Key Research Areas

Magnetic Resonance Imaging, Signal Processing and Communication, RF hardware


Dr. Erwin Fuhrer graduated in 2019 from Karlsruhe Institute of Technology (KIT), Germany in the field of Biomedical engineering. His thesis research had the core focus on hardware development for Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) applications. After a year in industry he joined IIT Mandi as Visiting Assistant Professor. His core research sits at the intersection of the fields of Signal Processing, RF hardware development and biomedical diagnostics with a focus on NMR/MRI based diagnostic devices. This includes advancement of existing technologies as well as feasibility studies and development of novel technologies. In addition, he develops technologies for low-cost devices. He currently teaches the courses BE303 - Applied biostatistics, EE16 - Biomedical systems and is involved in the course IC231 - Measurement & Instrumentation.

Recent Publications

1. E. Fuhrer, M. Jouda, C. O. Klein, M. Wilhelm, and J. G. Korvink, "Gradient-Induced Mechanical Vibration of Neural Interfaces During MRI," IEEE Transactions on Biomedical Engineering, vol. 67, no. 3, pp. 915-923, Mar. 2020, doi: 10.1109/TBME.2019.2923693.
2. S. Nimbalkar et al., "Glassy carbon microelectrodes minimize induced voltages, mechanical vibrations, and artifacts in magnetic resonance imaging," Microsystems and Nanoengineering, vol. 5, no. 1, p. 61, Dec. 2019, doi: 10.1038/s41378-019-0106-x.
3. M. Jouda, E. Fuhrer, P. Silva, J. G. Korvink, and N. MacKinnon, "Automatic Adaptive Gain for Magnetic Resonance Sensitivity Enhancement," Analytical Chemistry, vol. 91, no. 3, pp. 2376-2383, Feb. 2019, doi: 10.1021/acs.analchem.8b05148.
4. J. B. Erhardt et al., "Should patients with brain implants undergo MRI?," Journal of Neural Engineering, vol. 15, no. 4, p. 041002, Aug. 2018, doi: 10.1088/1741-2552/aab4e4.
5. E. Fuhrer et al., "3D Carbon Scaffolds for Neural Stem Cell Culture and Magnetic Resonance Imaging," Advanced Healthcare Materials, vol. 1700915, p. 1700915, Dec. 2017, doi: 10.1002/adhm.201700915.

Course Taught

1. BE303 - Applied biostatistics
2. EE16 - Biomedical systems
3. IC231 - Measurement & Instrumentation