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List of results
- Design and Evaluation of an LLM-Based Travel Planner with Dynamic Event and Accommodation Data + (2025-26)
- Interactive Anomaly Detection + (4th of November 2019 to 29th May 2020)
- Model-Based Testing of Zero-Copy Protocols + (6 months, starting as soon as possible)
- Analysis of industrial time series + (ASAP)
- Quantum Machine Learning models for predicting disease + (ASAP)
- Graph Neural Networks for cardiovascular disease + (ASAP)
- Gait analysis using wearable sensors in Parkinson's disease + (Autumn 2020 - Spring 2021)
- Explainable Decision Forest + (Autumn 2024)
- Project opportunity at PERIsign + (Autumn 2024)
- Tabular Health Data Under Attack: Benchmarking Privacy Risks and Defenses + (Autumn25-Spring26)
- Constrained dynamic path planning for truck and trailer + (Dec 2014 - June 2015)
- Comparative study of an automated testing coverage for a TCP/IP stack implementation + (Dec 2020 - May 2021)
- Security analysis of IIoT connectivity protocols + (Dec 2021 - May 2022)
- Reinforcement learning for End-to-End autonomous driving + (December 2016 - June 2017)
- Automatic Generation of Realtime Machine Learning Architectures + (December 2020, May 2021)
- Recurrent and Deep Learning for Machine Prognostics + (Fall 2017)
- Automatic Machine Learning (AUTO-AUTO-ENCODER!) + (Fall 2018)
- Peer Group Discovery in District Heating Substations and Heat Pumps for Self-Monitoring + (Fall 2018)
- Wisdom of the crowd, is there a single crowd? + (Fall 2018)
- Deep Recurrent Networks for Machine Prognostics + (Fall 2018)
- Understanding usage of Volvo trucks + (Fall 2018)
- Understand Patterns in Volvo Truck Lifetime Repair History + (Fall 2018)
- Contactless monitoring of blood pressure using photoplethysmography + (Fall 2018)
- Machine Learning and LeadTime Prediction + (Fall 2018)
- Deep learning and Back Order Solutions + (Fall 2018)
- AI Enabled Service Market Logistics + (Fall 2019)
- AI R&D at King + (Fall 2019)
- Analyzing white blood cells in blood samples using deep learning techniques + (Fall 2019)
- Automatic Generation of Descriptive Features for Predicting Vehicle Faults + (Fall 2019)
- Detecting changes in causal relations + (Fall 2019)
- Detecting different types of machines based on usage + (Fall 2019)
- Estimating Architectural Properties of Buildings Based on Heating Data + (Fall 2019)
- F1tenth + (Fall 2019)
- Forklift Trucks Usage Analysis + (Fall 2019)
- Name of the new projectEstimating agricultural development indicators over large areas from satellite images – an approach using convolutional neural networks and transfer learning + (Fall 2019)
- Representation Learning for Deviation Detection + (Fall 2019)
- Transfer Learning for Machine Diagnostics and Prognostics + (Fall 2019)
- Value of BIG DATA for Large Building Owners + (Fall 2019)
- Forecast energy consumption in buildings to help Mestro customers save energy + (Fall 2020)
- Intelligent claim Process with Volvia + (Fall 2020)
- Risk as a Service with Volvia + (Fall 2020)
- Transfer Learning for Machine Diagnosis and Prognosis + (Fall 2020)
- Algorithm development for realtime route planning + (Fall 2020)
- Thesis with Jayway + (Fall 2020)
- Sandboxed scripting on embedded systems + (Fall 2021)
- Effecient implementation of DL models on embedded platforms + (Fall 2021)
- Building a Knowledge-based AI Framework for Mobility + (Fall 2021)
- Project with Whole AB + (Fall 2021)
- Music style transfer + (Fall 2021)
- Explainable AI for predictive maintenance in collaboration with Volvo + (Fall 2021)
- Deepfake Detection + (Fall 2021)
- Optimising Energy Consumption for Ferries in Collaboration with Cetasol + (Fall 2021)
- Identify boundary or, corner test cases for AD/ADAS functions using ML in MIL and HIL environment + (Fall 2021)
- Optimization of a 5G algorithm by parallelization + (Fall 2021)
- Blockchain for polls and elections + (Fall 2022)
- Project with Atos + (Fall 2022)
- Thesis with Medius + (Fall 2022)