Edinburgh Huawei Research Lab

This partnership will allow Huawei and the University of Edinburgh to jointly explore new theories and technologies in data management and provide direction for cutting-edge research into the next generation of information technology.

Building and Interrogating Knowledge Graphs from Text

Much of the promise of wide-coverage parsing for NLP applications such as interrogating knowledge graphs remains unfulfilled.

Deep Learning for Document Summarisation and Question Answering

Computers are excellent at working with crisp or tabular information, but the ambiguity that exists in human language makes it much harder for them to understand textual data and to interact in natural language.

Deep Learning in Dynamic, Constrained Systems

Modern machine learning methods are poorly targeted at many industry-relevant settings.

Deep Learning to Help People Understand Data and Understand Deep Networks

Large data sets are now generated by almost every activity in society, science, and commerce.

McDoC (Many-Core In-Memory Database on a Chip)

In this project we explore and quantify architectural design options for domain-specific single-chip many-core architecture, specifically tailored to support In-Memory Databases.

SplitChain: Scalable Blockchain using Shielded Execution

The goal of our project, SplitChain, is to build a scalable blockchain technology to support high performance transaction processing for millions of active users.

Techniques for Querying Big Data

The project aims to develop effective methods for querying big relations with constrained resources.

Game-theoretic Approaches to Data Privacy

The personal data of individuals is a key driver of the internet economy.

Towards Service Assurance in a Multi-Tenant 5G Mobile Network Architecture

Enabling diverse services with quality assurance is key to the success of 5G.