Semantic search
From ISLAB/CAISR
| Supervisors | OneLineSummary | Status | |
|---|---|---|---|
| Fault detection using acoustic signals through anomaly detection | Elena Haller Peyman Mashhadi |
Fault detection using acoustic signals through anomaly detection | Open |
| Federated Learning Aggregation Strategies by Weight Exploration | Jens Lundström Amira Soliman Sadi Alawadi |
Investigation of aggregation strategies for federated learning | Open |
| Federated learning in automotive industry | Zahra Taghiyarrenani Sławomir Nowaczyk Sepideh Pashami |
Federated learning in automotive industry | Open |
| Forecasting Industrial IoT Time Series @AlfaLaval | Hadi Fanaee | Forecasting industrial IoT Time Series | Open |
| Foundation Models for Time Series Analysis | Zahra Taghiyarrenani Yuantao Fan Ali amirahmadi |
Explore the use of large pre-trained time-series foundation models (TSFM) and design fine-tuning strategies on tasks of interest | Open |
| Generating synthetic time series data in case of data scarcity | Alexander Galozy Peyman Mashhadi |
Generating synthetic time series data in case of data scarcity | Open |
| Generative Approach for Multivariate Signals | Kunru Chen Thorsteinn Rögnvaldsson Abdallah Alabdallah |
The topic focuses on generative models (VAE) for CAN-bus data and investigating the representation learning capabilities of such techniques | Open |
| Graph Neural Networks for Multivariate Time Series Data Analysis | Prayag Tiwari Guojun Liang |
Our project aims to analyze multivariate time series through the innovative application of graph neural networks. | Open |
| Graph Neural Networks for Traffic Flow Forecasting | Prayag Tiwari Sławomir Nowaczyk |
The main goal of this project is to explore GNN for traffic flow forecasting | Open |
| Graph Neural Networks for cardiovascular disease | Prayag Tiwari | The main goal of this project is to explore GNN for cardiovascular disease | Open |
| Hardware Security Enhancement in Cyber-Physical Systems using Deep Learning-based Anomaly Detection | Mahdi Fazeli | In this project, we intend to employ a deep learning approach to detect anomalies in cyber-physical systems using data flow monitoring. | Open |
| Human ground robot interaction | Cristofer Englund Martin Cooney Fernando Alonso-Fernandez |
External communication from mobile robots to minimize conflicts with pedestrians | Open |
| Human-in-the-loop Discovery of Interpretable Concepts in Deep Learning Models | Ece Calikus | Interactive discovery of disentangled and interpretable concepts in Deep Learning Models | Open |
| Hydro Power Station | TBD (contact Slawomir Nowaczyk if interested) | Collaboration with Ålberga Bruk 1919 | Open |
| Ideology and Power Identification in Parliamentary Debates | Pablo Picazo-Sanchez | Ideology and Power Identification in Parliamentary Debates | Open |
| Improving Time-series Generative Adversarial Networks (GANs) for Generating Electronic Health Records (EHRs) | Amira Soliman Atiye Sadat Hashemi |
Synthetic Electronic Health Records | Open |
| Incorporate behaviour modelling into AGV safety performance stack | Björn Åstrand | Incorporate behaviour modelling into AGV safety performance stack | Open |
| Intrusion detection and prevention for IIoT using Ensemble Deep Network | Reza Khoshkangini Mohamed Eldefrawy |
In this project students will work on network data and try to detect malicious behavior using ensemble deep network. | Open |
| Investigating depression signs among older adults using Swedish National Registry Data | Mahmoud Rahat | Investigating depression signs among older adults using Swedish National Registry Data | Open |
| Investigation of spread spectrum techniques to reduce the electromagnetic interference in switch mode power supply | Maria De Lauretis Elena Haller |
The goal of the project is to investigate spread-spectrum-based PWM techniques to reduce the EMI in motor drivers caused by the SMPS | Open |
| IoT Forensics | Mohamed Eldefrawy and Hazem Ali | To achieve a systematic approach for data extraction (i.e., imaging), forensically sound, from the hardware level | Open |
| Joint Analysis of Multimodal data on climate change for the educational purpose | Sławomir Nowaczyk Zeinab Shahbazi Carlos Silla |
Exploring climate change data using machine learning and deep learning | Open |
| Knowledge graphs in healthcare | Grzegorz J. Nalepa | Investigae the use of KG in healthcare applications | Open |
| Leveraging LLMs for Clinical Note Annotation and Uncertainty Estimation | Awais Ashfaq Prayag Tiwari |
The student will investigate the potential of LLMs to simplify clinical note annotation along with uncertainty estimation, contributing to improved healthcare data management. | Open |
| LiDAR Denoising | Eren Erdal Aksoy | In this project, the candidate is supposed to implement various filtering algorithm to denoise 3D LiDAR point cloud data. | Open |
| Lighting up the bicycle roads with drones | Cristofer Englund Lei Chen |
Lighting up the bicycle roads with drones | Open |
| Machine Learning for Segmentation of Lensed Galaxies: Distinguishing Source Galaxies from Gravitational Lenses | Tiago Cortinhal Idriss Gouigah Eren Erdal Aksoy Margherita Grespan Hareesh Thuruthipilly |
Machine Learning for Segmentation of Lensed Galaxies: Distinguishing Source Galaxies from Gravitational Lenses | Open |
| Machine Learning-based optimization of physical activity | Cristofer Englund Kevin Hernandez Diaz |
The project should be able to detect the difference between the current exercise and a reference version of the exercise. | Open |
| Mapping SFO mitigation/Linearization algorithms, trade-off between memory and computation on GPU | Hazem Ali (HH) Håkan Johansson (LiU) |
investigating the parallelisation and mapping of Sampling Frequency Offset algorithms | Open |
| Meta-learning for Multivariate Signals | Kunru Chen Anna Vettoruzzo Mohamed-Rafik Bouguelia |
Apply meta-learning algorithms to unlabelled time-series data to solve machine activity recognition problems. | Open |
| Model Heterogeneity in Federated Learning | Amira Soliman Sławomir Nowaczyk |
Group users within a federated learning environment into different learning overlays according to their behavioural similarities | Open |
| Model-Based Testing of Zero-Copy Protocols | Wojciech Mostowski | Challenges in Model-Based Testing of Zero-Copy Protocols | Open |
| Modeling patient trajectories using different representation learning techniques | Stefan Byttner Kobra Etminani Amira Soliman |
Modeling Electronic Health Record (EHR) data and predict future events for specific patients | Open |
| Multi-Sensor Fusion for Semantic Scene Understanding | Eren Erdal Aksoy | Multi-Sensor Fusion for Semantic Scene Understanding | Open |
| Multi-modal Weather type Classifier | Eren Erdal Aksoy | Camera, LiDAR, and Radar based weather type classification using deep neural networks on the K-RADAR dataset | Open |
| Multi-modal risk prediction models on osteoporotic fracture, myocaridal infarction and stroke | Kobra Etminani (Farzaneh) TBD Peder Wiklund (from Region Halland) Markus Lingman (from Region Halland) |
develop and evaluate how well a multimodal model derived from the regional healthcare information platform, with or without the CT-derived measures, can predict the risk of subsequent osteoporotic fracture, myocardial infarction and stroke | Open |
| Multiband RF Rectifier for Self-Powered IoT Devices | Amjad Iqbal | In this project, Mutiband RF rectifiers will be designed for self-powered IoT devices | Open |
| Multitask Learning in Autonomous Driving | Eren Erdal Aksoy | The student should annotate 3D point cloud data for semantic segmentation and object detection. A new deep learning model needs to be implemented to learn both tasks. | Open |
| Multivariate Time Series Analysis with Irregularly Sampled Data | Awais Ashfaq Prayag Tiwari |
The student will devise methods for handling irregularly sampled multivariate time series data, addressing missing data and modeling temporal relationships for applications in healthcare | Open |
| Music style transfer | Peyman Mashhadi Yuantao Fan |
Develop a system that receives a piece of music in one genre and changes/transfers its style into another genre, using machine learning algorithms. | Open |
| Network-assisted positioning in confined spaces using 802.11 Access Layer information | Oscar Amador Molina Elena Haller |
Proof of Concept of a Position-and-Time entity based on 802.11 to enable embedded beaconing systems (e.g., a “connected reflective vest”) for workers in confined spaces where satellite-based positioning is not possible. | Open |
| Object Tracking and Anticipation | Eren Erdal Aksoy | The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous driving. | Open |
| On the explainability of Graph Neural Networks: an application in credit scoring | Atiye Sadat Hashemi Peyman Mashhadi |
On the explainability of Graph Neural Networks: an application in credit scoring | Open |
| Open and Realistic smart City Activities Simulator (ORCAS) | Sławomir Nowaczyk Richard Bunk |
Create a simulation platform, loosely inspired by gamification, that is in principle capable of capturing the complexity of a complete city. | Open |
| Optimising Energy Consumption for Ferries in Collaboration with Cetasol | Yuantao Fan Peyman Mashhadi |
This project aims at developing data-driven methods to understand ferry operations and optimise enegery consumption | Open |
| Optimization of a 5G algorithm by parallelization | Hazem Ali | Optimization of a 5G algorithm by parallelization | Open |
| Predicting Energy Consumption for Heavy-Duty Vehicles via Time Series Embeddings (in collaboration with Volvo) | Yuantao Fan & TBD | Develop deep learning based methods for time series forecasting; explore self-supervised learning methods for multi-variate time series embeddings | Open |
| Predicting electricity generation capacity in solar and wind power plants based on meteorological data using machine learning algorithms | Reza Khoshkangini Ramin Sahba Amin Sahba |
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)). | Open |
| Privacy-Preserved Generator for Generating Synthetic EHR data | Atiye Sadat Hashemi Jens Lundström Farzaneh Etminani |
Time-series GAN and generation of synthetic electrical health records | Open |
| Project opportunities at ElectronicArts | TBD | Each year there are several project opportunities at Electronic Arts | Open |
