Dr. S. Pradeep Kumar Kenny

Assistant Professor, Department of Computer Science and Applications

Dr. S. Pradeep Kumar Kenny

Assistant Professor, Department of Computer Science and Applications

Biography

Dr. S. Pradeep Kumar Kenny

Assistant Professor of Data Science

Passionate educator with over 16 years of experience in Image Processing and Data Science, dedicated to inspiring the next generation of technology innovators. Committed to blending theory with practical applications for a transformative learning experience.

Area

Image Processing | Data Science

Qualification

M.Sc., M.Tech., Ph.d.,

Experience

16 years

Research Publications in International Journals

  • Pradeep Kumar Kenny, S. "Optimizing Space Complexity using Color Spaces in CBIR Systems for Medical Diagnosis." World News of Natural Sciences 30.2 (2020): 101-108.
  • S.Pradeep Kumar Kenny, Dr.S.P.Victor, “A Comparative Analysis of Single and Combination Features Extraction Techniques for Detecting Cervical Cancer Lesions”, ICTACT Journal on Image & Video Processing 6, no. 3 (2016), PP 1167-1173
  • S.Pradeep Kumar Kenny, et.al, “ ”, SYLWAN journal, Print: ISSN: 0039-7660, Vol. 158, Issue. 6, 2014, PP 423-429.
  • S.Pradeep Kumar Kenny, et.al, “Analysis of Multi Textural Features for Cervical Cancer Cell Staging”, SYLWAN journal, Print: ISSN: 0039-7660, Vol. 158, Issue. 6, 2014, PP 417-422.
  • S.Pradeep Kumar Kenny, et.al, “Creating a Optimal Set of Textural Features for Cervical Cancer Lesions Using Hierarchal Clustering Technique”, International Journal of Emerging Technology and Advanced Engineering, ISSN 2250–2459 (Online), Volume 4 Issue 6,  June 2014, PP 81-88.
  • S.Pradeep Kumar Kenny, et.al, “Determining Optimal Textural Features for Cervical Cancer lesions using the Gaussian Function”, International Journal of Emerging Technology and Advanced Engineering, ISSN 2250–2459 (Online), Volume 4 Issue 6,  June 2014, 89-96.
  • S.Pradeep Kumar Kenny, et.al, “Detecting Prominent Textural Features for Cervical Cancer Lesions Using Outlier Detection and Removal Techniques”, Journal of Emerging Trends in Computing and Information Sciences, E-ISSN 2218-6301/ ISSN 2079-8407, Vol. 5 No. 5, May 2014.
  • N .Krishnan, S.Allwin, S.Pradeep Kumar Kenny, "Feature set for indexing in content based image retrieval of cervical cyto images", International Journal of Imaging Science and Engineering, Volume 3 July 2009.

Research Publications in International Conferences

  • Bhuyan, Rupanka, Pradeep Kumar Kenny.,  et al. "Recent Advancements in Continuous Authentication Techniques for Mobile-Touchscreen-Based Devices." Intelligent and Cloud Computing. Springer, Singapore, 2021. 263-273.
  • Bhuyan, Pradeep Kumar Kenny., “Continuous Authentication of Tablet Users using Raw Swipe Characteristics”, 22nd Intelligent Systems and Design Applications (ISDA’22), Machine Intelligence Research Labs (MIR Labs) Scientific Network for Innovation and Research Excellence Auburn, Washington, USA. 12-13,2022.
  • S.Pradeep Kumar Kenny, et.al, “A Study on Campus Recruitment Management System”, Presented at the Global Multi-Track Conference SEMA held between November 18 and 27, 2022.
  • S.Pradeep Kumar Kenny, et.al, “Internet of Things (IoT) Based Energy Tracking and Bill Estimation System”, Presented at the Global Multi-Track Conference SEMA held between November 18 and 27, 2022.
  • Attended a two day International Conference on Application of SPSS and Statistical Data Analysis Organized by Eudoxia Research Centre 29th and 30th April 2020.
  • Recent Advancements in Continuous Authentication Techniques for Mobile Touch Screen Based Devices by Rupanka Bhuyan, Pradeep Kumar Kenny., et.al., presented in the International conference on Intelligent and cloud Computing (ICICC-2019 Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, India 16-17 December 2019)
  • S.Pradeep Kumar Kenny, et.al, “Fuzzy Optimal Threshold for Medical Images”, Proc of the International Conference on Design and Application of Structures, Drives, Communicational and Computing Systems (ICDASDC’2014)
  • S.Pradeep Kumar Kenny, et.al, “Analysis of Gradient Textural Features for Cervical Cancer Cell Staging”, Proc of the International Conference on Design and Application of Structures, Drives, Communicational and Computing Systems (ICDASDC’2014)
  • Balaji Thirupathi Kannan; Krishnaveni Krishnasamy and Pradeep Kumar Kenny S."A fuzzy optimal threshold technique for medical images", Proc. SPIE 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis, 83490O (January 11, 2012); doi:10.1117/12.920893; http://dx.doi.org/10.1117/12.920893.
  • S.Pradeep Kumar Kenny, et.al, “Feature set for extraction of cervical cyto images”, Computational Intelligence and Computing Research (ICCIC), 2010 IEEE.
  • S.Pradeep Kumar Kenny, et.al, “Classification of stages of maligancies using textron signatures of a cervical cyto image”, Computational Intelligence and Computing Research (ICCIC), 2010 IEEE.
  • S.Pradeep Kumar Kenny, et.al “Analysis for textural features in Nuclei of Cervical Cyto Images”, Computational Intelligence and Computing Research (ICCIC), 2010 IEEE.
  • K.Krishnaveni, S.Pradeep Kumar Kenny, "Multiscale Morphological Watershed Segmentation of Color Cervical Cytology", Proc of the International Conference on Computing Technologies (ICONCT'09), pp.  171-177

Research Publications in National Conference

  • S.Senthil Kumar, S.Pradeep Kumar Kenny, “Segmenting Cervical Cyto Images Using Double Fuzzy Threshold Values”, Proc of the National Conference on Information Science & Security (NISS’10), pp. 152-154

Professional Affiliations

  • Indian Society for Technical Education (Life Member)
  • Academic and Research Conclave (Life Member)

Academic Achievements

  • Participated in the 40th National Convention of Computer Society of India representing A.J College, Sivakasi in November 2005.

Caias

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Blog

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Alumni

Everything that I learned at CAIAS University really helped put me above the competition in the field of business management.

Alyssa Watson
BA Business Management