Meysam Mayahi

Researcher | Wireless Communications

Salary / Daily rate

Rennes, France

Freelance, open to permanent contract

Skills

Machine Learning

Languages

ArabicEnglishFrenchPersian

About me

Intro

PhD researcher specializing in wireless communications with 5+ years experience at leading institutions like IRISA and Orange. Expert in IoT protocols, energy-efficient networks, and algorithm design with proven track record in heterogeneous technology integration. Ready to deliver cutting-edge solutions for wireless networking challenges.

Links

Work experience

Research Assistant

IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires

Nov 2024 - Present

2 years

Rennes, France

Postdoctoral Researcher

Orange

Sep 2023 - Oct 2024

1 year 2 months

Rennes, France

Doctoral Researcher

Inria

Oct 2019 - Dec 2022

3 years 3 months

Lille, France

Intern

Centre national de la recherche scientifique

Oct 2018 - May 2019

8 months

Lille, France

I started my Internship at IRCICA, UCR CNRS 3380 on October 2018 under supervision of professor Chiara Buratti and co-supervision of Professor Laurent Clavier after I won the Tesi all'estero scholarship among more than 50 applicants. The idea was to study and examine the Cooperation and coexistence of heterogeneous technologies for IoT applications where the new protocol has to choose the best radio network for transmission in order to comply with the number of factors from MAC layer point of view. We had two possibilities for transmission : long-range (LoRaWAN )and short-range(IEEE 802.15.4) radio links with the possibility of transmitting over multi-hops link in order to expands its transmission range. We investigate the way to choose the efficient radio to send a common IoT traffic in scenarios such as smart cities, industry 4.0 and smart agriculture. The most important factors considered in this study were: energy consumption, latency, reliability, scalability and the packet length. From algorithm designing point of view, the new layer or sub-layer works between the data link layer and the network layer of the protocol stack and it derives the parameters values from two resources: the liabilities which tie the parameter value to the electromagnetic environment detected through regular CCA or ETX, and the requirements which is more application-dependant assumption. At the end the proposed algorithm will evaluate through fuzzy logic (which gives the protocol a level of flexibility from machine learning point of view) the required and the available parameters for each radio and choose the efficient one for transmission. Last but not least, I simulate the algorithm in two different environments: Contiki and MATLAB and tested the accuracy of the protocol by introducing input parameters from regular IoT applications such as smart cities, smart agriculture and M2M communication.


Education

University of Lille 1 Sciences and Technology

Doctor of Philosophy - PhD

2019 - 2022

4 years

Alma Mater Studiorum – Università di Bologna

Master's degree

2016 - 2019

4 years

ACECR Khouzestan

Bachelor's degree

2011 - 2014

4 years

Portfolio

Draft manuscript case study (not yet published) — 23 Dec 2025

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