Dr Umme Salma M. MSc, PhD (Computer Science)

Dr. Umme Salma M is a Data Science Researcher,  Professor and Author. She has Published several articles in peer reviewed international journals, conferences and book chapters like IEEE, Springer, Taylor & Francis,  DeGruyters, InderScience and so on. Her area of research includes Medical Analytics, IoT, Natural Language Processing, Machine Learning and Artificial Intelligence. she is currently  rendering her service in CHRIST (Deemed to be University) as an assistant professor and is guiding three research scholars in Data Science towards their PhD. She is an author and scribes poems, quotes and stories in English, Kannada and Hindi languages across various genres.

International Journals

  1. Umme Salma M and Doreswamy. Hybrid BATGSA: A Meta Heuristic Model for the Classification of Breast Cancer Data, International Journal of Advanced Intelligence Paradigms (IJAIP), Inderscience, ISSN (Online) 1755-0394, ISSN (Print) 1755-0386 Vol.15 No.2, pp.207 – 227.
  2. Doreswamy and Umme Salma M. Reducing the feature space using constraint governed association rule mining. Journal of Intelligent Systems, De-Gruters, ISSN (Online) 2191-026X, ISSN (Print) 0334-1860, pp.139-152.

Book Chapter

    1. Diya C. R., Umme Salma M., and Chaitra R Beerannavar. A Case Study on Zonal Analysis of Cyber Crimes over a Decade in India. Taylor and Francis (In press)

    2. Umme Salma, M., Narayanamoorthy, S., Kureethara, J.V. (2023). Clustering Faculty Members for the Betterment of Research Outcomes: A Fuzzy Multi-criteria Decision-Making Approach in Team Formation. In Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain. Studies in Fuzziness and Soft Computing, vol 420. Springer, Singapore. https://doi.org/10.1007/978-981-19-4929-6_29

    3. Ummesalma, M., Subbaiah, R., and Narasegouda, S. A Spatio Temporal Model for the Analysis and Classification of Soil using IoT. In Cyber Physical IoT and Autonomous Systems in Industry 4.0, pp. 221-234, CRC Press, Boca Raton, 2021.

    4. Ummesalma, M., and Ann, K. A. Active Learning from an Imbalanced Dataset: A Study Conducted on the Depression, Anxiety, and Stress Dataset. In Handbook of Machine Learning for Computational Optimization(pp. 251-266). CRC Press, Boca Raton, 2021.

    5. Ummesalma, M., Subbaiah, R., and Narasegouda, S. A Decade Survey on Internet of Things in Agriculture. In Internet of Things (IoT), pp. 351-370, Springer, Cham, 2020.

    6. Ummesalma, M., and Sharma. Social, Medical, and Educational Applications of IoT to Assist Visually Impaired People. In Internet of Things for Healthcare Technologies, pp. 195-214. Springer, Singapore, 2020.

    7. Umme Salma, M., & Narasegouda, S. Agricultural IoT as a Disruptive Technology: Comparing Cases from the USA and India. In The Digitalization Conundrum in India(pp. 123-132). Springer, Singapore, 2020.

    8. Ummesalma M, Srinivas Narasegouda, and Anuraha N Patil. A Meta-Heuristic based Hybrid Predictive Model for Sensor Network Data. Computational intelligence in sensor networks, pp 167-186, Springer, Berlin, Heidelberg, 2018

    9. Srinivas Narasegouda, Ummesalma M, and Anuraha N Patil. Nature Inspired Algorithm Approach for the Development of an Energy Aware Model for Sensor Network. Computational intelligence in sensor networks, pp 55-77, Springer, Berlin, Heidelberg, 2018.

    10.  

International Conferences

  1. Umme salma and Najmusseher. Impact of Feature Selection Techniques For EEG-Based Seizure Classification. Springer (In press)
  2. Umme salma and Najmusseher. Classification Algorithms Used In The Study of EEG-Based Epileptic Seizure Detection. In 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC), 2021, pp. 1518-1521, IEEE, 5-7 October 2021.
  3. Ummesalma, M., and Yashiga, C. (2021, June). COLPOUSIT: a hybrid model for tourist place recommendation based on machine learning algorithms. In 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)(pp. 1743-1750). IEEE, 03-05 June 2021.
  4. Ummesalma M, and Raju, B. K. Demography-Based Hybrid Recommender System for Movie Recommendations. In Sustainable Advanced Computing(pp. 49-58). Springer, Singapore, 05-06 March 2021.
  5. Ummesalma, M., and Rajashekar, P. K. M. (2020, December). Constraint Governed Association Rule Mining for Identification of Strong SNPs to Classify Autism Data. In 2020 International Conference on Communication, Computing and Industry 4.0 (C2I4)(pp. 1-5). IEEE, 17 December 2020 .
  6. Shailaja, K. P., Manjunath, M., and Umme Salma M. Impact of Learning Functions on Prediction of Stock Data in Neural Network. In 2018 3rd International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS), pp. 82-86., IEEE, Bangalore 20-22 December 2018.
  7. Doreswamy and Umme Salma M. PSO based fast K-means algorithm for feature selection from high dimensional breast cancer data. In Proceedings 10th International Conference on intelligent systems and control (ISCO-2016), Coimbatore, 7-8 January, 2016,
  8. Doreswamy and Umme Salma M. BAT-ELM: A bio inspired model for prediction of breast cancer data. In Proceedings of International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT-2015), 501-506, IEEE, Davanagere, 29-31 October, 2015.
  9. Doreswamy and Umme Salma M. Fast Modular Artificial Neural Network for the Classifi- cation of Breast Cancer Data. In Proceedings of the Third International Symposium on Women in Computing and Informatics, pp. 66-72, ACM, 10-13 August 2015.