Ofertes de projectes

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To date, traditional Deep Learning (DL) solutions (e.g. Feed-forward Neural Networks, Convolutional Neural Networks) have had a major impact in numerous fields, such as Speak Recognition (e.g., Siri, Alexa), Autonomous driving, Computer Vision,etc. It was just recently, however, that a new DL technique called Graph Neural Network (GNN) was introduced, proving to be unprecedentedly accurate to solve problems that are formalized as graphs.

Gràfics i Realitat Virtual

Navigation meshes are necessary to represent the walkable space of an environment so that agents can perform pathfinding and move through them. Current navigation meshes tend to flatten the environmetn to represent it as 2D polygons connected by edges (square cells, triangles or larger convex polygons). This abstraction presents problems when dealing with complex outdor geometry where the terrain may not be completely flat. With this project, we would develop a novel navigation mesh that can keep the complexity of any 3D input geometry, while still generating small graphs

Xarxes de Computadors i Sistemes Distribuïts Computació Avançada

In this project, we wish to create a summarized universal representation of packet flows within a computer network. We approach this problem as an Unsupervised Learning problem, where the summarized representation must be as small as possible while minimizing the reconstruction error. In order to build this representation, multiple approaches are to be considered. This includes using traditional techniques such as a Fourier Transformation, and using representations learned Machine Learning models, specifically Autoencoders and sequence models like 1-dimensional CNNs, RNNs

Gràfics i Realitat Virtual

Dimensionality reduction algorithms transform high-dimensional data to lower dimensions, usually 2D or 3D. Analyzing the results of such algorithms typically is carried out using 2D plots and measures. The goal of the project is the creation of an application that facilitates the visual comparison and exploration of those spaces.

Xarxes de Computadors i Sistemes Distribuïts

UPC and Nestlé are offering a new position to develop the TFM in the field of Machine Learning and Cybersecurity. This TFM will be fully funded (internship) and carried out in collaboration with the Global Security Operations Center of Nestlé and UPC.

Xarxes de Computadors i Sistemes Distribuïts Computació Avançada

Recent advances in the field of Reinforcement Learning (DRL) are rising a lot of attention due to its potential for automatic control and automatization. Breakthroughs from academia and the industry (e.g, Stanford, DeepMind and OpenAI) are demonstrating that DRL is an effective technique to face complex optimization problems with many dimensions and non-linearities. However, to train a DRL agent in large optimization scenarios still remains a challenge due to the computational intensive operations during backpropagation.

Computació Avançada Ciència de les Dades

This project is a continuation of three previous master theses that have provided key knowledge to be utilized by several sailing teams during the upcoming Paris 2024 Olympic Games. TriM s.r.l., the leading company for the Paris 2024 weather project, has been collecting a significant amount of sea data since 2021 through real-time sensors during training and racing sessions. This data is stored in a cloud database. Sailing strategy and performance are closely linked to environmental parameters such as weather conditions, oceanic currents, and geographical data.

S'ofereix una beca d'iniciació a la recerca de 20 hores/setmana amb un salari aprox. de 600 Euros/mes per realitzar el TFM en el marc del projecte Eprivo.eu.

Xarxes de Computadors i Sistemes Distribuïts

The work to do includes: - Analysis of existing specifications for health/genomics consent (FHIR, GA4GH, ...) - Analysis of GA4GH's DUO and other related ontologies for access control - Analysis of how ODRL and other related rights management languages could be used for consents management - Investigate how XACML could be used to manage health/genomics consent information. Existing technologies will be investigated (many of them under development) to provide added value on analysis and proposals for use, standardization and iteroperability approaches.

Xarxes de Computadors i Sistemes Distribuïts Computació Avançada Computació d'Altes Prestacions Ciència de les Dades

Quantum computers promise exponential improvements over conventional ones due to the extraordinary properties of qubits. However, quantum computing faces many challenges relative to the scaling of the algorithms and of the computers that run them. This thesis delves into these challenges and proposes solutions to create scalable quantum computing systems.

Xarxes de Computadors i Sistemes Distribuïts Computació Avançada Computació d'Altes Prestacions Ciència de les Dades

Computing systems are ubiquitous in our daily life, to the point that progress is intimately tied to the improvements brought by new generations of the processors that lie at the heart of these systems. A common trait of current computing systems is that their internal data communication has become a fundamental bottleneck and traditional interconnects are just not good enough. This thesis aims to study how we can speed up architectures with CPUs, GPUs, and ML accelerators thanks to unconventional (e.g. wireless) interconnects.

Xarxes de Computadors i Sistemes Distribuïts Computació Avançada Computació d'Altes Prestacions Ciència de les Dades

This thesis aims to explore the possibilities of the new and less studied variant of neural networks called Graph Neural Networks (GNNs). While convolutional networks are good for computer vision or recurrent networks are good for temporal analysis, GNNs are able to learn and model graph-structured relational data, with huge implications in fields such as quantum chemistry, computer networks, or social networks among others.

Xarxes de Computadors i Sistemes Distribuïts Computació Avançada Ciència de les Dades

Recent advancements in nanotechnology have enabled the concept of the "Human Intranet", where devices inside and on our body can sense and communicate, opening the door to multiple exciting applications in the healthcare domain. This thesis aims to delve into the computing, communication, and localization aspects of the "Human Intranet" and how to practically realize them in the next decade.

Computació Avançada Ciència de les Dades

We offer TFM positions at the Barcelona Supercomputing Center (BSC) in a join collaboration between BSC and UPC, in the context of the EU project SAFEXPLAIN (https://safexplain.eu/). The goal of the TFM is assessing existing solutions to measure whether training and validation data used for DL models provide sufficient coverage against relevant or expert-designed features (e.g., object characteristics, weather conditions) in the context of autonomous driving.

The syntactic structure of a sentence can be represented as a tree where vertices are words and arcs indicate syntactic dependencies between words. Syntactic dependency parsing is the branch of computational linguistic concerned with the extraction of syntactic dependency structures from raw text. This research proposal is focused on unsupervised syntactic dependency parsing, i.e. methods to extract syntactic dependency structures from unlabelled data. This projects consists of implementing simple unsupervised parsers and evaluating them on human languages and other species

Gràfics i Realitat Virtual

In this project, we aim to extend the current motion-matching algorithm to handle features extracted from a virtual crowd such as density, average and relative velocity, and potential colliders. We would also need to further extend the motion capture data base to have animations that can much such scenarios.

Computació Avançada Ciència de les Dades

This project is a continuation of three previous master theses that have provided key knowledge to be utilized by several sailing teams during the upcoming Paris 2024 Olympic Games. TriM s.r.l., the leading company for the Paris 2024 weather project, has been collecting a significant amount of sea data since 2021 through real-time sensors during training and racing sessions. This data is stored in a cloud database. Sailing strategy and performance are closely linked to environmental parameters such as weather conditions, oceanic currents, and geographical data.

Computació Avançada Computació d'Altes Prestacions

This master thesis project aims to elevate the capabilities of PETGEM, a cutting-edge open-source 3D electromagnetic modeler written primarily in Python. Conducted in collaboration with the Wave Phenomena Group of the Barcelona Supercomputing Center, the Programming Models Group of the Universitat Politecnica de Catalunya, and the Argonne National Laboratory and University of Chicago, this research adds a substantial real-world context to the development.

Xarxes de Computadors i Sistemes Distribuïts Computació Avançada

This project will be done in collaboration with Telefonica Research. Telefonica Research is a diverse, multidisciplinary and international group of scientists who dare to push the frontiers of knowledge and prepare for the upcoming challenges on communications and the Internet.

Gràfics i Realitat Virtual

The goal of the project is to create an immersive analytics module to explore the results of training experiences.

Xarxes de Computadors i Sistemes Distribuïts

The DMAG (Distributed Multimedia Applications Group) of the IMP (Information Modeling and Processing) research group of the UPC has developed Reference Software (validated as an ISO International Standard) for JPEG Systems, a set of standard applications to provide extra facilities to JPEG images. This work intends to develop software applications on top of that Reference Software to demonstrate its use. Examples include protection of regions of images using JPEG Systems Privacy and Security standard or use of JPEG Snack standard with audio, images, etc.

Gràfics i Realitat Virtual

The goal of the project is to create an application that facilitates the segmentation of medical models using immersive techniques.

Consulta ofertes d'altres estudis i especialitats