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Previous     Results 51 – 100    Next        (20 | 50 | 100 | 250 | 500)
  Supervisors OneLineSummary Status
Explainable AI by Training Introspection Jens Lundström
Peyman Mashhadi
Amira Soliman
Atiye Sadat Hashemi
Research and development of novel XAI methods based on training process information Open
Explainable Decision Forest Sławomir Nowaczyk
Hamid Sarmadi
Sepideh Pashami
Designing an explainable decision forest classifier for fault detection Open
FLBench: A Comprehensive Experimental Evaluation of Federated Learning Frameworks Sadi Alawadi
Jens Lundström
Exploring Federated Learning Frameworks Open
Fair Conformal Prediction Ece Calikus Our goal is to design algorithms using conformal prediction framework that make fair predictions across various groups based on e.g., age, sex, income. Open
Fair representation learning of electronic health records Ali Amirahmadi
Ece Calikus
Kobra Etminani
Fair representation learning of electronic health records Open
Fault detection using acoustic signals through anomaly detection Elena Haller
Peyman Mashhadi
Fault detection using acoustic signals through anomaly detection Open
Feature-wise normalization for 3D medical images Amira Soliman
Stefan Byttner
Kobra Etminani
Normalization of 3D medical imaging either as a data pre-processing or as feature-wise batch normalization during CNN model training 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
Forecast energy consumption in buildings to help Mestro customers save energy To be decided (contact Slawomir Nowaczyk for more details) The thesis will be focused on forecasting the energy consumption in buildings (e.g. electricity consumption), with some optional “add-ons” where student will also develop... 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
Hide-and-Seek Privacy Challenge (NeurIPS 2020) Onur Dikmen Building novel methods for privacy-preserving data sharing and/or re-identification 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
Indoor localization for ground vehicles Cristofer Englund Indoor localization for ground vehicles Open
Intelligent claim Process with Volvia To be decided (contact Slawomir Nowaczyk for more details) Intelligent claim Process 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
Multitask learning on vehicle data Mahmoud Rahat
Peyman Mashhadi
Learning shared representation using multitask learning on a vehicle-related data 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
Previous     Results 51 – 100    Next        (20 | 50 | 100 | 250 | 500)