Pooneh Mohaghegh

I recently completed my Ph.D. in Microsystems and Electronics at EPFL. Throughout my doctoral studies, I actively participated in various projects in collaboration with both an industry partner and applied science university, HE-Arc, located in Neuchatel. My primary research focus involved the design and development of real-time positioning systems (RTLS) that utilize Bluetooth Direction Finding to accurately position IoT devices within indoor environments.

During my master's study I was engaged in design and fabrication of Nano-bio sensors for cancer detection and drug monitoring.

I'm passionate about electronics and I would like to follow this path.

Ph.D Thesis: Real-time indoor positioning system design for IoT application, 2019-2023, EPFL, Switzerland

• Developed and created a real-time indoor positioning system based on Bluetooth Direction finding protocol for IoT application

2020–June 2023

A low-power, low-cost solution compatible with mobile devices

• Designed & prototyped a fast switch and antenna array, increasing the switching speed by x2 and the number of antennas by x24, using Altium Designer.
• Developed an estimation algorithm and implemented Machin learning methods k_Nearest Neighborhood (k_NN), Gaussian Mixture Models (GMM), reaching 95% accuracy in 2D angle estimation, using Python & C++, zephyr on Linux .
• Designed, developed, and prototyped a real-time hybrid access control system based on electromagnetic and vision system

2019–2020

• Developed & implemented merging algorithm for a robust, low power, and reliable access control system, using k-NN, and Global Nearest Neighborhood (GNN) algorithms through MQTT servers, achieving > 97% accuracy in un-authorized access detection.
• Designed, developed, and prototyped a smart card based on active RFID for positioning

2019–2020

• Designed & prototyped and characterized a low frequency, low power wake-up ASK receiver controlled with ESP32 and 3 electromagnetic coils as a transmitter, reaching <50cm precision for localization.
• Implement a neural network model to increase the position estimation precision by 85%.

Master Thesis: Application of Electrochemical Biosensors for Tracing Cancerous Cells Under the Incubation by Anti-Cancer Drugs, 2016–2019, University of Tehran, Iran

• Fabricate and Design electrochemical Cancer diagnosis sensors
• Fabricated and designed a real-time sensor based on carbon nanotubes (CNTs) on steel needles with an electrochemical method to diagnose breast cancerous margins, decreasing the detection time from below 1hr to a few seconds.
• Fabricated nanostructure sensors based on CNT, ZnO, and SiNW to trace electrochemical ionic charges of cancerous cells to investigate the effect of drug-treated cancerous cells of Breas and Prostate, decreasing detection time from several months to 10 days.

Doctorate of Philosophy, Microelectronics

2019-June 2023, Integrated Actuators Laboratory (LAI), École Polytechnique Fédéral Lausanne (EPFL), Switzerland

Master of Science , Micro and Nano Electronics

2016-2019, University of Tehran, Iran

Bachelor of Science , Electronics Engineering 

2011-2015, Shiraz University, Shiraz, Iran