Hemlata Sharma

Dr Hemlata Sharma

Lecturer in Digital Analytics and Technology


Summary

I have more than a decade (14+ years) of experience in Industry and Academia altogether. I have done PhD in Computer Science Engineering from Banasthali Vidyapith, Rajasthan in 2019.  My research interest area includes IOT, Artificial Intelligence, Machine Learning, Data Science, Text mining and NLP.  I have published and presented research papers in various National/International Journals and Conferences.  I have been invited as a resource person for various Management/Faculty development Programs and expert talks on topics like Machine Learning, Visualization using Tableau, Industry 4.o etc.    

 

Teaching

Department of Computing

College of Business, Technology and Engineering

Publications

Journal articles

Nandini, Y.V., Lakshmi, T.J., Enduri, M.K., & Sharma, H. (2024). Link Prediction in Complex Networks Using Average Centrality-Based Similarity Score. Entropy, 26 (6). http://doi.org/10.3390/e26060433

Nandini, Y.V., Tangirala, J.L., Enduri, M.K., Sharma, H., & Ahmad, M.W. (2024). Extending Graph-Based LP Techniques for Enhanced Insights Into Complex Hypergraph Networks. IEEE Access, 12, 51208-51222. http://doi.org/10.1109/access.2024.3385320

Ogunleye, B., Zakariyyah, K., Ajao, O., Olayinka, O., & Sharma, H. (2024). Higher education assessment practice in the era of generative AI tools. Journal of Applied Learning & Teaching, 7 (1). http://doi.org/10.37074/jalt.2024.7.1.28

Sharma, H., Andhalkar, A., Ajao, O., & Ogunleye, B. (2024). Analysing the Influence of Macroeconomic Factors on Credit Risk in the UK Banking Sector. Analytics, 3 (1), 63-83. http://doi.org/10.3390/analytics3010005

Sharma, H., Harsora, H., & Ogunleye, B. (2024). An Optimal House Price Prediction Algorithm: XGBoost. Analytics, 3 (1), 30-45. http://doi.org/10.3390/analytics3010003

Tokala, S., Enduri, M.K., Tangirala, J.L., & Sharma, H. (2023). Community-Based Matrix Factorization (CBMF) Approach for Enhancing Quality of Recommendations. Entropy, 25 (9). http://doi.org/10.3390/e25091360

Khari, M., González Crespo, R., & Sharma, H. (2023). Guest editorial of the special issue ‘human-centric, decentralised, and hyper automated cyber-physical systems’. Journal of Control and Decision, 10 (1), 1-2. http://doi.org/10.1080/23307706.2022.2145059

Ogunleye, B., Zakariyyah, K.I., Ajao, O., Olayinka, O., & Sharma, H. (n.d.). A Systematic Review of Generative AI for Teaching and Learning Practice. Education Sciences, 14 (6), 636. http://doi.org/10.3390/educsci14060636

Conference papers

Sybol, S.S., Srivastava, S., & Sharma, H. (2023). Soft Computing Approach for Student Dropouts in Education System. In Soft Computing for Problem Solving, (pp. 325-335). Springer Nature Singapore: http://doi.org/10.1007/978-981-19-6525-8_25

Sharma, H., & Chug, A. (2015). Dynamic metrics are superior than static metrics in maintainability prediction: An empirical case study. 2015 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions). http://doi.org/10.1109/icrito.2015.7359354

Book chapters

Sharma, H., Srivastava, S., & Gupta, V. (2023). Application and challenges of optimization in Internet of Things (IoT). In Nature-Inspired Optimization Algorithms and Soft Computing: Methods, Technology and Applications for IoTs, Smart Cities, Healthcare and Industrial Automation. (pp. 147-172).

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