Reza Ranjandish

• Low-power analog/digital/mixed-mode circuit design for wireless, biomedical, sensor, and RF applications.
• Low-power wireless data telemetry, wireless power transfer and battery charger for biomedical applications.
• Brain inspired computing and Machine Learning (ML) for biomedical applications.
• Low-power data compression architectures for biomedical applications.
• Smart wireless wearable electronics for health monitoring.

Ranjandish, R., & Schmid, A. (2019) A design methodology for charge-balanced stimulators based on anodic current variation monitoring. Analog Integrated Circuits and Signal Processing, pp.1-10.

Ranjandish, R., & Schmid, A. (2018). A Sub-µW/channel, 16-channel Seizure Detection and Signal Acquisition SoC Based on Multichannel Compressive Sensing. IEEE Transactions on Circuits and Systems II: Express Briefs.

Ranjandish, R., & Schmid, A. (2018, Nov).  A 4-Channel, 5.04 uW, 0.325 mm2, Parallel Neural Recording System Based on Orthogonal Sampling. In 2018 IEEE Asian Solid-State Circuits Conference (ASSCC 2018).

Ranjandish, R., & Schmid, A. (2018, Sep). An All Wireless, 16-Channel Epilepsy Control System with Sub-uW/Channel and Closed-Loop Stimulation Using a Switched-Capacitor-Based Active Charge Balancing Method. In 48th IEEE European Solid-State Circuits conference (ESSCIRC).

Ranjandish, R., & Shoaei, O. (2014, October). "A simple and precise charge balancing method for voltage mode stimulation." In 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings (pp. 376-379). IEEE.

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• Student travel grant award, ISSCC 2019, San Francisco, United States.
• Student travel grant award, ASSCC 2018, Tainan, Taiwan.
• Silver leaf award for the presented paper at PRIME 2016, Lisbon, Portugal.
• Ranked 2nd among 20 top master students in Circuits and Systems, University of Tehran, Iran.

• A wristband for healthcare monitoring and seizure detection (EPFL) 04-2019/11-2019

This project which was supported by Hasler Stiftung Foundation (50k CHF) was a 7.5 months’ project in which I had to implement one of my ideas for healthcare IoT as a Postdoctoral research fellow. In this project a wristband had to be designed using discrete components, to monitor and record different biosignals including heart rate, oxygen saturation of the blood, body temperature, etc. to obtain information for seizure detection.

Responsibilities:

1. System-level design of the wristband.
2. PCB design of the system.
3. Soldering the components.
4. Test and validate the modules.
5. Assembly and implementation of the final design using an ultra-low-power micro controller.

• Implantable Autonomous Wireless Closed-loop Bio-electronics for Epilepsy Control (EPFL)

03-2015/03-2019

This project which was supported by Swiss National Science Foundation (SNF) as four years of PhD study and doctoral assistantship. In this project I was supposed to implement an implantable low-power closed-loop stimulation system to detect seizures and stimulate the brain in order to stop the seizures.

Responsibilities:

1. Application Specific Integrated Circuit (ASIC) design of the system.
2. Design of the analog front-end.
3. Design of the digital signal processing circuit for seizure detection.
4. Design of the Electrical Stimulator (ES).
5. (Optional) Design of the wireless data communication, wireless power transfer and battery charger.

Results:

1. Several versions of low-power and low-noise amplifier were implemented and tested successfully.
2. Hard thresholding and light-weight Machine Learning circuits was implemented and tested successfully using 420 h of iEEG signals provided by Hospital University of Bern (Inselespital).
3. A new method for implementing multi-channel compressive sensing was tested successfully.
4. Several versions of Electrical Stimulator in voltage mode, current mode and charge mode were implemented and tested in vitro
5. Low-power and safe charge balancing methods were designed and implemented successfully.
6. A low-power narrow-band OOK transmitter for ISM 433 MHz and a low-power ASK-PWM receiver were implemented and tested successfully.
7. A novel design of a high-efficient battery charger was simulated successfully.

• Design of a low cost Polymerase chain reaction (PCR) device (Arka Fannavari Raya Co.)

12-2013/02-2015

This project which was a self-funded project was the preliminary idea for funding my startup namely Arka Fannavari Raya.

Responsibilities:

1. System-level design of the PCR system.
2. PCB design of the system.
3. Soldering the components.
4. Testing and validating the system.

Results:

1. The response of the system was fast for a temperature sweep from 25º to 100º Celsius.
2. The controller was stable and the settling of the system was fast.
3. A high-efficiency AC/DC converter was designed and the first prototype was completed.

Master Thesis Supervisions

• Sebastien Debenest, 2019, EPFL, Lightweight machine learning hardware implementation of seizure detection algorithms.
• Niederhauser Loïc, 2018, EPFL, Epilepsy Feature Extraction Using Support Vector Machine (SVM).

Master Semester Project Supervisions

• Emrick Sinitambirivoutin, 2019, EPFL, Lightweight machine learning hardware implementation of seizure detection algorithms.

Bachelor Thesis Supervisions

• Lucas Biotto, 2018, EPFL, Implantable multi-channel bio-electronics for epilepsy detection.

Internship Supervisions

• Ali Amidi, 2014, Universyty of Tehran, Iran.

• Project Management Institute (PMI) Member
• IEEE Member

• Farsi (Persian): Native
• English: Fluent
• French: A2
• German: A0

• Swimming
• Table Tennis
• Football
• Beach volley
• Tennis
• Hiking

• Nationality: Iranian
• Permit type: B
• Age: 31