Projects and Theses

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Are you looking for an interesting topic for a project or a thesis?

Here, you can look for topics across various application fields like Autonomous driving, Renewable energy applications etc. and also across various machine learning topics like Novelty detection, Graph neural networks etc. Under each category, you will find names of researchers from IES department who are working in the respective categories and the specific topics offered by each researcher can be found by clicking on the dropdown button. The contact details of researchers are also provided with respective links to employee webpages.

Application Fields

Autonomous Driving and e-Mobility

  • Research topics:
    • Failure Detection in (Electro-)Motor Test Stands
    • Predictive Monitoring and Analysis
    • Deep Learning Performance Analysis of Electric Motors
    • Multidimensional Target Prediction
  • Employee Site
  • Research topics:
    • Data Acquisition, Annotation, and Evaluation
    • Perception (Camera, Radar, Lidar)
  • Employee Site

Biometrics

  • Research topics:
    • Biometrics with a focus on online signature verification
  • Employee Site

Renewable Energy

  • Research topics:
    • Self-adaptive charging management for electric vehicle infrastructures
  • Employee Site
  • Research topics:
    • Transfer learning and multi-task learning
  • Employee Site

Experimental Physics & Materials Science

  • Research topics:
    • Deep learning methods in material science applications
  • Employee Site
  • Research topics:
    • Intelligent experimentation in technology and physics
    • Image analysis for accelerator physics and microscopy
    • 2D & 3D particle tracking in the nano range
  • Employee Site
  • Research topics:
    • Deep learning methods in materials science applications
    • Deep learning methods in accelerator physics
    • Inversion of simulations with deep learning
  • Employee Site

Finance

  • Research topics:
    • Data-centric deep learning in application-oriented settings
  • Employee Site

Learning & Teaching Systems

  • Research topics:
    • Fully integrated learning, teaching and assessment environments
    • Simulators in learning, teaching and assessment (in technical computer science)
    • Learning, teaching and assessment life cycles (in computer engineering)
  • Employee Site

Machine Learning Techniques

Deep Learning

  • Research topics:
    • Deep generative models - VAEs & GANs
    • Embedding learning with deep neural networks
  • Employee Site
  • Research Topics:
    • Deep Learning Performance Analysis of Electric Motors
    • Deep Learning for Magnetic Fiel Estimation
    • Generative Deep Learning
    • Representation Learning
  • Employee side
  • Research topics:
    • Accelerated topology optimization with deep generative models
  • Employee Site
  • Research topics:
    • Intelligent experimentation in technology and physics
    • Image analysis for accelerator physics and microscopy
    • 2D & 3D particle tracking in the nano range
  • Employee site
  • Research topics:
    • Deep reinforcement learning for charging management
  • Employee Site
  • Research topics:
    • Deep object detection in autonomous environments
  • Employee Site
  • Research topics:
    • Deep learning methods for applications in materials science
    • Deep learning methods in accelerator physics applications
    • Inversion of simulations with deep learning
  • Employee Site
  • Research topics:
    • Data-centric deep learning in application-oriented settings
  • Employee Site
  • Research topics:
    • (Unsupervised) Representation Learning for Data Acquisition
    • Object Detection for Autonomous Driving
  • Employee Site

Explainable AI

  • Research topics:
    • Explainable deep reinforcement learning
  • Employee Site
  • Research topics:
    • Explainability of the framework for continuous learning
  • Employee Site
  • Research topics:
    • Explainability of graph neural networks
  • Employee Site

Graph Neural Networks

  • Research topics:
    • Structural dynamic graphs
    • Graph embeddings
    • Graph neural networks
    • Graph stream processing
  • Employee Site
  • Research topics:
    • Neural graph networks (GNN)
    • Attribute dynamic graphs
    • Graph representations
  • Employee Site
  • Research topics:
    • Graph embeddings for transfer learning and multi-task learning
  • Employee Site
  • Research topics:
    • Neural graph networks
    • Graph convolution neural networks (spatial and spectral)
    • Translation of (learning) problems in graph-based form
    • Explainability of graph neural networks
  • Employee Site

Human-in-the-Loop

  • Research topics:
    • Active learning with multiple uncertain sources of knowledge
    • Active learning with alternative query types
    • Learning with noisy labels
    • Learning from information beyond labels
  • Employee Site
  • Research topics:
    • Active continuous learning
    • Deep active learning
  • Employee Site
  • Research topics:
    • Active learning for deep object detection
    • Active learning in deep learning
    • Interaction between humans and learning machines
  • Employee Site
  • Research topics:
    • Stream-based active learning
    • Stream/online learning
    • Active learning
  • Employee Site
  • Research topics:
    • Data Annotation and Evaluation Workflows
  • Employee Site

Novelty Detection

  • Research topics:
    • Anomaly Detection in Heterogeneous Sensor Data
  • Employee Site
  • Research topics:
    • Renewable energy forecasting and anomaly detection
  • Employee Site

Transfer Learning

  • Research topics:
    • Multi-task learning and transfer learning
  • Employee Site
  • Research topics:
    • Transfer learning and multi-task learning
  • Employee Site

Uncertainty & Probabilistic Models

  • Research topics:
    • Uncertainty modeling in deep learning (classification & object detection)
  • Employee Site
  • Research topics:
    • Sample Selection for Data Acquisition
  • Employee Site

Are you looking for an interesting topic for a project or a thesis?

Here you can search for topics from different application areas, such as autonomous driving, applications in the field of renewable energies, etc. and also for topics from the field of machine learning, such as novelty detection, graphical neural networks, etc.. Under each category, you will find the names of the researchers at the IES department working on each topic. You can find the specific topics offered by each researcher by clicking on the dropdown button. The researchers' contact information is also provided with corresponding links to their websites.

Fields of application

Autonomous driving and e-mobility

  • Research Topics:
    • Failure Detection in (Electro-)Motor Test Stands
    • Predictive Monitoring and Analysis
    • Deep Learning Performance Analysis of Electric Motors
    • Multidimensional Target Prediction
  • Staff page
  • Research Topics:
    • Data Acquisition, Annotation, and Evaluation
    • Perception (Camera, Radar, Lidar)
  • Staff page

Biometrics

  • Research topics:
    • Biometrics with a focus on online signature verification
  • Staff page

Renewable energies

  • Research topics:
    • Self-adaptive charging management for electric vehicle infrastructures.
  • Staff page
  • Research topics:
    • Transfer learning and multi-task learning
  • Staff page

Experimental Physics & Materials Science

  • Research topics:
    • Deep learning methods in material science applications
  • Staff page
  • Research topics:
    • Intelligent experimentation in technology and physics
    • Image analysis for accelerator physics and microscopy
    • 2D & 3D particle tracking in the nano range
  • Staff page
  • Research topics:
    • Deep learning methods in materials science applications
    • Deep learning methods in accelerator physics
    • Inversion of simulations with deep learning
  • Staff page

Finance

  • Research topics:
    • Data-centric deep learning in application-oriented settings
  • Staff page

Learning & Teaching Systems

  • Research topics:
    • Fully integrated learning, teaching and assessment environments
    • Simulators in learning, teaching and assessment (in technical computer science)
    • Learning, teaching and assessment life cycles (in computer engineering)
  • Staff page

Machine learning techniques

Deep Learning

  • Research topics:
    • Deep generative models - VAEs & GANs
    • Embedding learning with deep neural networks
  • Staff page
  • Research Topics:
    • Deep Learning Performance Analysis of Electric Motors
    • Deep Learning for Magnetic Fiel Estimation
    • Generative Deep Learning
    • Representation Learning
  • Staff page
  • Research topics:
    • Accelerated topology optimization with deep generative models
  • Staff page
  • Research topics:
    • Intelligent experimentation in technology and physics
    • Image analysis for accelerator physics and microscopy
    • 2D & 3D particle tracking in the nano range
  • Staff page
  • Research topics:
    • Deep reinforcement learning for charging management
  • Staff page
  • Research topics:
    • Deep object detection in autonomous environments
  • Staff page
  • Research topics:
    • Deep learning methods for applications in materials science
    • Deep learning methods in accelerator physics applications
    • Inversion of simulations with deep learning
  • Staff page
  • Research topics:
    • Data-centric deep learning in application-oriented settings
  • Staff page
  • Research Topics:
    • (Unsupervised) Representation Learning for Data Acquisition
    • Object Detection for Autonomous Driving
  • Staff page

Explainable AI

  • Research topics:
    • Explainable deep reinforcement learning
  • Staff page
  • Research topics:
    • Explainability of the framework for continuous learning
  • Staff page
  • Research topics:
    • Explainability of graph neural networks
  • Staff page

Graph Neural Networks

  • Research topics:
    • Structural dynamic graphs
    • Graph embeddings
    • Graph neural networks
    • Graph stream processing
  • Staff page
  • Research topics:
    • Neural graph networks (GNN)
    • Attribute dynamic graphs
    • Graph representations
  • Staff page
  • Research topics:
    • Graph embeddings for transfer learning and multi-task learning
  • Staff page
  • Research topics:
    • Neural graph networks
    • Graph convolution neural networks (spatial and spectral)
    • Translation of (learning) problems in graph-based form
    • Explainability of graph neural networks
  • Staff page

Human-in-the-loop

  • Research topics:
    • Active learning with multiple uncertain sources of knowledge
    • Active learning with alternative query types
    • Learning with noisy labels
    • Learning from information beyond labels
  • Employee side
  • Research topics:
    • Active continuous learning
    • Deep active learning
  • Staff page
  • Research topics:
    • Active learning for deep object detection
    • Active learning in deep learning
    • Interaction between humans and learning machines
  • Staff page
  • Research topics:
    • Stream-based active learning
    • Stream/online learning
    • Active learning
  • Staff page
  • Research Topics:
    • Data Annotation and Evaluation Workflows
  • Staff page

Novelty Detection

  • Research Topics:
    • Anomaly Detection in Heterogeneous Sensor Data
  • Staff page
  • Research topics:
    • Renewable energy forecasting and anomaly detection
  • Staff page

Transfer Learning

  • Research topics:
    • Multi-task learning and transfer learning
  • Staff page
  • Research topics:
    • Transfer learning and multi-task learning
  • Staff page

Uncertainty & Probabilistic Models

  • Research topics:
    • Predictive monitoring and analysis
  • Staff page
  • Research topics:
    • Probabilistic prediction
  • Staff page
  • Research topics:
    • Uncertainty modeling in deep learning (classification & object detection)
  • Staff page
  • Research Topics:
    • Sample Selection for Data Acquisition
  • Staff page