Development of an NLP Sales Assistant using Machine Learning Techniques

The main goal of this project is to develop machine learning and natural language processing approaches to help customers to communicate their preferred brands and/or retailers via Heyday solutions. These approaches will automate answers and help to humanely engage with customers. In order to reach these objectives, some challenges will be tackled such as automatically […]

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Bond Pricing AI Improvement

The fixed-income market consists of government and corporate bonds and other debt instruments which are used to finance operations and capital investments. The bond market remains heavily reliant on exchanges of information between counterparties and as a result information on prices is decentralized and market participants operate with different levels of information. The objective of […]

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Design and development of techniques to characterize optical, mechanical and chemical properties of metallic and semiconductor thin films with applications in MEMS structures and their packaging

Micro-Electro-Mechanical Systems (MEMS) are complex systems with sizes in the range of few microns (human hair has thickness of 150-200 microns) which have both mechanical and electronic components. MEMS technology has entered in many industries such as optical technology, point of care diagnostics, telecommunications, automotive, and military. Today, there are hundreds of MEMS devices, e.g. […]

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Intelligent Cyber-Physical Situational Awareness for Smart Infrastructures

The availability of big data in smart infrastructures have become a strategical asset for operators to understand the situation of the infrastructure and monitor potential threats. However, most of the data still have not circulated beyond traditional corporation and technological boundaries, which have limited the visibility that could have been provided by the abundant data. […]

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Self-Adaptive Penetration Tests with Deep-Reinforced Intelligent Agents

Penetration testing is a key security tactic, where defenders thinks like an attacker to predict the latter’s actions and develop effective defense. However, for large-scale cyber-physical infrastructures like the smart grid, traditional penetration tests on individual devices or networks are insufficient to exhaust all potential exploits or to reveal infrastructure-level vulnerabilities invisible to the local […]

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Data driven energy efficient base station sleep control for 5G systems

The objective of this project is to develop a software system which can optimally control the base station sleep states in 5G networks to save energy. The 5G wireless networks are required to be green and yield very low carbon dioxide emissions. Compared with that of 4G wireless networks, the power efficiency of 5G is […]

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Transparent and Trustworthy Deep Feature Learning for Cyber-Physical System Security

The latest artificial intelligence (AI) technologies have effectively leveraged the wealth of data from cyber-physical systems (CPSs) to automate intelligent decisions. However, for safety-critical CPS like smart grids and smart cities, the conversion of massive data into actionable information by the AI must be not only effective but also reliable. To this end, this project […]

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Machine Learning and Data Mining Approaches for Smart Buildings

The goal of this project is to develop machine learning and data mining algorithms relying on non-intrusive common sensor data to estimate and predict smart buildings’ occupancy and activities. Efficient feedbacks are automatically supplied to the end user to involve occupants and increase their awareness about energy systems. This consists of generating reports helping the […]

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Complementary and competitive interactions between wild and managed bees

A diversity of native bee species inhabit agricultural and urban landscapes and can be more effective pollinators than the widely employed European honey bee. However, honey and wild bee communities often overlap, which means these bees compete for the same floral resources. Studies of competition between wild and managed pollinators are limited due to methodological […]

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Complementary and competitive interactions between wild and managed bees – Year two

A diversity of native bee species inhabit agricultural and urban landscapes and can be more effective pollinators than the widely employed European honey bee. However, honey and wild bee communities often overlap, which means these bees compete for the same floral resources. Studies of competition between wild and managed pollinators are limited due to methodological […]

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Simeio: Anomaly Detection for Building Automation System

Buildings are an important energy consumer and are equipped with hundreds of sensors and control systems. The analysis of such massive data can reveal insights for building owners to optimize the building infrastructure. Currently, usage of such data is limited to traditional control systems, energy commissioning, and maintenance on a regular basis. Real-time monitoring and […]

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Simeio: Anomaly Detection for Building Automation System – Year two

Buildings are an important energy consumer and are equipped with hundreds of sensors and control systems. The analysis of such massive data can reveal insights for building owners to optimize the building infrastructure. Currently, usage of such data is limited to traditional control systems, energy commissioning, and maintenance on a regular basis. Real-time monitoring and […]

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