معرفی
Jari Nurmi is a Full Professor at Tampere University's Faculty of Information Technology and Communication Sciences, Department of Electrical Engineering. With over 30 years of experience in academia and industry, he specializes in communications engineering, positioning technologies, embedded systems, and reconfigurable computing. His roles include Director of the national DELTA doctoral training network, head of the European Joint Doctorate A-WEAR program, and coordinator of APROPOS MSCA ITN. He has supervised 32 PhD dissertations and over 160 MSc theses.
His research focuses on embedded processor systems, reconfigurable computing, approximate computing, and positioning technologies (especially GNSS receiver architectures). He is actively involved in organizing international conferences like IEEE Nordic Circuits and Systems Conference and serves on editorial boards of three journals. His recent work includes advancements in neural network inference on FPGAs, 5G NR localization, and energy-efficient edge AI for autonomous systems.
Nurmi has been recognized for his contributions to conference organization and innovation. His publications span topics such as FPGA optimization, GNSS error modeling, and machine learning for healthcare applications. He leads initiatives like the EWOk dataset compression framework and the Hard SyDR benchmarking environment for GNSS algorithms.
