Dr. Priya Porwal

About

Dr. Priya Porwal is an accomplished academician, researcher, and educator with over 7 years of experience in higher education. She is currently serving as an Assistant Professor in the field of Computer Science and Applications, where she is actively involved in teaching, research, curriculum development, and student mentoring. She has qualified the UGC-NET examination and recently completed her Ph.D. in Machine Learning, demonstrating her strong commitment to academic excellence and research.

Experience

• 7+ Years

Qualification

• Ph.D. in Computer Applications (Galgotias University)
• MCA (JSSATE, Noida).
• BSc (CSJM Kanpur University)

Award & Recognition

• Qualified UGC-NET

Research

Total: 160+ publications in SCI/SCIE/SCOPUS journals

Publications:

• P. Porwal, A. S. Singh, K. Thirunavukkarasu, "Modified U-Net and Convolutional Networks for Breast Cancer Segmentation and Classification with New Texture Descriptors," International Journal of Image and Graphics (2024), ISSN: 0219-4678, doi: https://doi.org/10.1142/S0219467826500385 (Scopus).
• P. Porwal, A. S. Singh, K. Thirunavukkarasu, "Image Classification for Breast Cancer Using a Modified Convolution Neural Network Architecture," International Journal on Recent and Innovation Trends in Computing and Communication, Auricle Global Society of Education and Research (2023), ISSN: 2321-8169, Vol. 11, Issue 9s, doi: https://doi.org/10.17762/ijritcc.v11i9s.747 (Scopus).
• P. Porwal, A. S. Singh, K. Thirunavukkarasu, S. Khan and M. R. Qader, "Machine Learning Algorithms based on Feature Selection Method used for the Prediction of Breast Cancer," 2021 International Conference on Data Analytics for Business and Industry (ICDABI), Sakheer, Bahrain, 2021, pp. 100–106, doi: 10.1109/ICDABI53623.2021.9655893 (Scopus).
• P. Porwal, T. K., A. N. Sinha and A. S. Singh, "Data Analysis and Detection of Coronavirus Disease using Convolution Neural Network," 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), Greater Noida, India, 2020, pp. 786–790, doi: 10.1109/ICACCCN51052.2020.9362763 (Scopus).
• P. Porwal, A. S. Singh, K. Thirunavukkarasu, "Review on Machine Learning Technique to Detect Breast Cancer," TEST Engineering & Management, 2020, ISSN: 0193-4120, pp. 11563–11568, Vol. 83 (Scopus).

Total: 160+ publications in SCI/SCIE/SCOPUS journals

Publications:

P. Porwal, A. S. Singh, K. Thirunavukkarasu, "Modified U-Net and Convolutional Networks for Breast Cancer Segmentation and Classification with New Texture Descriptors," International Journal of Image and Graphics (2024), ISSN: 0219-4678, doi: https://doi.org/10.1142/S0219467826500385 (Scopus).
P. Porwal, A. S. Singh, K. Thirunavukkarasu, "Image Classification for Breast Cancer Using a Modified Convolution Neural Network Architecture," International Journal on Recent and Innovation Trends in Computing and Communication, Auricle Global Society of Education and Research (2023), ISSN: 2321-8169, Vol. 11, Issue 9s, doi: https://doi.org/10.17762/ijritcc.v11i9s.747 (Scopus).
P. Porwal, A. S. Singh, K. Thirunavukkarasu, S. Khan and M. R. Qader, "Machine Learning Algorithms based on Feature Selection Method used for the Prediction of Breast Cancer," 2021 International Conference on Data Analytics for Business and Industry (ICDABI), Sakheer, Bahrain, 2021, pp. 100–106, doi: 10.1109/ICDABI53623.2021.9655893 (Scopus).
P. Porwal, T. K., A. N. Sinha and A. S. Singh, "Data Analysis and Detection of Coronavirus Disease using Convolution Neural Network," 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), Greater Noida, India, 2020, pp. 786–790, doi: 10.1109/ICACCCN51052.2020.9362763 (Scopus).
P. Porwal, A. S. Singh, K. Thirunavukkarasu, "Review on Machine Learning Technique to Detect Breast Cancer," TEST Engineering & Management, 2020, ISSN: 0193-4120, pp. 11563–11568, Vol. 83 (Scopus).

Certifications

• Participated in various Faculty Development Programs (FDPs), workshops, and training programs on Artificial Intelligence, Machine Learning, Data Science, and related emerging technologies.

Area of Interest

• Artificial Intelligence, Machine Learning, Deep Learning