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
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
Ahmadi N, Constandinou T, Bouganis C, 2018, Estimation of neuronal firing rate using Bayesian Adaptive Kernel Smoother (BAKS), Plos One, Vol:13, ISSN:1932-6203
et al., 2019, Towards a Distributed, Chronically-Implantable Neural Interface, IEEE/EMBS Conference on Neural Engineering (NER), Pages:1-6
Ahmadi N, Constandinou T, Bouganis C, 2019, Decoding Hand Kinematics from Local Field Potentials Using Long Short-Term Memory (LSTM) Network, 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER 2019), Pages:1-5
Ahmadi N, Constandinou TG, Bouganis C, Spike rate estimation using Bayesian Adaptive Kernel Smoother (BAKS) and its application to brain machine interfaces, 40th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE