Naourez Benhadj | Deep Learning | Excellence in Research

Prof. Naourez Benhadj | Deep Learning | Excellence in Research

Associate Professor | Ecole Nationale d’Ingénieurs de Sfax | Tunisian

Dr. Naourez Benhadj is a researcher at the Ecole Nationale d’Ingénieurs de Sfax (ENIS), Tunisia, specializing in electric machines, PMSM design, hybrid/electric vehicle energy management, and intelligent optimization techniques. With 32 scientific publications, 243 citations, and an h-index of 9, he has contributed significantly to fault detection, finite-element modeling, and advanced optimization algorithms, including recent work on transformer-based solar power prediction and PMSM design using chaotic PSO. Collaborating with over 30 international co-authors, his research supports sustainable mobility, smart energy systems, and high-efficiency electric transportation, fostering technological advancement and environmental impact on a global scale.

 

Citation Metrics (Scopus)

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Citations
243

Documents
32

h-index
9

🟦 Citations 🟥 Documents 🟩 h-index

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Featured Publications


Comparison of fuel consumption and emissions of two hybrid electric vehicle configurations.

-International Conference on Sciences and Techniques of Automatic Control and Computer Engineering. (2018) Cited By: 4

Design simulation and realization of solar battery charge controller using Arduino Uno..

-International Conference on Sciences and Techniques of Automatic Control and Computer Engineering . (2017) Cited By: 21

Torque ripple and harmonic density current study in induction motor: Two rotor slot shapes.

– International Review on Modelling and Simulations.(2007). Cited By: 5

Thermal modeling of permanent magnet motor with finite element method.

– International Conference on Sciences and Techniques of Automatic Control and Computer Engineering. (2014). Cited By: 5

Ms. Feride Secil Yildirim | Deep Learning | Best Researcher Award

Ms. Feride Secil Yildirim | Deep Learning | Best Researcher Award

Feride Secil Yildirim at Karadeniz Technical University, Turkey

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Summary

Passionate about Geomatics Engineering, Ms. Feride Secil Yildirim is a PhD student at Karadeniz Technical University, specializing in photogrammetry and advanced deep learning techniques.

Education

  • Bachelor’s Degree (2017-2021): Geomatics Engineering, Karadeniz Technical University (Graduated with High Honors)
  • Master’s Degree (2022-2024): Geomatics Engineering, Karadeniz Technical University (Specialization in Photogrammetry)
  • Doctoral Studies (2024-Present): Geomatics Engineering, Karadeniz Technical University

💼 Professional Experience

Ms. Feride has completed four research projects and is currently involved in two ongoing projects, including a TÜBİTAK 1001/2024 initiative focused on developing a new algorithm for automatic adjustment of building boundary geometries from point cloud data. 

🔬 Research Interests

Her primary research interests encompass deep learning, image processing, and machine learning, with notable publications in Q1 journals, including her work on “FwSVM-Net: A Novel Deep Learning-Based Automatic Building Extraction from Aerial Images.” 🔍

 

Publication

FwSVM-Net: A novel deep learning-based automatic building extraction from aerial images

  • Authors: Feride Secil Yildirim, Fevzi Karsli, Murat Bahadir, Merve Yildirim
  • Journal: Journal of Building Engineering
  • Year: 2024

Dr. Shivanshu Shrivastava | Deep Learning | Best Researcher Award

Dr. Shivanshu Shrivastava, Deep Learning, Best Researcher Award

Doctorate at Rajiv Gandhi Institute of Petroleum Technology, India

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🌍 Academic Background:

Dr. Shivanshu Shrivastava is an Assistant Professor in the Department of Electrical & Electronics Engineering at Rajiv Gandhi Institute of Petroleum Technology (RGIPT), Amethi, Uttar Pradesh, India. He has been contributing to the field of electrical and electronics engineering with a focus on artificial intelligence and communications since September 2021.

🎓 Education:

Dr. Shrivastava earned his Ph.D. from IIT Guwahati in August 2017, specializing in Wireless Communication with a thesis on “Security Issues in Cognitive Radios,” under the guidance of Prof. A. Rajesh and Prof. P. K. Bora. He completed his Postdoctoral Fellowships at Shenzhen University, China, and IIT Kanpur from August 2017 to December 2020, focusing on “Artificial Intelligence and Deep Learning Applications in 5G Communications” under Prof. Bin Chen. He holds a Bachelor of Engineering degree in Electronics and Telecommunication Engineering from CSVTU, Bhilai, with a CPI of 8.13/10.

💼 Work Experience:

Before joining RGIPT, Dr. Shrivastava worked as a Postdoctoral Fellow at Shenzhen University from January 2019 to December 2020 and as a SERB-NPDF at IIT Kanpur from August 2017 to October 2018. His current role involves advancing research in deep learning and AI applications in communications.

🔬 Research Areas:

His research interests encompass artificial intelligence and deep learning applications in communications, cognitive radio systems, wireless communications, visible light communications (VLC), and security issues in cognitive radios.

📝 Research Experience:

At RGIPT, Dr. Shrivastava leads research on deep learning and AI applications in wireless communication. His previous projects include optimizing achievable rates in hybrid RF/VLC systems and designing energy-efficient hybrid RF/VLC systems for 5G communications. He has supervised Ph.D. students and undergraduate project students in these areas.

🏆 Honors, Awards, and Memberships:

Dr. Shrivastava has received the International Travel Support (ITS) from SERB for attending the IEEE ICCCAS conference in Xiamen, China, and the Best Teacher Award from Union Bank of India at RGIPT. He was also honored with postdoctoral fellowships from Shenzhen University and IIT Kanpur.

📖 Publications:

A lightweight group-based SDN-driven encryption protocol for smart home IoT devices
  • Authors: Raza, A., Khan, S., Shrivastava, S., Wu, K., Wang, L.
  • Journal: Computer Networks
  • Year: 2024
Collision Penalty-Based Defense Against Collusion Attacks in Cognitive Radio Enabled Smart Devices
  • Authors: Shrivastava, S., John, S., Rajesh, A., Bora, P.K.
  • Journal: IEEE Transactions on Consumer Electronics
  • Year: 2024
Transfer learning for resource allotment in dynamic hybrid WiFi/LiFi communication systems
  • Authors: Verma, T., Shrivastava, S., Dwivedi, U.D., Kothari, D.P.
  • Journal: Optics Communications
  • Year: 2023
Asset Allotment in Hybrid RF/VLC Communication in the 400-700 THz Band
  • Authors: Shrivastava, S., Agarwal, S., Chen, B.
  • Journal: Terahertz Wireless Communication Components and System Technologies
  • Year: 2022
A survey on security issues in cognitive radio based cooperative sensing
  • Authors: Shrivastava, S., Rajesh, A., Bora, P.K., Lin, X., Wang, H.
  • Journal: IET Communications
  • Year: 2021