Ms. Nooshin Nemati | Computer Science | Best Researcher Award

Ankara University, Turkey

Dr. Nooshin Nemati is a dedicated researcher in the fields of Artificial Intelligence, Deep Learning, and Medical Image Processing, currently pursuing her PhD in Computer Engineering at Ankara University, where she also contributes to multiple AI-based cancer detection projects. She holds a Master’s degree in Electrical and Electronics Engineering from Yuzuncu Yıl University and a Bachelor’s from Qazvin Azad University.

Profile:

• Scopus
• Google Scholar 

Educational Background:

Nooshin Nemati is currently a PhD candidate in Computer Engineering at Ankara University. She earned her Master’s degree in Electrical and Electronics Engineering from Yuzuncu Yıl University with a completed her undergraduate studies at Qazvin Azad University in Iran.

Research Areas:

Her main research interests lie in Artificial Intelligence, Deep Learning, Medical Image Processing, and Computer Vision, particularly applied to cancer detection in histopathology images. She focuses on segmentation, classification, and detection tasks using advanced deep learning frameworks.

Projects and Contributions:

She has actively contributed to significant research initiatives such as the TUBITAK 1001 Project, focused on deep learning methodologies for breast cancer detection, and the BAP Project, which deals with cancer region detection in histopathology images. She has also been involved in the development of important datasets such as NuSeC and MiDeSeC, aimed at supporting machine learning in medical imaging. In addition, she has applied her technical skills in software development projects including system analysis and automation tools for banks.

Technical Skills:

Nooshin is proficient in AI, Machine Learning, Deep Learning, and programming frameworks such as ASP.NET and WordPress. She also holds certifications like Network+ and CCNA, showcasing her broad technical competence.

Citation Metrics:

• Total Citations: 75

• Citations Since 2020: 71

• h-index: 6

• h-index Since 2020: 5

• i10-index: 3

• i10-index Since 2020: 3

Publication Top Notes:

• An imbalance-aware nuclei segmentation methodology for H&E stained histopathology images
  2023
  Citations: 22

• Detection of colorectal cancer with vision transformers
  2022
  Citations: 11

• Effect of color normalization on nuclei segmentation problem in H&E stained histopathology images
  2022
  Citations: 10

• A hybridized deep learning methodology for mitosis detection and classification from histopathology images
  2023
  Citations: 8

• CompSegNet: An enhanced U-shaped architecture for nuclei segmentation in H&E histopathology images
  2024
  Citations: 7