Pit Hofmann

Jan 13, 2025 | fis.tu-dresden.de | Pit Hofmann |Deutsche Telekom Chair |Juan Cabrera |Gunnar Schulte

The Internet of Things (IoT) has changed the way how we interact with our physical environment, enabling connectivity and communication between physical and virtual entities, e.g., for digital twin applications. However, as we step beyond the IoT, developing the Internet of Bio-Nano Things (IoBNT), where biological and nanoscale entities will be included in our communication networks, includes challenges as well as opportunities.

Jan 10, 2025 | fis.tu-dresden.de | Pit Hofmann |Deutsche Telekom Chair |Pengjie Zhou |Chan Byoung Chae

The convergence of microfluidics and Molecular Communication (MC) has garnered significant attention in the context of the emerging Internet of Bio-Nano Things (IoBNT) paradigm. Microfluidic systems offer unique capabilities for manipulating fluids at the microscale, enabling precise control over molecular interactions. Potential IoBNT applications of microfluidic MC lie in healthcare, environmental monitoring, and biotechnology.

Sep 1, 2023 | fis.tu-dresden.de | Jorge Gomez |Jorge Gómez |Deutsche Telekom Chair |Pit Hofmann |Frank H.P. Fitzek

Recent molecular communication (MC) research suggests machine learning (ML) models for symbol detection, avoiding the unfeasibility of end-to-end channel models. However, ML models are applied as black boxes, lacking proof of correctness of the underlying neural networks (NNs) to detect incoming symbols. This paper studies approaches to the explainability of NNs for symbol detection in MC channels.