Pro­jects and Theses

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

Ag­ri­cul­ture

  • Research topics:
    • Precision farming
    • Deep learning with satellite imagery
  • Employee Site

 

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
  • Research topics:
    • Electricity forecasts for renewable energies and energy meteorology
  • 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:
    • Deep learning with satellite images
  • Employee Site
  • Research topics:
    • Accelerated topology optimization with deep generative models
  • 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
  • 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