Electrical Engineering Assistant Professor

Curriculum Vitae

Dr. Mohamed Salah SALHI

Email: ********.*****@****.***.**

Mobil: +216-********

Summary:

• Profile: Male. 59 years. Married

• Nationality: Tunisia

• Current location: El Omrane Superior, Tunis

• Current position : A. Professor-HDR

• Company: University of Carthage

• Research Laboratory: LR-SITI, National Engineering School of Tunis ENIT Work experience:

2011---2024 A. Professor at University of Carthage, Tunisia Specialty: Electronics and Signal processing.

1997---2011 Engineer Senior trainer at Vocational Training, Tunisia 1993---1997 Engineer Technical Director, industrial company MIG-SA, Tunisia Education:

HDR [Electrical Engineering, 2024]

Doctorate [Electrical Engineering, 2012]

Master degree [Automation and Signal Processing, 2006]

Engineer diploma [Electromechanical, 1993]

At Campus El Manar university, National Engineering School of Tunis, Tunisia. IT Skills:

Microsoft office, Matlab, Python, Arduino, C++, VHDL and Verilog Languages:

• Arabic Native

• English Fluent

• French Fluent

Main research topics:

1. Speech processing and voice control

Contribute to voice authentication

Enhance voice control of robots

2. Analysis of industrial processes signals

Anomaly detection using recognition tools such as RSOM and Evolutionary RSOM

Contribute to SCADA anomaly detection using SOM-Map-Reduce for Data aggregation and Machine learning

Contribute to WSN approach for anomaly detection using Computational intelligent sensor nodes, Deep learning, IoT, M2M 3. Embedded implementation of detection and recognition tools

Optimization and acceleration on puce of recognition tool algorithms Main recent publications:

1. Mohamed Salah Salhi, Ezzeddine touti, Faouzi Benzarti, Zied Laachiri:

“Computational Sensor Nodes Optimization for Smart Anomaly Detection applied to Wind Energy”, Renewable Energy Focus-Elsevier, September 2023.

Clarivate analytics, impact factor: 4,8.

Link: https://doi.org/10.1016/j.ref.2023.100489

2. Mohamed Salah Salhi, Manel Salhi, Ezzeddine Touti, Faouzi Benzarti:

“On the Use of Wireless Sensor Nodes for Agricultural Smart Fault Detection”, Wireless Personal Communications-Springer Nature, January 2024.

Clarivate analytics, impact factor: 2, 2.

Link: https://doi.org/10.1007/s11277-024-10889-8

3. Mohamed Salah Salhi, Manel Salhi, Ezzeddine Touti, Faouzi Benzarti:

“Artificial Intelligence Optimization for Forest Fire Risk Predicting applied to Green Environment”, Applied Ecology and Environmental Research, September 2023. Clarivate analytics, impact factor: 0,816. 4. El Manaa Barhoumi, Mohamed Salah Salhi, Paul C. Okonkwo, Faouzi Bacha: “Techno-economic optimization of wind energy-based hydrogen refueling station case study Salalah city Oman”, International Journal of Hydrogen Energy-Elsevier, December 2022.

Clarivate analytics, impact factor: 5,861.

Selected as Best Paper by Elsevier with Award.

Link: https://doi.org/10.1016/j.ijhydene.2022.12.148 5. Mohamed Salah Salhi, El Manaa Barhoumi, Zied Lachiri: ‘Effectiveness of RSOM Neural Model in Detecting Industrial Anomalies’, Diagnostyka, 2022, 23(1), 2022106, Indexed Scopus. Link: https://doi.org/10.29354/diag/146213

6. Mohamed Salah Salhi, Said Kashoob, Zied Lachiri: ‘Progress in Smart Industrial Control applied to Renewable Energy System’, Energy Harvesting and Systems-Germany, 2022, Indexed Scopus.

Link: https://doi.org/10.1515/ehs-2021-0004

7. Mohamed Salah Salhi, Hamid Amiri: ‘Design on FPGA of an obstacle detection module over stereo image for robotic learning’, Indian Journal of Engineering (Method Article), 19(51), 2022. Indexed Scopus. 8. Mohamed Salah Salhi, Rahmouni M.H., Hamid amiri: ‘Evolutionary Deep- indicators Algorithm in Facial Recognition improvement over SoC’, International Journal of Advanced Science and Technology Vol. 29, No. 5,

(2020), pp. 5376 – 5387. Indexed Scopus.

Link: http://sersc.org/journals/index.php/IJAST/article/view/14051 Main recent supervisions:

1. Thesis of Najib Khalfaoui. Subject: Modeling of a neural system for detecting anomalies from industrial process signals. 2. Thesis of Mohamed Hedi Rahmouni. Subject: Modeling and implementation on embedded system of an automatic speaker recognition algorithm.

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