Jayakumar Sadhasivam

  Educator – Researcher – Coder

About Me

Passinate Educator

Jayakumar Sadhasivam is an Associate Professor Grade 1 at Vellore Institute of Technology (VIT) in the School of Computer Science and Engineering (SCOPE).

Jayakumar’s areas of expertise include Open Source Programming, Network Security, Storage Technologies, and Machine Learning. His research interests are in the use of technology in education and developing open-source software that takes into consideration the unique needs of learners. He received his Ph.D. in Information Technology from the Vellore Institute of Technology (VIT).

Jayakumar has been a volunteer at Mozilla. He is contributing to various projects in Mozilla few of them are SUMO (Support Mozilla), QA (Quality Assurance), l10n (Localization), WebMaker, Bugzilla, and OpenBadges.

 

Students Handled

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in Course
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as a Mentor

Portfolio

Courses Handled
  • Problem Solving and Programming
  • Open Source Programming
  • Internet and Web Programming
  • Web Technologies
  • Web Design Techniques
  • Blockchain and Cryptocurrency Technologies
  • Digital Forensics
  • Malware Analysis
  • Storage System Management
  • Storage Technologies
  • Reverse Engineering
  • Database Management Systems
  • Software Security
  • Network and Information Security
  • Principles of User Interface Design
  • Software Engineering
  • Software Engineering Process, Tools and Methods
  • Software Project Management
  • Software Development
  • E-Commerce
Recent Publications
  • J. Sadhasivam, S. Jayavel, and A. Rathore, “Survey of genetic algorithm approach in machine learning,” SSRG Int. J. Eng. Trends Technol., vol. 68, no. 2, 2020, doi: 10.14445/22315381/IJETT-V68I2P218S.
  • J. Sadhasivam and R. B. Kalivaradhan, “An empirical comparison of supervised learning algorithms and hybrid WDBN algorithm for MOOC courses,” J. Ambient Intell. Humaniz. Comput., 2019, doi: 10.1007/s12652-019-01190-9.
  • S. Basheer, S. Mariyam Aysha Bivi, S. Jayakumar, A. Rathore, and B. Jeyakumar, “Machine learning based classification of cervical cancer using K-Nearest neighbour, Random Forest and Multilayer Perceptron algorithms,” J. Comput. Theor. Nanosci., vol. 16, no. 5–6, 2019, doi: 10.1166/jctn.2019.7925.
  • S. Basheer, N. Sampath, J. Sadhasivam, R. Ilampirai, R. Ramya Bharathi, and V. Ilakkiya, “Healthcare android application,” J. Comput. Theor. Nanosci., vol. 16, no. 5–6, 2019, doi: 10.1166/jctn.2019.7911.
  • N. Sampath, J. Sadhasivam, R. Raj Kumar, M. Sathish Kumar, B. Jeyakumar, and P. V Praveensundar, “Analyzing financial data and mutual funds recommendation by using big data analytics,” J. Comput. Theor. Nanosci., vol. 16, no. 5–6, pp. 2414–2418, 2019, doi: 10.1166/jctn.2019.7910.
  • J. Sadhasivam, S. Jayavel, A. Rathore, A. P. Singh, A. Singh, and J. Cynthia, “Work with streaming data using twitter API to build a job portal,” Int. J. Recent Technol. Eng., vol. 8, no. 2 Special Issue 8, 2019, doi: 10.35940/ijrte.B1009.0882S819.
  • J. Sadhasivam, R. B. Kalivaradhan, and S. Jayavel, “Survey of various algorithms used in twitter for sentiment analysis,” J. Crit. Rev., vol. 6, no. 6, 2019, doi: 10.31838/jcr.06.06.69.
  • J. Sadhasivam and R. B. Kalivaradhan, “Sentiment analysis of Amazon products using ensemble machine learning algorithm,” Int. J. Math. Eng. Manag. Sci., vol. 4, no. 2, 2019.
My Favorite No-Code
  • Notion
  • Airtable
  • Webflow
  • WordPress
  • Typeform
  • Carrd
  • Zapier

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