0000-0003-2095-5069 About
Dr Rashmi Agrawal is PhD and UGC-NET qualified with 20 years of experience in teaching and research, working as Professor in Department of Computer Applications, Manav Rachna International Institute of Research and Studies, Faridabad, India. She is associated with various professional bodies in different capacities, life member of Computer Society of India and senior member of IEEE, She is book series editor of Innovations in Big Data and Machine Learning, CRC Press, Taylor and Francis group, USA and Advances in Cybersecurity in Wiley. She has authored/ co-authored many research papers in peer reviewed national/international journals and conferences which are SCI/SCIE/ESCI/SCOPUS indexed. She has also edited/authored books with national/international publishers (Springer, Elsevier, IGI Global, Apple Academic Press, and CRC Press) and contributed chapters in books . Currently she is guiding PhD scholars in Sentiment Analysis, Educational Data Mining, Internet of Things, Brain Computer Interface and Natural language Processing. She is Associate Editor in Journal of Engineering and Applied Sciences and Array Journal, Elsevier.
Employment
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Manav Rachna International University Professor
Education
Education history is unavailable.
Projects & Funding
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Publications (79)
- Real-time emotion detection system using a hybrid machine learning model for enhanced sentiment analysis in online learning environments Save
- Enhancing image classification accuracy with AL-CNN: a hybrid of AlexNet and LeNet architectures Save
- AL-CNN: A Unified Framework for Image Classification and Captioning Save
- A Comparative Analysis of Image Classification Models Across Multiple Domains and Benchmark Datasets Save
- Value group classifier model for ethical decision-making Save
- MVC in machine learning: a decade of algorithmic advances, challenges, and applications–a systematic review Save
- Understanding explainable artificial intelligence techniques: a comparative analysis for practical application Save
- Understanding Biomedical Engineering for Quantum Computing Save
- Correction to: LTE-NBP with holistic UWB-WBAN approach for the energy efficient biomedical application Save
- LTE-NBP with holistic UWB-WBAN approach for the energy efficient biomedical application Save