This project studies how live streaming commerce, a fast-growing way of selling products through real-time online video is changing supply chain management. Unlike traditional e-commerce, live streaming creates sudden spikes in customer demand that existing supply chains often struggle to handle efficiently. The research aims to understand how these new sales models affect inventory management, […]

Ce projet de recherche vise à améliorer une technique de fabrication miniature appelée « gravure chimique assistée par décharges » pour sculpter le verre de façon très précise. Pendant son stage à l’ÉTS, Augustin Mazet utilisera des équipements de pointe pour tester de nouvelles méthodes de fabrication de composants en verre de quartz extrêmement fins. […]

In this project, students are expected to set up a testbed and run experiments to evaluate the impact of integrating post quantum cryptography (PQC) into IoT devices. The evaluation metrics include CPU usage, memory usage, bandwidth usage, and energy usage. Various PQC mechanisms will be evaluated on MQTT over TCP+TLS, including ML-KEM, HQC, ML-DSA, and […]

In this project, we will design and develop an IoT device auto-detection model and deploy it on a Raspberry Pi. The model will follow a continuous machine-learning approach and will be trained using an IoT dataset developed in our lab. The Raspberry Pi will function as a Wi-Fi router, allowing IoT devices to connect to […]

This project aims to develop an optimal Agentic AI Framework for next-generation intelligent mobility systems. Rather than focusing on a single algorithm or application, the research seeks to establish a generalizable architecture that integrates advanced optimization methods with graph-based large language model orchestration. Demand-Responsive Transit (DRT) serves as the primary testbed due to its inherent […]

This project will develop and pilot-test a dual-function Generative AI chatbot to support student learning in an undergraduate course. The system will integrate: (1) a definition-retrieval component that provides course-aligned explanations drawn from the textbook, lecture slides, and instructor-approved materials, and (2) an assessment component that evaluates students’ written explanations of key concepts by comparing […]

Accurately assessing and managing pain in dogs is one of the most challenging aspects of veterinary medicine because animals cannot verbally communicate their discomfort. Current methods rely heavily on behavioral observations and standardized scoring tools, which are often subjective and prone to inconsistencies. This project aims to address these limitations by developing an AI-powered predictive […]

This project focuses on using deep learning techniques and AI for medical image processing, optimizing these techniques to maximize efficiency and accuracy in processing large sets medical data. This project specifically aims to improve generalization and explainability of deep learning models used in medical imaging, focusing on medical image segmentation to explore how current medical […]

This project aims to improve how polymer-based solvents are modeled during freezing and solidification processes that are critical to modern semiconductor manufacturing. Building on prior experimental and theoretical studies (i.e., the collaborative work from participated institutions), the project will develop an accurate and reliable computational framework that captures how heat transfer and mechanical stresses interact […]

This project is an research internship with SOKENDAI in Japan with the goal of gaining hands-on experience with advanced mass spectrometry techniques used in nuclear and atomic physics. During the internship, the intern will work alongside researchers at SOKENDAI to learn how Multi-Reflection Time-of-Flight Mass Spectrometry systems are operated, optimized, and used in active experiments. […]

Software developers and companies are increasingly adopting agentic AI to implement software features. In practice, developers guide AI agents through explicit instructions that specify, for example, how to navigate the project, identify relevant source files, and test the generated code. Without such instructions, agents may blindly perform implementations leading to incomplete or incorrect results. While […]

The proposed project aims to develop and validate a computational method for estimating how brain tissue moves and reacts to surgical tools using only videos captured from a microscope. The student will test both classical and modern deep-learning optical-flow algorithms, adapt them to the specific challenges of microscope imaging, and evaluate how well they can […]