Ahmad Reza Naghsh Nilchi | Deep Learning | Best Researcher Award

Prof. Ahmad Reza Naghsh Nilchi | Deep Learning | Best Researcher Award

Faculty Member | University of Isfahan | Iran

Prof. Ahmad Reza Naghsh-Nilchi is a distinguished researcher in computer vision, artificial intelligence, and medical image processing with a strong academic and professional background. He completed his PhD in Electrical and Computer Engineering at Michigan State University, where he specialized in digital image processing, and has since built an influential career in both academia and research. Over the years, he has served in multiple leadership positions including department chair, dean of research, and head of research laboratories, while also supervising numerous PhD and master’s students in advanced AI and imaging topics. His professional experience extends internationally through collaborations with leading institutions such as UC Irvine, University of Toronto, York University, and University of Ireland, contributing significantly to global research initiatives. His research interests span robust deep learning, adversarial defense, trustworthy AI, multimodal action recognition, image captioning, retinal analysis, and robot-camera pose estimation, reflecting both theoretical innovation and practical applications. He has published more than 70 papers in prestigious journals and conferences indexed by IEEE and Scopus, and his work has received more than 2,200 citations. His excellence has been recognized through multiple honors, including awards as University Researcher of the Year and Industrial Researcher of the Year. He possesses advanced research skills in AI model development, medical imaging, digital signal processing, and multimodal data analysis, complemented by editorial roles, conference organization, and active memberships in professional associations such as IEEE and ACM. His career demonstrates a commitment to advancing science, mentoring the next generation, and fostering impactful interdisciplinary collaborations. His Scopus output reflects international impact, with 1,319 citations by 1,214 documents, 65 published documents, and an h-index of 21.

Profile: Google Scholar | Scopus Profile | ORCID Profile

Featured Publications

Fathi, A., & Naghsh-Nilchi, A. R. (2012). Noise tolerant local binary pattern operator for efficient texture analysis. Pattern Recognition Letters, 33(9), 1093–1100.

Fathi, A., & Naghsh-Nilchi, A. R. (2012). Efficient image denoising method based on a new adaptive wavelet packet thresholding function. IEEE Transactions on Image Processing, 21(9), 3981–3990.

Fathi, A., & Naghsh-Nilchi, A. R. (2013). Automatic wavelet-based retinal blood vessels segmentation and vessel diameter estimation. Biomedical Signal Processing and Control, 8(1), 71–80.

Amirgholipour, S. K., & Ahmad, R. (2009). Robust digital image watermarking based on joint DWT-DCT. International Journal of Digital Content Technology and its Applications, 3(2), 42–48.*

Kasmani, S. A., & Naghsh-Nilchi, A. (2008). A new robust digital image watermarking technique based on joint DWT-DCT transformation. In 2008 Third International Conference on Convergence and Hybrid Information Technology (pp. 539–544). IEEE.

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

Profiles

Scopus

Google Scholar

🌍 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