Jasmin Aghassi‐Hagmann

Papers

Total Citations

H-Index

About

Jasmin Aghassi‐Hagmann is a pioneering researcher at the intersection of printed electronics and neuromorphic computing. Her work focuses on developing inkjet-printed electrolyte-gated field-effect transistors (EGFETs) for low-power, flexible electronic systems. Her major contributions include the realization and training of the first inverter-based printed neuromorphic computing system (2021, 18 citations), which enables adaptive, brain-inspired computation on soft substrates for applications in soft robotics, wearables, and IoT. She has also advanced materials discovery through automated X-ray diffraction analysis (2023, 8 citations), accelerating the identification of novel materials for energy-efficient electronics and batteries. Additionally, her work on crossover-aware placement and routing for inkjet-printed circuits (2020, 5 citations) addresses critical design challenges in fabricating functional printed electronics. Aghassi‐Hagmann’s research uniquely bridges materials science, circuit design, and machine learning, demonstrating that printed electronics can achieve complex computational tasks. Her achievements highlight the potential of low-cost, flexible, and on-demand fabrication for next-generation smart systems, making her a leading figure in the field of printed neuromorphic hardware.