Summary
Biography
Nur Ahmadi received the B.Eng. degree in electrical engineering from Bandung Institute of Technology (ITB), Indonesia, in 2011. Subsequently, he was awarded Monbusho/MEXT scholarship for pursuing M.Eng degree at the Department of Communication and Integrated Systems, Tokyo Institute of Technology, Japan. After graduated in 2013, he moved back to Indonesia and worked at the Microelectronics Centre, ITB for 2.5 years. In 2016, he joined the Next Generation Neural Interfaces (NGNI) Lab, within the Department of Electrical & Electronic Engineering and Centre for Bio-Inspired Technology, Imperial College London to pursue a Ph.D. degree funded by LPDP scholarship.
phd thesis topic
Neural Signal Processing and Decoding Methods for Intracortical Brain-Machine Interfaces
research interests
Digital signal processing, biomedical signal processing, artificial intelligence, machine learning, deep learning, digital IC/VLSI design, embedded system, system on chip, brain-machine interface, healthcare and neurotechnology
Publications
Journals
Ahmadi N, Adiono T, Purwarianti A, et al., 2022, Improved spike-based brain-machine interface using bayesian adaptive kernel smoother and deep learning, Ieee Access, Vol:10, ISSN:2169-3536, Pages:29341-29356
Ahmadi N, Constandinou T, Bouganis C, 2021, Inferring entire spiking activity from local field potentials, Scientific Reports, Vol:11, ISSN:2045-2322, Pages:1-13
Ahmadi N, Constandinou TG, Bouganis C-S, 2021, Robust and accurate decoding of hand kinematics from entire spiking activity using deep learning, Journal of Neural Engineering, Vol:18, ISSN:1741-2552, Pages:1-23
Ahmadi N, Constandinou T, Bouganis C-S, 2021, Impact of referencing scheme on decoding performance of LFP-based brain-machine interface, Journal of Neural Engineering, Vol:18, ISSN:1741-2552
Ahmadi N, Constandinou TG, Bouganis C-S, 2020, Robust and accurate decoding of hand kinematics from entire spiking activity using deep learning