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From ISLAB/CAISR
| Supervisors | OneLineSummary | |
|---|---|---|
| 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 |
| Hydro Power Station | TBD (contact Slawomir Nowaczyk if interested) | Collaboration with Ålberga Bruk 1919 |
| Ideology and Power Identification in Parliamentary Debates | Pablo Picazo-Sanchez | Ideology and Power Identification in Parliamentary Debates |
| Improving Time-series Generative Adversarial Networks (GANs) for Generating Electronic Health Records (EHRs) | Amira Soliman Atiye Sadat Hashemi |
Synthetic Electronic Health Records |
| Investigating depression signs among older adults using Swedish National Registry Data | Mahmoud Rahat | Investigating depression signs among older adults using Swedish National Registry Data |
| 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 |
| IoT Forensics | Mohamed Eldefrawy and Hazem Ali | To achieve a systematic approach for data extraction (i.e., imaging), forensically sound, from the hardware level |
| 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 |
| Knowledge graphs in healthcare | Grzegorz J. Nalepa | Investigae the use of KG in healthcare applications |
| 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. |
| 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 |
| 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. |
| 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 |
| 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. |
| 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 |
| Model-Based Testing of Zero-Copy Protocols | Wojciech Mostowski | Challenges in Model-Based Testing of Zero-Copy Protocols |
| Multi-Sensor Fusion for Semantic Scene Understanding | Eren Erdal Aksoy | Multi-Sensor Fusion for Semantic Scene Understanding |
| 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 |
| 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 |
| Multiband RF Rectifier for Self-Powered IoT Devices | Amjad Iqbal | In this project, Mutiband RF rectifiers will be designed for self-powered IoT devices |
| 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. |
| 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 |
| 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. |
| 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. |
| 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 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. |
| Optimization of a 5G algorithm by parallelization | Hazem Ali | Optimization of a 5G algorithm by parallelization |
| 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 |
| 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 |
| Project opportunities at ElectronicArts | TBD | Each year there are several project opportunities at Electronic Arts |
| Project opportunities at HMS | TBD | Each year there are several project opportunities at HMS (a company with motto of "We create products that enable industrial equipment to communicate and share information") |
| Project opportunities at RISE | TBD | Each year there are several project opportunities at RISE (Research Institutes of Sweden) |
| Project opportunities at Toyota | TBD | Each year there are several project opportunities at Toyota |
| Project opportunities at zenseact | TBD | Each year there are several project opportunities at zenseact |
| Project opportunity at PERIsign | Abdallah Alabdallah & TBD | Peritonitis (inflammation of the peritoneum) detection via EMG-signals. |
| Project with Atos | TBD Please contact Sławomir Nowaczyk if interested |
The project involves the development of software for the TrueDepth technology of the iPhone. |
| Project with chargefinder.com | TBD Please contact Sławomir Nowaczyk if interested |
Use data to create a machine learning model that can predict estimated availability of a specific charger based on day, time and maybe other external factors (holiday, weather) |
| Project(s) at Volvo Cars Corporation | TBD | Thesis topics at Volvo Car Corporation |
| Project(s) at Volvo Group | TBD | Thesis topics at Volvo Group |
| Protein Language Models for drug discovery | Prayag Tiwari Ali Amirahmadi |
Leveraging the sequence-based transformer protein language model for improving potential drug targets identification |
| Quantifying exercise-induced muscle fatigue by machine learning | Jens Lundström | Exploring machine learning methods on an EMG muscle fatigue pipeline |
| Quantum Machine Learning models for predicting disease | Prayag Tiwari | explore quantum models, including hybrid (classical-quantum), and apply them to different disease prediction tasks |
| Real-time bladder scanner | Pererik Andreasson | Real-time bladder scanner |
| Reconfigurable Orbital angular momentum (OAM) antenna for High-Speed Wireless Communications | Amjad Iqbal | In this project, a reconfigurable (operating modes will be controlled using p-i-n diodes) OAM antenna will be designed. |
| Reliability Analysis and Assessment of Multi- Core System-on-Chip through Transaction Pro- filing and Machine Learning | Mahdi Fazeli | |
| Resilience of ML Hardware Accelerators Against Accuracy Degrading Trojans | Mahdi Fazeli | The goal of this project is to assess the resilience of machine learning (ML) hardware accelerators, with a specific focus on Convolutional Neural Network (CNN) accelerators, when subjected to Trojan attacks aimed at degrading their accuracy. |
| Road user behavior prediction | Cristofer Englund Björn Åstrand Fernando Alonso-Fernandez |
Road user behavior recognition and manipulation using deep learning |
| SCANIA Project: Graph neural networks for anomaly detection | Sepideh Pashami | Graph neural networks for anomaly detection |
| Secure Hardware Accelerators for Machine Learning: Design, Evaluation, and Mitigation of Vulnerabilities | Mahdi Fazeli and Ahmad Patooghy (North Carolina University US) |
This master's project focuses on investigating the security of hardware accelerators designed for machine learning |
| Secure IP Core Design Through LLM-Driven Logic Locking | Mahdi Fazeli |
