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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.

Gráficos y Realidad 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

Computación de Altas Prestaciones

This is an offer for a PhD Dissertation, which can be initiated as a MS Thesis. We are working to design a domain-specific accelerator, in the context of high-performance computing, for homomorphically-encrypted deep learning inference. Previous cryptography experience is not required, since there will be an expert in the team advising on those matters. The successful candidate will be integrated into an international team of 9 members working toward this purpose on different topics.

Redes de Computadores y Sistemas Distribuidos Computación Avanzada

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

Gráficos y Realidad 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.

Redes de Computadores y Sistemas Distribuidos

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.

Computación de Altas Prestaciones

This is an offer for a PhD Dissertation, which can be initiated as a MS Thesis. We are working to accelerate homomorphically-encrypted deep learning inference via different efforts, in this case FPGA accelerators. Previous cryptography experience is not required, since there will be an expert in the team advising on those matters. The successful candidate will be integrated into an international team of 9 members working toward this purpose on different topics.

Computación de Altas Prestaciones

This is an offer for a PhD Dissertation, which can be initiated as a MS Thesis. We are working to accelerate homomorphically-encrypted deep learning inference via different efforts, in this case GPU accelerators. Previous cryptography experience is not required, since there will be an expert in the team advising on those matters. The successful candidate will be integrated into an international team of 9 members working toward this purpose on different topics.

Redes de Computadores y Sistemas Distribuidos Computación Avanzada

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.

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.

Redes de Computadores y Sistemas Distribuidos

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.

Redes de Computadores y Sistemas Distribuidos Computación Avanzada Computación de Altas Prestaciones Ciencia de los Datos

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.

Redes de Computadores y Sistemas Distribuidos Computación Avanzada Computación de Altas Prestaciones Ciencia de los Datos

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.

Redes de Computadores y Sistemas Distribuidos Computación Avanzada Computación de Altas Prestaciones Ciencia de los Datos

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.

Redes de Computadores y Sistemas Distribuidos Computación Avanzada Ciencia de los Datos

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.

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

Computación Avanzada Computación de Altas Prestaciones

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.

Redes de Computadores y Sistemas Distribuidos Computación Avanzada

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.

Gráficos y Realidad Virtual

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

Redes de Computadores y Sistemas Distribuidos

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.

Gráficos y Realidad Virtual

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

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