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.

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

Profiles

Orcid

Research Gate

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