents in real-time meetings. Rel. Alessandro Aliberti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Enrico Chen. Recursive Video Language Summarization Model: An Approach to Long Video Summarization. Rel. Luca Cagliero, Lorenzo Vaiani, Alessia Intini. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Lorenzo Calogiuri. A Unified Approach for Sexism and Misogyny Detection in Social Media Memes Under Hard and Soft Evaluation Settings. Rel. Luca Cagliero, Elöd Egyed-Zsigmond. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

D

• Christian D'Alleva. Multimodal Transformer for Spatio-Temporal Urban Air Quality Forecasting: An Ablation Study over Milan. Rel. Andrea Bottino, Luca Barco, Lorenzo Innocenti, Giacomo Blanco. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Ehsan Dashti. RGB-Based Crop Coverage Estimation under Side-View and Top-View Imaging Conditions Using Deep Learning. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Arash Daneshvar. Real-World Industrial Deployment of Vision–Based Robotic Manipulation in the Beverage Industry. Rel. Giuseppe Bruno Averta, Davide Buoso. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Rino Di Chiara. Subgraph-Based Training Augmentation for Graph Anomaly Detection with Very Few Labels. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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E

• Kevin Elezi. Learning to Rank in 2D : Differentiable Spatial Prioritization for Deforestation Forecast. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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F

• Elia Faure Rolland. Enabling Autonomous Agentic Client Participation in Federated Learning. Rel. Paolo Garza, Pietro Michiardi. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Federico Fili'. From Business Intelligence to Agentic AI Systems: Enterprise Integration and Strategic Value Creation in the Energy Industry. Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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G

• Alessio Giuffrida. Amadeus Revenue Management with Spiking Neural Networks. Rel. Paolo Garza, Pietro Michiardi. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Francesco Giannuzzo. Automatic Generation of Tool-Use Traces for Evaluating LLM Agents. Rel. Paolo Garza, Paolo Papotti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Matteo Giardino. DIVINE - Imaging DIagnosis of VIne diseases using NEural networks and deep learning. Rel. Andrea Bottino, Alessandro Emmanuel Pecora. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Francesco Giuseppe Gillio. Development of a Robotic Framework for the Simulation and Cooperative Navigation of Nano-Drone Swarms. Rel. Alessio Burrello, Daniele Jahier Pagliari, Giovanni Pollo, Beatrice Alessandra Motetti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Giovanni Grossi. Generative Models for Vehicle Trajectory Synthesis. Rel. Claudio Ettore Casetti, Giuseppe Perrone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Hamed Goldoust. Machine Learning per prevedere le prestazioni degli studenti. = Machine Learning for student performance prediction. Rel. Paolo Giaccone, Paolo Manfredi. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Ginevra Giulia Galeotti. The MultiMotion Project : A Multimodal Multivariate Fusion Framework for Continous Emotion Recognition. Rel. Gabriella Olmo, Vito De Feo. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Andrea Vasco Grieco. On the Role of Policy Variance in Proximal Policy Optimization for Continuous-Action Robot Control. Rel. Raffaello Camoriano, Daniele Pucci, Evelyn D'Elia, Edoardo Caldarelli, Lorenzo Rosasco. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Mohammadmahdi Gheisari Hassanabadi. One-Shot Learning algorithms in computer vision task on thermographic acquisition. Rel. Raffaella Sesana. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Sara Giorza. Zampa Ideale: a Web and Mobile Platform for Conscious Pet Adoptions. Rel. Alessandro Fiori. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026

H

• Mozhdeh Hajiani. Automated brain segmentation framework from 3D cranial ultrasound images of preterm newborns. Rel. Marco Agostino Deriu, Syed Taimoor Hussain Shah. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Sina Hamedani. FPSmart: Automated Function Point Analysis from Functional Analysis Documents Using Large Language Models. Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026

K

• Nithyakalyani Karthikeyan. Development of an Activity Index of Rodents in Preclinical Studies Using Low-Resolution Fish-Eye Video Data. Rel. Andrea Bottino, Marco Garzola. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Alexandre Korosi Casarin. Optimization of Employee Scheduling in a Dark Kitchen Company. Rel. Giovanni Zenezini. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Taha Kamalisadeghian. Real-Time Defect Identification in Welding Processes through Thermal and Audio Signal Analysis. Rel. Raffaella Sesana, Luca Santoro. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Reihaneh Kharazmi. Silent Speech. Rel. Alessio Burrello. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Reza Kharamani. Thermographic images post processing for welding process monitoring. Rel. Raffaella Sesana, Luca Santoro. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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L

• Mehrnoosh Liravi. Deep Learning for Electric Network Mapping Using Aerial Imagery. Rel. Paolo Garza, Daniele Rege Cambrin. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Francesco La Rota. Design and Deployment of a Multi-Agent Chatbot for Incident Management and System Monitoring. Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Aurora Leone. Design and Implementation of a Metadata-Driven Enterprise ETL Framework on Databricks. Rel. Daniele Apiletti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Zepeng Li. Incremental Learning for sEMG-Based Neuroprosthetic Control Using TCNformer Model. Rel. Alessio Burrello, Daniele Jahier Pagliari. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Nunzio Licalzi. Secure and Efficient Inference as a Service with Fully Homomorphic Encryption. Rel. Valentino Peluso, Daniele Jahier Pagliari, Andrea Calimera, Manuel Roveri, Alessandro Falcetta. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026

M

• Farzaneh Masteri Farahani. Anonymization of Sensitive Text Using LLM-based Models. Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Maham Maham. Bidirectional Text Style Transfer via Reinforcement Learning for Professional Social Media Communication. Rel. Riccardo Cantoro, Nicolo' Bellarmino. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Chiara Maretto. Cross-Dataset Classification of Postural Instability in Parkinson's Disease from a Single Wearable Sensor: A Machine Learning Approach. Rel. Luigi Borzi'. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Andrea Mengheres. Development and parameterization of a software system for the automatic management of curing presses based on production defects. Rel. Sara Vinco, Simone Lessone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Pouria Mohammadalipourahari. Domain Adaptation of Large Language Models for Financial Analysis: A Dual-Adapter Training and Merging Framework. Rel. Daniele Jahier Pagliari, Beatrice Alessandra Motetti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Tommaso Mazzarini. An End-to-End Pipeline for Extracting Circular Economy Indicators from Corporate Reports. Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Leonardo Merelli. An End-to-End Pipeline for Extracting Entities and Relations from Heterogeneous Documents. Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Leonardo Maggio. Enhancing Supply Chain Performance Through Integrated KPI Analytics: A Case Study on Weight Per Shipment. Rel. Daniele Apiletti. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Federica Mendoza. Exploiting skeleton-based Motion Encoder Networks to characterize Parkinsonian gait. Rel. Gabriella Olmo, Gianluca Amprimo. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Hojjat Miryavifard. Forgetting Topics from Multimodal News Summaries. Rel. Luca Cagliero, Giuseppe Gallipoli. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Amir Maleki. A Machine-Learning Pipeline for Ultrasonic A-Scan Quality Assessment and Thickness Estimation in Hydropower Penstocks. Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Mohammadreza Mashhadigholamali. Radar-Based Human Activity Recognition In An Indoor Environment. Rel. Luigi Borzi'. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Felipe Toshiyuki Miamoto. The Role of Large Language Models in Clinical Decision Support: A Systematic Literature Review and a Survey with Physicians. Rel. Marco Cantamessa. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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N

• Yasaman Noshirvanbaboli. Data-Driven Modeling of Multivariate Energy Signatures for Building Performance Analysis and Forecasting. Rel. Davide Papurello. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Van Thanh Nguyen. ESG Indicator Extraction and Green Bond Assessment from Non-Financial Disclosures. Rel. Luca Cagliero, Giuseppe Gallipoli. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Mehrbod Nowrouz. Multimodal Interpretation of Time-Series Discords: A Hybrid Approach using Matrix Profile and Visual Language Models. Rel. Luca Cagliero, Ali Yassine. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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O

• Ugur Baris Ozturk. Interpretable Machine Learning for Used Vehicle Pricing in the Turkish Automotive Market: Development and Deployment of an Explainable Boosting Machine. Rel. Paolo Chiabert. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Muhammed Emin Oral. A Knowledge Graph Approach to Critical Raw Materials Risk Monitoring: Developing a Strategic Digital Twin with Neo4j. Rel. Alessandro Savino, Nicolò Maunero, Andrea Bernardini, Francesco Giancaterini. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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P

• Riccardo Pisanu. Hateful Meme Detection via Large Language Models: A Comparative Analysis. Rel. Luca Cagliero, Lorenzo Vaiani. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Giovanni Pellegrino. Pruning-Aware Analysis of Accumulator Bit-Width in TFHE-Based CNN Inference. Rel. Valentino Peluso, Andrea Calimera. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Vito Perrucci. Real-Time 3D Reconstruction of Indoor Environments with NVIDIA NvBlox. Rel. Marina Indri, Gianluca Prato, Enrico Ferrera. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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Q

• Abdessamed Qchohi. On the Role of Uncertainty in In-Context Grokking: a Bayesian Approach. Rel. Paolo Garza, Simone Rossi. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

R

• Shakti Singh Rathore. Spiking Neural Networks in PPG-Based Blood Pressure Estimation. Rel. Alessio Burrello, Daniele Jahier Pagliari, Vittorio Fra. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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S

• Filippo Struffi. Data Guided Benchmarking of Optimization Strategies = -. Rel. Paolo Garza, Daniele Rege Cambrin. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Sahil Singh. Enhanced Time Series Analysis and Trading Strategy Development Using Dynamic Time Warping. Rel. Monica Visintin. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Mattia Sabato. Higher-Order Message Passing for Structured Video Understanding of Human Dynamics. Rel. Giuseppe Bruno Averta, Francesca Pistilli, Simone Alberto Peirone, Giulia Fracastoro. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  
• Cesar Augusto Seminario Yrigoyen. Investigating LIONESS-Derived Gene Regulatory Networks and Advanced Graph Neural Networks for Leukemia Subtype Classification and Cross-Cancer Disease Association Analysis. Rel. Roberta Bardini, Stefano Di Carlo, Alessandro Savino. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Giovanni Stina'. Popularity Dynamics on Bluesky: A Large-Scale Stochastic Analysis of High-Volatility Environments. Rel. Emilio Leonardi, Franco Galante. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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T

• Lorenzo Tozzi. Dynamic Tiling for Reinforcement Learning. Rel. Giuseppe Bruno Averta. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
• Parsa Taati. Machine Learning per predire la produzione di energia = Machine Learning to Predict Energy Production. Rel. Michela Meo, Greta Vallero. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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• Matteo Tomatis. A Modular Vision Pipeline for Motion Detection and Object Segmentation in Industrial Systems. Rel. Valentino Peluso, Andrea Calimera, Enrico Macii. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026

V

• Alessandro Valenti. Active Inference for Autonomous Exploration on Nano-drones. Rel. Daniele Jahier Pagliari, Alessio Burrello, Beatrice Alessandra Motetti, Matteo Risso, Carlo Marra. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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Y

• Farhad Yousefi Razin. Variational Autoencoders for Multi-Omic Transcriptomic and Epigenomic Data. Rel. Roberta Bardini, Stefano Di Carlo, Alessandro Savino, Lorenzo Martini. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2026
  

  

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