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Electrical Engineering

Master´s programmes

Master's thesis projects

Electrical Engineering

Master's thesis projects

The diploma thesis work may be conducted within one of our research divisions, or within a company.
General guidelines, forms and instructions for Master's thesis

Interested in our student projects?
See our upcoming Master´s thesis presentations at Electrical Engineering

Available projects

At the department

(181022) Vienna rectifier for wind turbine
(181022) Well2Wheel – generating electricity of fossil fuels or sue fossil fuels in a vehicle
(181022) PCB Design of a Single Star Cascaded H-bridge Multilevel Inverter for Vehicle Traction Applications
(181022) High-Voltage wind turbine with direct in-slot cooling
(181022) Control of a Single Star Cascaded H-bridge Multilevel Inverter for Vehicle Traction Applications
(181022) 100 % solar energy
(181022) 100 % renewable energy

(181025) Automatic assessment of cardiac ultrasound images with deep learning

(181026) Design and integration of an open-source human intent-recognition system for safety-critical human-machine interactions and shared control

(181026) Intelligent control of electrified vehicles

(181026) Optimal control of a hybrid electric heavy-duty vehicle for real-driving emission compliance

(181026) Modeling and parameter identification of soft objects

(181031) Parametric spectral estimation using convex optimization

(181105) Microwave imaging system based on software defined radio technology

(181126) Control of a DAB for a dc-network implementation

(181129) Deep learning for pituitary gland tumor analysis from MR images

(181129) Machine learning for reconstructing hyper-dimensional magnetic resonance spectra of large biomolecules

(181206) Active inference of formal models using simulations

(190424) Stochastic geometry analysis of vehicular networks near intersections

At companies

(181101) A model library for operating cycle simulation of longitudinal dynamics and transport efficiency

(181108) Feasible DC voltage levels in households

(181108) Characterization of insulation material for high voltage DC transformer application

(181108) Feasible DC voltage levels in households

(181115) Real-time electric vehicle routing

(181115) Using collaborative robots and machine learning based on synthetic data for dynamic bin picking

(181115) Machine learning using synthetic data for dynamic quality inspection

(181119) Analysis of integrated access and backhaul (IAB) in future 5G systems

(181122) Road user classification using deep learning on images and 3D data

(181122) 3D stereo vision and tracking - focus on handling of occlusion and multi-object tracking

(181122) 3D stereo vision with wide FOV, e.g. using fish eye optics

(181122) Detection and analysis of traffic conflicts using tracking data

(181214) Collision avoidance by steering and braking interventions

(181214) Driver monitoring camera-based collision avoidance algorithms

(181214) Driver monitoring camera-based threat awareness for collision avoidance

(181220) Hybrid model-based model-free reinforcement learning for robotics manipulation

(181220) Online planning based reinforcement learning for robotics manipulation

(181221) Outlier analysis/classification based on data quality

(181221) Automatic coupling/decoupling of i-dolly (VERA auto coupling) used for local distributions

(181221) GPS-based path-following control of i-dolly (VERA auto coupling) used for local distributions

(190107) Automation of dataset generation for detailed object identification

(190109) Machine learning for prediction of renovation potential and energy efficiency measures in the building stock

(190211) Artificial intelligence by means of deep learning for radar-based road-surface monitoring

(190319) Capturing, extracting and analyzing text from video in real driving conditions

Published: Tue 14 Aug 2012. Modified: Wed 24 Apr 2019

Apply for Challenge Lab

Apply for Challenge Lab

Master’s students from all disciplines are invited to apply to Challenge Lab - to take on the planet's biggest challenges together with industry, government and academia.