The project has the following objectives: Improving and Adapting VR/AR applications for Medical Imaging and Health Applications Perform user tests with students, clinicians, and radiologists in the context of the XAVIER project Help with Data analysis and validation of the applications to support the publication of results

Develop an edge controller allowing the management of electric vehicles, PV generation and house appliances. Test the edge device in laboratorial facilities. Support the development of the demonstrator. Assist the research team in the production of reports and research papers.

Te@ch4SocialGood aims to develop, pilot test, and study the efficacity of a teacher training program to promote both engagement as well as competence on the subject of cyberbullying. The grant holder will work on the content management platform supporting the learning process, as well as its integration with the serious game supporting the intervention and the social agent guiding the participants throughout the whole process. This includes extending, deploying, documenting, testing and disseminating the existing online platform and further developing and managing the learner profile supporting the intelligent decision-making of the tutoring system.

Study, development, and implementation of Visual-Inertial Simultaneous Localization and Mapping (VI-SLAM) methods targeting their deployment in FPGA-based accelerator for 3D mapping of underwater caves, under development in the scope of the 3D-CAVE project.

The objective of this summer internship is to create generative agents to be able to perform actions in hybrid societies with agents and humans. Inspired by the article "Generative agents: Interactive simulacra of human behavior” (see https://arxiv.org/abs/2304.03442) is intended to explore how LLMs (in particular ChatGPT) can help generate behaviors in scenarios of social dilemmas with humans and agents. It is intended to compare different models of agents, and explore the trust placed by humans in them (as far as they are trustworthy) as well as different degrees of delegation.

The goal of this project is to contribute to the development of advanced security and privacy-preserving technologies for smart-retail stores. Specifically, this project aims to design and implement a security infrastructure for protecting the confidentiality of sensor data and proprietary data processing algorithms using trusted execution environments based on enclave computing techniques. By leveraging trusted hardware such as Intel SGX, trusted pieces of software will be able to run in isolation (inside enclaves), thereby ensuring that privacy-sensitive data cannot be extracted and algorithms cannot be reverse-engineered in run-time even if the local operating system is compromised. To develop this project, three main tasks will be pursued: 1) study the hardware features of server platforms to better understand the security and performance trade-offs provided by the underlying enclave technology, 2) develop a software prototype that leverages enclave technology to provide end-to-end confidential computing, and 3) study the evolution of this system to incorporate fault tolerance mechanisms. The expected outcome of this project includes both a report of the analysed solutions and a software prototype of the implemented solution.

The objective and workplan consist of developing scalable and performant solutions for achieving causal consistency in clusters with multiple distributed systems. This will entail the development of new consistency protocols, their practical deployment according to state of the art cluster management tools, an experimental evaluation of the solution and writing research papers on this topic.

The workplan consists in the adaptation/partial redesign of electronic boards for testing of cables and electronic boards prototypes of the Tilecal High Voltage system (up to 1 kV). The candidate will test prototypes and will adapt the design of the testing boards to allow them to be assembled with components currently available in the market, working also in the development of the associated software. The testing boards are intended to be used in the calibration and monitoring of other boards of the high voltage system of the Tilecal calorimeter of the Atlas detector and of the respective high voltage cables after insertion of the connectors.

Several formal models for evaluating non-discrimination in machine learning algorithms resort to formulations using propositional logic. The formulations that result from these models have been getting bigger and bigger, so finding optimal solutions for these formulations is increasingly difficult. The alternative is to find solutions as close as possible to the optimal value. This scholarship intends to develop new approximation algorithms for the MaxSAT problem. New ways of partitioning soft clauses in MaxSAT will be developed. After obtaining the partitions, we will use multi-objective optimization algorithms to optimize each of the partitions and obtain a better approximation to the MaxSAT problem.