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List of results

• Project opportunities at zenseact  + (Each year there are several project opportunities at zenseact)
• Emergency vehicle movement prediction  + (Emergency vehicle movement prediction)
• Analysing Engine Performance based on Vehicle Data  + (Estimate engine perfromance based on data logged on-board Volvo vehicles and using it for diagnostics, e.g. detection of cylinder heads in need of replacement)
• Traffic Estimation From Vehicle Data  + (Estimate traffic density based on logged vehicle data)
• Surface normal estimation by Spiral Codes  + (Estimating 3d surface normal from a single image)
• Blood splatter analysis  + (Estimation of direction and distance to origin from blood splatter images)
• Machine Unlearning Faithfulness with XAI  + (Evaluating Machine Unlearning Faithfulness in Deep Neural Networks using Explainable AI)
• Safe deployment of Deep Neural Networks in automotive engineering  + (Evaluation of DNN factors with respect to robustness in safety critical systems.)
• Evaluation of captchas.  + (Evaluation of liveness detection provided by ocr captchas)
• Evolutionary Behavior Trees for Multi-Agent Task-Oriented Environment  + (Evolutionary generating Behavior Trees for use in multi-agent task-oriented environment.)
• Collaboration with Bankomat  + (Explainable AI for Forecasting in Corporate Environments ( RQ: How to provide interpretable/explainable forecasts that align with business logic?)
• XAI for time series data - collaboration with the mathematics and statistics dept. of the University of West Florida  + (Explainable Artificial Intelligence (XAI) on Time Series Data)
• Explainable Anomaly Detection  + (Explainable anomaly detection in time series data utilising causal inference)
• Sailboat Motion Planning using the Level-Set Method  + (Explore the use of Level-Set and Fast-Marching Methods to create time-optimal motions of a point in a plane subject to direction-dependent velocity.)
• Foundation Models for Time Series Analysis  + (Explore the use of large pre-trained time-series foundation models (TSFM) and design fine-tuning strategies on tasks of interest)
• FLBench: A Comprehensive Experimental Evaluation of Federated Learning Frameworks  + (Exploring Federated Learning Frameworks)
• Joint Analysis of Multimodal data on climate change for the educational purpose  + (Exploring climate change data using machine learning and deep learning)
• Quantifying exercise-induced muscle fatigue by machine learning  + (Exploring machine learning methods on an EMG muscle fatigue pipeline)
• Human ground robot interaction  + (External communication from mobile robots to minimize conflicts with pedestrians)
• Scalable Standardized Information Extraction from Free-Text Electronic Health Records  + (Extracting clinical information from free-text notes and providing standardized mapping of extracted concepts using the SNOMED CT medical ontology.)
• Body posture alignment feedback using xAI  + (Extracting the body alignment in different postures and giving feedback to reduce harm during physical exercise)
• F1tenth  + (F1tenth competition)
• Improved face tracking driven by optical flow  + (Face Tracking Using Optical Flow)
• Fair representation learning of electronic health records  + (Fair representation learning of electronic health records)
• ISLAB/CAISR:Fault detection using acoustic signals through anomaly detection  + (Fault detection using acoustic signals through anomaly detection)

• A study about the future and usability of Bio-electronic “smart” implants in humans  + (Feasibility study on bioimplants in humans.)

• Federated learning in automotive industry  + (Federated learning in automotive industry)
• Project with HMS  + (Few-shot Learning for Quality Inspection)
• Segmentation of shoeprints  + (Finding boundaries of homogeneous regions in shoeprint images)
• Wisdom of the crowd, is there a single crowd?  + (Finding different clusters of machines based on their behavior as a first step towards anomaly detection and predictive maintenance.)
• Model Volvo Truck Lifetime Repair History  + (Finding good representations for data-driven description of Volvo truck's repair and maintenance history)
• Thermal Profiling of Residential Energy Consumption for Heat Pump and District Heating Customers  + (Finding interesting patterns of heat pump and district heating customers in order to identify meaningful thermal profiles)
• Detecting Faults and Estimating Missing Values in Smart Meter Data  + (Finding outliers and missing energy consumptions, and replace them with estimated values)
• Finding patterns/motifs in time series data  + (Finding patterns/motifs in time series data, for autonomous clustering or outlier detection)
• Peer Group Discovery in District Heating Substations and Heat Pumps for Self-Monitoring  + (Finding suitable peer groups to represent district heating and heat pump customers)
• Meta-learning for evaluation and implementation of predictive maintenance solution  + (Finding the best strategy to schedule a predictive maintenance intervention optimizing the cost of unexpected breakdowns against unuseful visits to the workshop.)
• Representation of Complex Data Types for Machine Learning  + (Finding ways to represent complex data types (e.g. histograms) present in Logged Vehicle Database databse for machine learning-based fault prediction)
• Replacements vs repairs. What is really a breakdown from the point of view of the data?  + (Finding ways to test how similar or different are the actions performed on a faulty machine. How does the effect of an intervention on the machine affect the data?)
• FirstResponse  + (First response to emergency situation in a smart environment using a mobile robot)
• Multi-robot trajectory adaptation using a state-time elastic band approach  + (For teams of robots moving through dynamic environments, deform planned trajectories in space and time such that they remain collision-free and reach the goal (if possible) or report failure if replanning is needed.)
• Detection of smart cars cyber attacks  + (For treating the probem of cyber attacks against smart vehicles, new change-point detection and anomaly detection methods by means of statistics and machine learning are developed and evaluated.)
• Forecasting Industrial IoT Time Series @AlfaLaval  + (Forecasting industrial IoT Time Series)
• Short-Term Energy Demand Forecasting  + (Forecasting the electricity consumption based on historical usage by using smart meter data)
• Collaboration with Bankomat 5  + (Forecasting with Sparse and Noisy Corporate Data RQ: What preprocessing techniques improve LLM performance on sparse transactional datasets?)
• Prototype Aligned Embedding for Time Series Forecasting  + (Generate prototype based explanation for time series forecasting)
• Evaluating Privacy Leakage Attacks on Fine-Tuned Clinical Models with Synthetic Data  + (Generate synthetic clinical data to fine-tune models and systematically evaluate privacy leakage risks using advanced attack techniques.)
• Intelligible patient representation for outcome prediction of congestive heart failure patients  + (Generating patient representation using EHR data)
• Generating synthetic time series data in case of data scarcity  + (Generating synthetic time series data in case of data scarcity)
• Image Retrieval for Arguments  + (Given a controversial topic, the task is to retrieve images (from web pages) for each stance (pro/con) that show support for that stance.)
• Human Value Detection  + (Given a textual argument and a human value category, classify whether or not the argument draws on that category.)
• SCANIA Project: Graph neural networks for anomaly detection  + (Graph neural networks for anomaly detection)