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List of results

• Anomaly ranking of District Heating Substations  + (Implementing anomaly ranking algorithm to monitor district heating substations.)
• OpticalFlowForHMI/  + (Implent a high speed, low latency motion estimation technique)
• Improving MEDication Adherence through Person Centered Care and Adaptive Interventions  + (Improving MEDication Adherence through Person Centered Care and Adaptive Interventions)
• Improving MEDication Adherence through Person Centered Care and Adaptive Interventions iMedA  + (Improving MEDication Adherence through Person Centered Care and Adaptive Interventions iMedA)
• Intrusion detection and prevention for IIoT using Ensemble Deep Network  + (In this project students will work on network data and try to detect malicious behavior using ensemble deep network.)
• Optimisation in Heavy Duty Vehicles Configuration  + (In this project we aim to optimise the vehicles setting based on their usage style. Here we focus more on fuel consumption.)
• Anomaly Detection of the Activities of the Elderly Living in the Smart Home  + (In this project we detect the anomaly of the actives of the elderly people or those with some sorts of health problem.)
• Optimisation Algorithm for Feature enginnering  + (In this project we intend to design an optimisation system using artificial intelligence algorithms in order to select/extract the best features for developing a forecasting system in predictive maintenance.)
• Self-adaptive Recommender System In Conditional Context  + (In this project we intend to develop an adaptive system that can adapt itself --based on different context-- at providing service to conditional preference of users which change over time.)
• Reinforcement learning in Automation  + (In this project we plan to use reinforcement learning in multi-agent systems to improve decision making. in automated systems.)
• Name of the new projectEstimating agricultural development indicators over large areas from satellite images – an approach using convolutional neural networks and transfer learning  + (In this project you will use deep learning models, specifically convolutional neural networks (CNN), to analyze satellite imagery to estimate agricultural development indicators.)
• Multiband RF Rectifier for Self-Powered IoT Devices  + (In this project, Mutiband RF rectifiers will be designed for self-powered IoT devices)
• Reconfigurable Orbital angular momentum (OAM) antenna for High-Speed Wireless Communications  + (In this project, a reconfigurable (operating modes will be controlled using p-i-n diodes) OAM antenna will be designed.)
• Wideband Dielectric Resonator Antenna Array for Autonomous Vehicles  + (In this project, a wideband millimeter-wave dielectric resonator antenna will be designed to ensure high gain and channel capacity.)
• Ultra-wideBand Antenna Array for Vehicular Communication  + (In this project, an ultra-wideband millimeter-wave antenna array will be designed to ensure high gain and channel capacity.)
• Deep clustering for vehicle operation type  + (In this project, deep clustering will be used on the logged vehicle data (LVD) to find the best representation of vehicles’ operation to explain the behavior of the vehicles over time.)
• Automatic Generation of Realtime Machine Learning Architectures  + (In this project, it is required to build a tool to generate a dataflow model and construct architectures for such algorithms, while minimizing latency or meeting a specific deadline under area and power constraints.)
• LiDAR Denoising  + (In this project, the candidate is supposed to implement various filtering algorithm to denoise 3D LiDAR point cloud data.)
• Deep Graph Networks for Future Graph Prediction  + (In this project, the candidate is supposed to implement a deep graph network that receives a set of graphs as input and returns the predicted next upcoming graph(s).)
• Hardware Security Enhancement in Cyber-Physical Systems using Deep Learning-based Anomaly Detection  + (In this project, we intend to employ a deep learning approach to detect anomalies in cyber-physical systems using data flow monitoring.)
• Effecient implementation of DL models on embedded platforms  + (In this project, we optimize DL models to run efficiently on resource-bounded embedded platforms.)
• A Reliable IoT Messaging Protocol Based on MQTT Standard  + (In this project, we will modify the well-known IoT protocol, i.e., MQTT to consider a topic-based reliability strategy between the broker and subscribers.)
• Incorporate behaviour modelling into AGV safety performance stack  + (Incorporate behaviour modelling into AGV safety performance stack)
• Increase Data Rate over Error-prone networks  + (Increase Data Rate over Error-prone networks (AIRBUS))
• HUMAI - Test and Demonstration of HUMan-centered AI  + (Increased engagement of industral operators through human-centered AI; the project is done in collaboration with local rubber factory)

• Indoor localization for ground vehicles  + (Indoor localization for ground vehicles)

• Simulating Crowds for Traffic Safety Research  + (Integrate crowd simulation into a mixed-reality platform for development and testing of advanced automotive safety systems.)
• Integrating a new rigid-body dynamics model library with an existing whole-body controller  + (Integrating a new rigid-body dynamics model library with an existing whole-body controller)
• Intelligent claim Process with Volvia  + (Intelligent claim Process)
• Human-in-the-loop Discovery of Interpretable Concepts in Deep Learning Models  + (Interactive discovery of disentangled and interpretable concepts in Deep Learning Models)
• Knowledge graphs in healthcare  + (Investigae the use of KG in healthcare applications)
• Federatad Learning (FL) improving security and privacy in tactical networks  + (Investigate and prototype how FL can improve security and privacy in tactical networks, with a focus on intrusion detection or anomaly detection. The project will combine a literature review with a simulation-based implementation to assess feasibility.)
• Driver Prediction for Automative Industry  + (Investigate if and how it is possible to predict the drivers actions and inentions in a predefined limited number of scenarios)
• Investigating depression signs among older adults using Swedish National Registry Data  + (Investigating depression signs among older adults using Swedish National Registry Data)
• Fuzz testing of network protocols  + (Investigation how fuzz testing of network protocols could be implemented and provide rapid robustness testing)
• Federated Learning Aggregation Strategies by Weight Exploration  + (Investigation of aggregation strategies for federated learning)
• The effect of a mixed-capability vehicular fleet on Vulnerable Road User safety  + (Investigation of the effect of different levels of connection, cooperation, and automation (e.g., local awareness, collective perception, statistics) on road safety and traffic efficiency for future mobility scenarios including pedestrians and cyclists.)
• Comparative Study on Data Abstraction Methodologies for Interoperable V2X Roadside Units (RSU)  + (It is a collaboration with MittLogik on development of Interoperable RSU Prototype focused on Vulnerable Road User (VRU) safety.)
• Value of BIG DATA for Large Building Owners  + (It is an explanatory project with a company called Mutual Benefits Engineering AB)
• Thesis in connection with KEEPER project  + (KEEPER – knowledge creation for efficient and predictable industrial operations)
• Knowledge graphs 4 XAI in Healthcare  + (Knowledge graphs in Healthcare)
• Collaboration with Bankomat 3  + (LLM Feedback Loops for Autonomous Knowledge Updating RQ: What mechanisms allow LLMs to autonomously refine their knowledge based on user feedback?)
• MMultitask Learning on Vehicle Data  + (Learning shared representation using multitask learning on a vehicle-related data)
• Multitask learning on vehicle data  + (Learning shared representation using multitask learning on a vehicle-related data)
• Building a Knowledge-based AI Framework for Mobility  + (Leveraging new knowledge to improve the productivity of mobility services)
• Protein Language Models for drug discovery  + (Leveraging the sequence-based transformer protein language model for improving potential drug targets identification)
• Lighting up the bicycle roads with drones  + (Lighting up the bicycle roads with drones)
• Lightweight foundation model for time series classification  + (Lightweight foundation model for time series classification)
• Adapt LoCoMotif to forklift data  + (LoCoMotif is a novel TSMD method able to discover motifs that have different lengths (variable-length motifs), exhibit slight temporal differences (time-warped motifs), and span multiple dimensions (multivariate motifs))
• Predicting electricity generation capacity in solar and wind power plants based on meteorological data using machine learning algorithms  + (ML algorithms will be used to analyze meteorological data to predict the electricity generation capacity of solar and wind power plants. This project is a collaboration between Halmstad and Sam Houston University (USA)).)
• Machine Learning and LeadTime Prediction  + (Machine Learning and LeadTime Prediction)