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Gráficos y Realidad Virtual

L'objectiu del projecte és afegir noves mètafores tant de manipulació com d'interació a la plataforma de visualització de models volumètrics en un entorn de realitat virtual.

Gráficos y Realidad Virtual Redes de Computadores y Sistemas Distribuidos Computación Avanzada Computación de Altas Prestaciones Ingeniería de Servicios Ciencia de los Datos

Machine Learning (ML) has taken the world by storm and has become a fundamental pillar of engineering. As a result, the last decade has witnessed an explosive growth in the use of deep neural networks (DNNs) in pursuit of exploiting the advantages of ML in virtually every aspect of our lives: computer vision, natural language processing, medicine or economics are just a few examples. However, NOT all DNNs fit to all problems: convolutional NNs are good for computer vision, recurrent NNs are good for temporal analysis, and so on. In this context, the main focus of N3Cat and BNN-UPC is to explore the possibilities of the new and less explored variant called Graph Neural Networks (GNNs), whose aim is to learn and model graph-structured data. This has huge implications in fields such as quantum chemistry, computer networks, or social networks among others. OBJECTIVES =========== N3Cat and BNN-UPC are looking for students wanting to work in the area of Graph Neural Networks studying their uses, processing architectures, and algorithms. To this end, the candidate will work on ONE of the following areas: - Investigating the state of the art on this area, surveying the different works done in terms of applications, processing frameworks, algorithms, benchmarks, datasets. This can be taken from a hardware or software perspective. - Helping to build a testbed formed by a cluster of GPUs that will be running pyTorch or Tensorflow. We will instrument the testbed to measure the computation workload and communication flows between GPUs. - Analyzing the communication workload of running a GNN either in the testbed or by means of architectural simulations. - Developing means of accelerating GNN processing in software (e.g., improving scheduling of the message passing) or hardware (e.g. designing a domain-specific architecture).

La principal problemática en Realidad Virtual es la imposibilidad de estudiar entornos de alta densidad de población, debido a la falta de realismo que existe entre la visualización y las sensaciones táctiles (empujones, presión). Es por ello que nos proponemos estudiar el uso del Joystick háptico para dirigir el movimiento de un avatar en un entorno con una gran densidad de agentes. Pretendemos evaluar si el uso de estos dispositivos permite aumentar el realismo y la inmersión, para avanzar en este tipo de estudios con escenarios que presenten una gran densidad de objetos dinámicos.

Gráficos y Realidad Virtual Redes de Computadores y Sistemas Distribuidos Computación Avanzada Computación de Altas Prestaciones Ingeniería de Servicios Ciencia de los Datos

Companies and scientists working in areas such as finance or genomics are generating enormously large datasets (in the order of petabytes) commonly referred as Big Data. How to efficiently and effectively process such large amounts of data is an open research problem. Since communication is involved in Big Data processing at many levels, at the NaNoNetworking Center in Catalunya (N3Cat) we are currently investigating the potential role of wireless communications in the Big Data scenario. The main focus of the project is to evaluate the impact of applying wireless communications and networking methods to processors and data centers oriented to the management of Big Data. OBJECTIVES =========== N3Cat is looking for students wanting to work in the area of wireless communications for Big Data. To this end, the candidate will work on one of the following areas: - Traffic analysis of Big Data frameworks and applications, as well as in smaller manycore systems. - Channel characterization in Big Data environments: indoor, within the racks of a data center, within the package of CPU, within a chip. - Design of wireless communication protocols for computing systems from the processor level to the data center level.

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

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.

Redes de Computadores y Sistemas Distribuidos

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

Quantum computing aims to provide significant speedup to many problems by taking advantage of quantum mechanical properties such as superposition and entanglement. Important applications such as Shor's integer factoring algorithm and Grover's unordered database search algorithm provide potentially exponential and quadratic speedups, respectively.

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

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.

Redes de Computadores y Sistemas Distribuidos

Deployment of distributed systems requires an Orchestrator to create pipelines, where a set of heterogeneous functions are connected. The project consists of implementing an Orchestrator and demonstrating the deployment and reconfiguration of pipelines on a 5G network scenario. The Orchestrator will run an optimization algorithm to assign the different functions into datacenters and then coordinate with the Virtual Infrastructure Orchestrator(VIO) and the Software Defined Networking(SDN) controller to create such functions.

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

Redes de Computadores y Sistemas Distribuidos Ciencia de los Datos

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.

Gráficos y Realidad Virtual

Reading charts in desktop and virtual reality environments can be difficult depending on the configuration of different parameters such as the width and height of different visual marks. The project aims to explore the perceptual limits of a set of well-known visualization techniques in desktop and VR-based environments.

Ciencia de los Datos

In recent years the volume of information available electronically has increased exponentially, coining the term Big Data to refer to this phenomenon. The medical domain is an area in which the number of documents generated by the centers for patient primary care constantly increases. However, a bottleneck is generated because processing these documents requires specialized personnel craftly performing tasks. In the framework of TAIDAMED research project, we are developing a set of processors that allow automatic analysis of medical texts taking into account criteria of robustness, high precision and coverage. In particular, this thesis would aim at the acquisition of patterns of clinical behavior from medical reports represented as semantic graphs using Neo4J database.

Redes de Computadores y Sistemas Distribuidos

Traditionally, Software Defined Networks (SDN) have been applied for configuring networks for which such configuration was intended to last for hours or even, days. However, the high dynamicity foreseen for 5G scenarios requires adapting SDN to be able to dynamically configure the network with much finer granularity (e.g. in the order of seconds) to adapt to high traffic variations. In this project, we will implement some components for such architecture and test them in an experimental platform.

Redes de Computadores y Sistemas Distribuidos Ciencia de los Datos

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.

Redes de Computadores y Sistemas Distribuidos

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

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.

Gráficos y Realidad Virtual

This master's thesis aims to analyze the feasibility of a remote VR system based on the use of mobile devices with cardboard glasses and low-cost interaction devices. It will start from a system based on HTC-VIVES programmed with Unity. Different portability alternatives to the new platform will be analyzed both in terms of the rendering of the models (locally or on a server) and the limitations of the interaction and connection between students and teacher. A prototype will be developed with basic interaction techniques and its usability will be analyzed.

Redes de Computadores y Sistemas Distribuidos Ciencia de los Datos

Fully funded intership with a top international research group at Telefonica Research (Barcelona) to develop a TFM on the application of deep learning to improve the management of a nation-wide 5G network.

Consulta ofertas de otros estudios y especialidades