Design Automation for Microfluidic Devices
Doctoral Theses
Over the years, many talented researchers have completed their doctoral studies at our chair. The following list provides an overview of their dissertations and reflects the breadth of research topics pursued within our group. This research often takes place in collaboration with partners from academia and industry.
Simulation of Microfluidic Devices at Multiple Levels of Abstraction
Deep Learning-based Radar Camera Fusion for Perception in Autonomous Driving
Explainable and Interpretable AI for Sensing Applications
Physical Design for Field-coupled Nanocomputing
Advancing Quantum Error Correction with Quantum Low-Density Parity-Check Codes
MQT Qudits, Simulation and Compilation for Mixed-Dimensional Quantum Computing
Supporting End Users: Methodologies and Software Tools to Develop Quantum Computing Solutions
Noise-Aware Quantum Circuit Simulation with Decision Diagrams
Design Automation Tools and Software for Quantum Computing
Stochastic Modeling and Machine Learning Techniques for Graphene-based Environmental Gas Sensors
Simulation and Design Automation Tools for Microfluidic Devices
Efficient Implementation of Quantum Circuit Simulation with Decision Diagrams
Improved System-on-Chip-Design-Automation for Industrial Requirements
Cost Estimation and Optimization of Hardware/Software Co-Designs Using Machine Learning
High Performance Simulation for Industrial Paint Shop Applications
Design Automation for Quantum Computing
For our current research visit our Research page.