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Dr. Blessy Trencia Lincy

Dr Blessy Shepherd
Assistant Professor, Faculty of Mathematics and Data Science

Telephone: +971 4 6050172

Email: blessy.shepherd@eau.ac.ae

Dr Blessy Trencia Lincy. S. S has completed her Doctoral of Philosophy in the Faculty of Computer Science and Engineering, Vellore Institute of Technology (VIT), Master of Technology in Computer Science and Engineering from SRM University and Bachelor of Engineering in Computer Science and Engineering from DMI College of Engineering. Her doctoral thesis is about “Dimensionality Data Reduction and An Incremental Classification Model in Big Data”. Currently, she is working as an Assistant Professor in Emirates Aviation University, Dubai, UAE. She possesses 6 years of experience in both teaching as Assistant Professor and a Software Engineer. She has 15 publications in National, International journals, conferences and book chapters. Her research interests include Data Science, Big data analytics and Machine Learning.

  • PhD, Computer Science Specialization (Big Data Analytics), Vellore Institute of Technology, India, 2019.
  • Master of Technology (MTech), Computer Science and Engineering, SRM University, India, 2015
  • Bachelor of Engineering (B.E), Computer Science and Engineering, DMI College of Engineering, India, 2013
  • Business Intelligence and Big Data
  • Data Mining
  • Object Oriented Programming
  • Operating Systems
  • Software Quality Assurance and Testing
  • Software Design and Architecture
  • Data Science
  • Big Data
  • Machine Learning
  • Artificial Intelligence
    1. Blessy Trencia Lincy.S.S. Artificial Intelligence (AI) Driven Industrial Automation. Industry Automation: The Technologies, Platforms and Use Cases, 2024. 85, Link.
    2. Salah Uddin, M. ; Blessy Trencia Lincy. S. S, Hannah Al Ali; 2024. Exploratory Data Analysis and Prediction of Passenger Satisfaction with Airline services; IEEE, Link.
    3. Ali Hassan Alsayed Mohamad Alsayed Ali Al Moosawi, Sara Fahad Mohammad Hassan Alhammadi, Blessy Trencia Lincy. S. S, Hannah Al Ali, 2022. Aviation Sentimental Analysis and Multiclass Classification using Natural Language Processing Techniques. 4th International Aviation Management Conference, IAMC –2022, pp.220 – 227.
    4. Saif Alnaqbi, Abdalla Almail, Mirza Zaeem Baig, Blessy Trencia Lincy. S. S and Disha Kaur Phull, 2022.  Safety Incident Classification using Machine Learning Techniques in Airline Industry. 4th International Aviation Management Conference, IAMC – 2022, pp. 237 – 242.
    5. Blessy Trencia Lincy. S. S, Hannah Al Ali, Ahmad Abdulla Abdulaziz Mohd Majid, Omeer Arif Abdelbaqi Abdalla Alhammadi, Aysha Momen Yousuf Mohammed Aljassmy, Zindoga Mukandavire, 2022. Analysis of Flight Delay Data Using Different Machine Learning Algorithms." 2022 New Trends in Civil Aviation (NTCA). IEEE, 2022., pp. 57-62.
    6. Blessy Trencia Lincy.S.S. and Suresh Kumar, N. A Case study for an Incremental Classifier model in big data. International Journal of Cloud Computing. 8.3 (2019): 266-282.
    7. Blessy Trencia Lincy.S.S. and Suresh Kumar, N. An enhanced hybrid feature selection approach for high dimensional data processing. Journal of Testing and Evaluation, 47.6 (2019): 4161-4176.
    8. Blessy Trencia Lincy.S.S. and Suresh Kumar, N., 2018. MR-mRMR Feature Selection Approach with an Incremental Classifier Model in Big data. International Journal of Pharmaceutical Research, 10(4), pp.365-379.
    9. Blessy Trencia Lincy.S.S. and Suresh Kumar, N., 2018. An Effective Ensemble Model for Performance Optimization and Predictive Analytics in the Healthcare. Journal of Computational and Theoretical Nanoscience. 15(8), pp.2014–2022.
    10. Blessy Trencia Lincy.S.S. and Suresh Kumar, N., 2017. Enhanced Predictive Model for Healthcare Analytics : A Case Study on Diabetes Mellitus. Journal of Advanced Research in Dynamical and Control Systems, (4), pp.247–254.
    11. Dave, G. P., Sureshkumar, N., & Blessy Trencia Lincy, S. S. (2017, November). Performance evaluation of throughput computing workloads using multi-core processors and graphics processors. In Materials Science and Engineering Conference Series (Vol. 263, No. 4, p. 042101).
    12. Vyavahare, T., Tekade, D., Nayak, S., & Blessy Trencia Lincy, S. S. (2017, November). Enhanced rearrangement technique for secure data transmission: case study credit card process. In Materials Science and Engineering Conference Series (Vol. 263, No. 4, p. 042102).
    13. Blessy Trencia Lincy, S. S., Swarnalatha.P. (2016). A Comparative Study on MapReduce and Spark. In the International Journal of Control Theory and Applications, No.9 (2016) Issue No. :26 (2016), 67-72.
    14. Blessy Trencia Lincy, S. S., Swarnalatha.P., S.Prabu (2016, Sep). A Novel User-Based Recommendation System Using Mahout Framework., IJPT| Sep-2016 | Vol. 8 | Issue No.3 | 16222-16229.
    15. Blessy Trencia Lincy.S.S., GK, A. Hadoop MapReduce Framework: Performance Analysis in Business Intelligence. In International Journal of Computer Applications, 975, 8887.
    16. Blessy Trencia Lincy.S.S.,Varalakshmi.(2015). An Advanced Approach for Improving Performance in BigData Application Using Cache. In International Journal of Advanced and Innovative Research (IJAIR) 479 / Volume 4 Issue 3.
    17. Blessy Trencia Lincy.S.S. and Suresh Kumar, N., 2017. An enhanced pre-processing model for big data processing: A quality framework. Innovations in Green Energy and Healthcare Technologies (IGEHT), International Conference on IEEE, pp.1-7.
    18. Blessy Trencia Lincy.S.S. and Suresh Kumar, N., 2019. A Distributed Support Vector Machine under Apache Spark for Semi-Supervised Classification with Data Augmentation. Soft Computing and Signal Processing. Springer, Singapore. pp.395-405.
    19. Presented a paper “A Novel Method for Data Cleaning Process” in the National Conference on the “Recent Trends and Advancement in Information Technology” (NCIT 2014) held at Karpagam University, Coimbatore.
    20. Blessy Trencia Lincy.S.S. and Suresh Kumar, N., 2018. Transforming Healthcare via Big Data. Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications, pp.319-334.