• Natural Language Processing

• Data Mining/Text Mining

• Machine Learning

• Natural Language Processing

• Artificial Intelligence

• Programming in Java

• Database Management System

• PHP Programming

• Computer Graphics

• Android Programming

• Software Engineering

• Programming in Python

• Programming in C++

• Data Structures

• Operating System

• HTML, CSS

• Kumawat, H., Sharan, A., & Verma, S. (2025). Impact analysis of text representation on biomedical multi-label text classification with deep learning. Procedia Computer Science, 258, 3294–3304.
• Verma, S., Kumawat, H., Sharan, A., Hooda, S., & Verma, N. (2025). Unveiling biomedical insights: A semantic pipeline from document entities to knowledge graph analysis of hallmarks of cancer.Procedia Computer Science, 258, 2200–2209.
• Verma, S., Sharan, A., & Gautam, A.K. (2025). Correlating the hallmarks of cancer: A study using conditional dependency networks. In Artificial Intelligence in Oncology: Cancer Diagnosis and
Treatment.
• Verma, S., Sharan, A., & Malik, N. (2024). Efficient classification of hallmark of cancer using embedding-based support vector machine for multilabel text. New Generation Computing, 42(4), 685–714.
• Malik, N., Jindal, K., Verma, S., & Gupta, S. (2024). Metaverse dynamics: Exploring industry impacts and educational frontiers. Educational Perspectives on Digital Technologies in Modeling and
Management.
• Verma, S., Ahmad, O., & Sharan, A. (2024). Multilabel text classification in biomedical domain. In Text Mining Approaches for Biomedical Data (pp. 299–326).
• Verma, S., & Gupta, Y. (2024). Biomedical text data visualization. In Text Mining Approaches for Biomedical Data (pp. 105–114).
• Verma, S., & Sharan, A. (2024). Unveiling the biomarkers: Identifying key signatures for cancer hallmarks. EAI Endorsed Transactions on Pervasive Health & Technology, 10(1).
• Soni, G., Verma, S., Sharan, A., & Ahmad, O. (2023). BioBERT-based model for COVID-related named entity recognition. In International Conference on Advances in IoT and Security with AI (pp.
333–346).
• Verma, S., & Sharan, A. (2023). Incorporating semantics for text classification in biomedical
domain. Proceedings of the International Health Informatics Conference (IHIC 2022).
• Kamble, S., Saini, D.K.J., Kumar, V., Gautam, A.K., Verma, S., Tiwari, A., & Goyal, D. (2022). Detection and tracking of moving cloud services from video using saliency map model. Journal of
Discrete Mathematical Sciences and Cryptography, 25(4), 1083–1092.
• Kumar, S., Dubey, K.K., Gautam, A.K., Verma, S., Kumar, V., & Mamodiya, U. (2022). Detection of recurring vulnerabilities in computing services. Journal of Discrete Mathematical Sciences and
Cryptography, 25(4), 1063–1071.
• Malik, M., Kumar, M., Kumar, V., Gautam, A.K., Verma, S., Kumar, S., & Goyal, D. (2022). High level browser security in cloud computing services from cross site ing attacks. Journal of Discrete
Mathematical Sciences and Cryptography, 25(4), 1073–1081.
• Verma, S., Gautam, A.K., Gandhi, S., & Goyal, A. (2022). Improving and analyzing the movie sentiments using the SVM approach. IEEE Conference on Interdisciplinary Approaches in Technology
and Management.
• Gautam, A.K., & Verma, S. (2022). Hybrid approach for classification of medical imaging data using machine learning techniques. Workshop on Mining Data for Financial Applications (pp. 431–437).
• Verma, S., & Gautam, A.K. (2020). A survey on phishing detection and the importance of feature selection in data mining classification algorithms. Journal of Science and Technology, 5(6), 11–18.
• Verma, S., & Gautam, A.K. (2019). Machine learning techniques for classification of Spambase dataset: A hybrid approach. Proceedings of the 3rd International Symposium on Computer Science and Intelligent Control.
• Verma, S. (2014). Analysis of strengths and weakness of SDLC models. International Journal of Advance Research in Computer Science and Management.
• Verma, S. (2014). Comparative study on integration testing and system testing. International Journal of Advance Research in Computer Science and Management.
• Verma, S. (2014). A study on unified modelling language and its architecture. International Journal of Advanced Scientific and Technical Research.
• Verma, S. (2014). Model architecture and model building. International Journal of Computer Applications.
• Verma, S. (2014). A study on page life-cycle of ASP.NET. International Journal of Advanced Research in Computer Science and Software Engineering.

 

AI-Driven Centrifuge Tubes for Optimized Laboratory Workflows- Ms. Shikha Verma, Dr. Arun Kumar Gautam, Patent Number:6349127, Granted (07 March 2024).

1. Verma, S., Gupta, Y. (2024). Biomedical Text Data Visualization. In: Sharan, A., Malik, N., Imran, H., Ghosh, I. (eds) Text Mining Approaches for Biomedical Data. Transactions onComputer Systems and Networks. Springer, Singapore. https://doi.org/10.1007/978-981-97-3962-2_6
2. Verma, S., Ahmad, O., Sharan, A. (2024). Multilabel Text Classification in Biomedical Domain. In: Sharan, A., Malik, N., Imran, H., Ghosh, I. (eds) Text Mining Approaches for Biomedical Data. Transactions on Computer Systems and Networks. Springer, Singapore.
https://doi.org/10.1007/978-981-97- 3962-2_14

• Hybrid Approach for Classification of Medical Imaging data using Machine Learning Techniques during the International Conference on “Machine Intelligence and Data Science Applications (MIDAS-2022)

• Presented the paper titled “Machine Learning Techniques for Classification of Spambase Dataset: A Hybrid Approach” in International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML 2019, Italy).

1. Selected in IIT Delhi for SFRF-Summer Faculty Research Fellowship in May-July, 2018
and May- July, 2019 and July 2020.
2. Gold Medalist in Post Graduation (Year 2013).
3. Selected as Exemplary Performer student of MCA in Guru Gobind Singh Indraprastha University.