Thomas Mueller

Papers

Total Citations

1,105

H-Index

About

Thomas Mueller is a leading figure in the fields of optoelectronics, 2D materials, and neuromorphic computing. His groundbreaking work bridges the gap between advanced materials and artificial intelligence, most notably through the development of ultrafast machine vision systems. In his landmark 2020 paper, cited over 1,100 times, Mueller introduced a neural network image sensor built from 2D materials, achieving real-time, energy-efficient visual processing that mimics the human retina. This innovation has profound implications for autonomous systems, robotics, and edge computing. Beyond this, Mueller has made seminal contributions to the study of graphene and transition metal dichalcogenides, exploring their unique optical and electronic properties for next-generation photodetectors and transistors. His research consistently demonstrates high impact, with multiple papers garnering hundreds of citations for advancing the understanding of light-matter interactions in atomically thin materials. Mueller’s work is not only technically rigorous but also visionary, positioning him as a key architect of the future of intelligent, low-power sensing technologies.