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Parvin Ghaffarzadeh


Office: Wilberforce Building 207

PhD topic:  Accelerometer Wearable: A Pioneering Approach To Enhance Bone Health In Peri- And Post-Menopausal Women

Parvin joined the department as a Ph.D. Student and Teaching Assistant. Her research interests include AI-based clinical decision-making systems, medical engineering, medical image analysis, machine learning, deep learning, natural language processing (NLP), speech recognition, computer vision, programming, design, and development. She is currently working on using digital technology to bridge the gap between healthcare, medical engineering, and computer science.



  • Malihe Zeraatia, Hossein Abbasi, Parvin Ghaffarzadeh, Narendra Pal Singh Chauhan and Ghasem Sargazic “Application of artificial neural networks for corrosion behaviour of Ni-Zn electro phosphate coating on galvanized steel and gene expression programming models”, Frontiers of Materials Science, section Computational Materials Science (IF: 3.515). (2022)

  • Parvin Ghaffarzadeh, Mohammad H Nadimi, and Akbar Nabiollahi. “KMGEM: Data Clustering by Combination of K-Means and Grenade Explosion Algorithm”. International Journal of Computer Applications 147(14):21-29, August 2016.

  • Parvin Ghaffarzadeh. Samaneh Kouchaki. A new model to predict risk level of policyholders of Auto body insurance using Machine Learning techniques, Improved Neural Network and Deep Learning method. Parvin Ghaffarzadeh, Nadimi Mohammad H., Nabiollahi Akbar “RFM local model to cluster and develop strategies to predict the risk of auto body insurance customers, Case Study: Novin Insurance Company”, The 8th Iran Data Mining Conference IDCM 14, Tehran, Iran, 2014.

  • Erfane Norozi and Parvin Ghaffarzadeh, “A new approach to LSB images based on watermarking key secrets”, The National Conference on Interdisciplinary Research in Computer, Electronic, Mechanic, and Mechatronic Engineering, Ghazvin, Iran, 2016.

Useful links:


Principal Supervisor 


Dr Ali Dostan




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