Keyvan Farhang Razi
Fields of expertise
Biomedical Microelectronics
Digital Circuit design
RISC Microprocessors
Neural signal processing
Radio-Frequency analog Integrated circuits
Mixed-signal I.C design
RF Energy Harvesting
Devices and Materials
Digital Circuit design
RISC Microprocessors
Neural signal processing
Radio-Frequency analog Integrated circuits
Mixed-signal I.C design
RF Energy Harvesting
Devices and Materials
Biography
Keyvan Farhang Razi received his BSc and MSc degrees in Electrical Engineering from Amirkabir University of Technology in 2016 and 2019, respectively. His field of research and interest during his Bachelor of science education mainly covered the design of analog circuits using advanced HBT transistors and studying III-V compounds semiconductors as well as VLSI circuits design. In 2016, he joined the photonics Research Lab (PRL) at Amirkabir university of Technology to carry out his bachelor's diploma project under the supervision of Prof. Hassan Kaatuzian.Subsequently, he became a member of the RFIC laboratory at the Amirkabir University of Technology as a Master of science student under the supervision of Dr. Mohsen Moezzi in 2017. During his MSc program, he conducted a great deal of research and projects in designing Radio-frequency integrated circuits and low-power analog CMOS integrated circuits. Also, he designed an elaborated RF-DC converter for RF energy harvesting applications in his MSc diploma project.
He started his PhD education in the Electrical Engineering department (EDEE) of EPFL, Lausanne, Switzerland as a doctoral assistant in the Biomedical Neuromorphic Microelectronic System group (BNMS) supervised by Dr. Alexandre Schmid in October 2019. He is currently working toward an interdisciplinary project involving mixed-signal I.C design, signal processing, machine learning, and a RISC processor design for low-power implantable biomedical applications. His PhD thesis concerns designing a closed-loop epileptic seizure control implant. The ultimate goal of this project is to provide autonomy and improve the quality of life of epileptic patients who are drug-resistant and can be treated neither by existing pharmacotherapies nor by resection surgeries.
Publications
Selected publications
| Keyvan Farhang Razi and Alexandre Schmid IEEE LASCAS 2023 |
Programmable Seizure Detector Using a 32-bit RISC Processor for Implantable Medical Devices |
| Keyvan Farhang Razi, Alexandre Schmid IEEE Transactions on Biomedical Circuits and Systems |
Epileptic Seizure Detection with Patient-Specific Feature and Channel Selection for Low-power Applications |
| Keyvan Farhang Razi, Alexandre Schmid IEEE EMBC 2021 |
Two-stage Hardware-Friendly Epileptic Seizure Detection Method with a Dynamic Feature extraction |
| Keyvan Farhang Razi, Mohammad Javad Karimi, Catherine Dehollain, Alexandre Schmid |
System-Level Modeling of a Safe Autonomous Closed-loop Epileptic Seizure Control Implant |
| Keyvan Farhang Razi and Alexandre Schmid 2022 29th IEEE International Conference on Electronics, Circuits and Systems (ICECS) |
Computation Complexity Reduction Technique for Accurate Seizure Detection Implants |
| Keyvan Farhang Razi, Mohammad Javad Karimi, Catherine Dehollain, Alexandre Schmid 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS) |
Modeling and Analysis of a Wirelessly Powered Closed-Loop Implant for Epilepsy |
| Keyvan Farhang Razi, Raquel Ramos Garcia and Alexandre Schmid 2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES) |
Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection |
| Keyvan Farhang Razi, Mohsen Moezzi |
A CMOS RF energy harvester with high PCE over a wide range of input power |