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List of results

• Securing Multi-Processor System-on-Chips: Assessing Vulnerabilities to Hardware Trojans Through Thermal Profiles  + (This master's thesis project is dedicated to conducting a comprehensive security assessment of modern multi-processor System-on-Chips (MPSoCs) equipped with multiple thermal sensors.)
• Optimising Energy Consumption for Ferries in Collaboration with Cetasol  + (This project aims at developing data-driven methods to understand ferry operations and optimise enegery consumption)
• Deep stacked ensemble  + (This project aims at training multiple parallel deep networks in such a way to learn different representation of data which will be suitable to frame these networks in stacked ensemble framework.)
• Concept Re-identification to Explain Online Continual Learning  + (This project aims to apply techniques from recurrent concept drifts to explain the predictions of Online Continual Learning methods.)
• Evolving Kolmogorov-Arnold Networks  + (This project aims to enhance the architecture of Kolmogorov-Arnold Networks (KANs) by optimizing key components such as loss functions, activation functions, initialization methods, and learning processes to improve their performance and interpretability.)
• Dynamic Churning-Based Logic Locking for Enhanced Hardware Security  + (This project aims to explore and implement advanced logic locking techniques to improve the security of integrated circuits (ICs) against modern attacks.)
• Automatic Idea Detection for controlling Healthcare-associated infections  + (This project aims to use advanced NLP tools to automatically detect interesting ideas by processing text available in the medical forums to address the Healthcare-associated infections problem in the hospitals)
• Automatic Idea Detection from social media for Controlling and Preventing Healthcare-Associated Infections (with funding opportunity)  + (This project aims to use advanced NLP tools to automatically detect interesting ideas by processing text available in the medical forums to address the Healthcare-associated infections problem in the hospitals)
• AGENTIC-AI TOWARDS INTERPRETATION OF SERVICE CANVAS AND AUTOMATION OF TRUSTWORTHY ML-PIPELINES  + (This project allows the MSc student(s) to study and experiment on Agentic AI methods for the generation of trustworthy ML-pipelines)
• Vehicle Usage Modeling over Time  + (This project intents to explore the modeling of the usage of vehicles using unsupervised machine learning algorithms in different context which are logged over time.)
• Forklift Trucks Usage Analysis  + (This project is about applying machine learning methods to have a better understanding for the usage of forklifts trucks in industrial application.)
• Deep feature analysis and extraction on Logged Vehicle data for the task of predictive maintenance  + (This project is about applying supervised/unsupervised methods of feature selection on Logged Vehicle data (LVD) from Volvo trucks and investigate the contribution in model construction for different predictive maintenance tasks)
• Exploring, modelling and optimization of home care regions  + (This project is about developing tools and methods for optimization of health care resources using machine learning as the central technology.)
• Detecting different types of machines based on usage  + (This project is about studying how can we distinguish among different types of machines based on their usage.)
• Empowering Adult Learners and Educators through AI  + (This project is part of an international collaborative project LEAD-AI, which aims to create a capacity-building programme designed to enhance AI skills of both educators and adult learners.)
• Reinforcement Learning with Adaptive Representation Learning  + (This project targets finding representations that make the reinforcement learning more efficient in terms of finding an easier state to action mapping.)
• Reliability Analysis and Assessment of Multi- Core System-on-Chip through Transaction Pro- filing and Machine Learning  + (This project will contribute to the develo … This project will contribute to the development of automated reliability as- sessment techniques for multi-core SoCs and demonstrate the potential of in- tegrating transaction profiling with ML-driven analysis to enhance the overall security and robustness of such systems.l security and robustness of such systems.)
• AI-driven Automotive Service Market Logistics  + (This project, in collaboration with Volvo Logistics, focuses on using state-of-the-art methods based on meta-learning to improve demand forecasting, inventory management and spare parts availability at Volvo dealers and warehouses.)
• Workshop Automation together with Volvo Group  + (This project, in collaboration with Volvo Group, investigates how automation can raise workshop throughput, repair quality, and technician experience through data-driven perception and pragmatic use of automation.)
• Resilient Recovery: A Byzantine Fault Tolerance (BFT) Framework for Tactical Mesh Networks  + (This proposal addresses the critical state-poisoning vulnerability in tactical networks during post-partition recovery. The research proposes the development of a recovery protocol centered on Byzantine Fault Tolerance (BFT))
• Robotics for Urban Traffic Support: Design, Prototyping, and Intelligent Interaction in Smart Cities  + (This proposal focuses on the application of robotics to enhance traffic safety and efficiency in smart cities. The research considers the interaction with VRU)
• Leveraging LLM for Proactive Fault Analysis and Prediction in V2X Communication Systems  + (This proposal outlines research into applying LLMs for advanced fault analysis and prediction within V2X communication systems. The study will involve analyzing public datasets, developing novel datasets for specific V2X scenarios.)
• Safety Assurance in Critical Automotive Control Systems: A Human-Centric and Standards-Compliant Approach  + (This research proposes an in-depth study into the safety aspects of critical automotive control systems, such as those found in autonomous vehicles. It will investigate the interplay between communication dependency in specific scenarios.)
• Tabular Health Data Under Attack: Benchmarking Privacy Risks and Defenses  + (This thesis aims to investigate privacy attacks and defenses in tabular health data.)
• Utilization of Foundation Models for Federated Learning  + (This thesis aims to leverage Foundation Models and develop new aggregation paradigms to overcome challenges in Federated Learning.)

• Thesis with Medius  + (Three thesis topics with Medius)

• Project Related to FeelAI -Collaboration with Volvo AMT  + (Time Series Forecasting with Incrementally Evolving Windows)
• Privacy-Preserved Generator for Generating Synthetic EHR data  + (Time-series GAN and generation of synthetic electrical health records)
• Timeseries XAI in Cybersecurity and Industry  + (Timeseries data analysis with XAI in Cybersecurity and Industry)
• Timeseries representation learning for EHR  + (Timeseries representation learning for Electronic Health Records)
• IoT Forensics  + (To achieve a systematic approach for data extraction (i.e., imaging), forensically sound, from the hardware level)
• XAI for yoga posture recognition  + (To analyze the classification of yoga postures and the potential misclassification due to occlusion and perspective of images)
• Analyzing white blood cells in blood samples using deep learning techniques  + (To analyze white blood cell content in blood samples using deep learning techniques.)
• Mining For Meanings In Robot Maps  + (To build a hybrid map by augmenting the intrinsic kinematic model of a mobile robot to a spatial map, and semi-supervised learning of meanings towards self/situation awareness.)
• Face and eye categorization and detection  + (To build a new database of face and eye images of different species and to evaluate holistic and local detection algorithms)
• AI-Driven Semantic Encoding for Efficient Communication  + (To develop and evaluate an AI-based semantic encoding model capable of transforming raw data into compact, structured representations.)
• Biases in electronic health records  + (To evaluate the impact of sample bias on the predictive value of machine learning models built using EHR data)
• Evaluating the Digital Tools for Promoting Sustainable Food Consumption  + (To identify the key features and functionalities of sustainable food apps in Sweden)
• Identity verification of humans performing physical activities  + (To verify the identity of an individual performing a particular activity with sensors placed at different parts of the body)
• Blockchain for polls and elections  + (Today, there is no blockchain solution that meets the requirements for polls/elections; therefore, we would like to develop our own)
• Towards robustness of post hoc Explainable AI methods  + (Towards robustness of post hoc Explainable AI methods)
• Activity monitoring for AAL  + (Tracking of more than one person in a smart environment using fixed sensors and a mobile robot)
• CACC  + (Traffic situation estimator for adaptive cruise control (ACC))
• Understanding Applicability of Echo State Networks to Diverse Industrial Data  + (Understanding the Governing Dynamics of Echo State Networks (ESN) on time varying signals (in terms of properties) from different industry sources.)
• Captioning Engine for AD/ADAS data using Multi-Modal Large Language Models  + (Use advanced LLMs to describe and interpret sensor data from autonomous vehicles.)
• Project with chargefinder.com  + (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))
• Barcode mapping in warehouses  + (Using barcode detection and decoding for mapping the infrastructure and inventory of warehouses)
• Visual Transformers for 3D medical images Classification: use-case neurodegenerative disorders  + (Using visual transformers for predicting the diagnosis of multiple neurodegenerative brain disorders)
• Embeded wearable sensors application at the HINT  + (Using wearable stretch sensors to recognize activities of a user at HINT)
• Visual analysis for infotainment in car interiors  + (Visual analysis to steer infotainment in car interiors)
• Analyzing Gender Bias in Pose Estimation Models  + (We will analyze the gender bias of current pose estimation models when trained with unbalanced gender data)