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From ISLAB/CAISR
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 |