Dr. Prerna Agrawal
Assistant Professor
Ph.D - Computer Applications, MCA, BCA
Experience: 15+ years
Specialization: Machine Learning, Deep Learning, Artificial Intelligence, Generative AI, Big Data, Data Science, DBMS, Cloud Computing, Python, Computer Networks etc.
Research Area: Artificial Intelligence (AI), AI in Healthcare, Deep Learning & Machine Learning, Reinforcement Learning for Clinical Decision Support, Intelligent Autonomous Systems
About
I am a dedicated researcher and educator with expertise in Artificial Intelligence, Machine Learning, Deep Learning, Generative AI, Big Data, Data Science, Cloud Computing, Computer Networks, Python, and Databases. With a strong academic and research background, I strive to bridge the gap between theoretical knowledge and practical applications in emerging technologies.
🔹 Research & Publications: Authored and co-authored 30+ research publications in reputed national and international conferences and journals.
🔹 Academic Contributions: Served as Session Chair and Reviewer for various international conferences, contributing to the advancement of the research community.
🔹 Passion for Learning: A continuous learner who believes in adapting to technological innovations and sharing knowledge through teaching, mentoring, and collaborative research.
✨ My mission is to inspire students, collaborate with researchers, and contribute to impactful innovations in the fields of AI, Data Science, Machine Learning, Deep Learning and Big Data Technologies.
P. Agrawal, “From models to impact: A systematic review of generative artificial intelligence in education,” Int. J. Res. Eng., Sci. Manag., vol. 9, no. 1, pp. 7–10, 2026, doi: 10.65138/ijresm.v9i1.3398.
Year: 2026
P. Agrawal, “Agentic AI for modern healthcare: A comprehensive review,” Indian Journal of Computer Science and Technology, vol. 5, no. 1, pp. 125–129, Feb. 2026, doi: 10.59256/indjcst.20260501017.
Year: 2026
I. Shetty, P. Agrawal, and S. Gandhi, “Deep learning-based pulmonary edema detection: Performance evaluation of optimizers,” J. Comput. Anal. Appl., vol. 34, no. 8, pp. 50–67, Aug. 2025. [Online]. Available: https://eudoxuspress.com/index.php/pub/article/view/3453
Year: 2025
P. Agrawal, F. Shaikh, and H. Mansuri, “Generation of machine learning dataset from relational database and its evaluation using supervised classifiers,” Gradiva Rev. J., vol. 8, no. 5, pp. 689–694, 2022, doi: 10.37897/GRJ.2021.V7I11.21.49852.
Year: 2022
P. Agrawal, H. Tolani, A. Memon, and S. Oza, “Generation of machine learning dataset from RDBMS for clustering and association analysis,” Gradiva Rev. J., vol. 8, no. 5, pp. 868–874, 2022, doi: 10.37897/GRJ.2021.V7I11.21.49872.
Year: 2022
P. Agrawal and B. Trivedi, “Feature mining from APK files for malware detection,” Int. J. Appl. Inf. Syst., vol. 12, no. 32, pp. 6–10, 2020, doi: 10.5120/ijais2020451874.
Year: 2020
P. Agrawal and B. Trivedi, “Unstructured data collection from APK files for malware detection,” Int. J. Comput. Appl., vol. 176, no. 28, pp. 42–45, 2020, doi: 10.5120/ijca2020920308.
Year: 2020
P. Agrawal and B. Trivedi, “Automating the process of browsing and downloading APK files as a prerequisite for the malware detection process,” Int. J. Emerg. Trends Technol. Comput. Sci., vol. 9, no. 2, pp. 13–17, 2020.
Year: 2020
P. Agrawal and B. Trivedi, “Analysis of Android malware scanning tools,” Int. J. Comput. Sci. Eng., vol. 7, no. 3, pp. 807–810, 2019, doi: 10.26438/ijcse/v7i3.807810.
Year: 2019
H. Shivnani, P. Agrawal, and S. Gandhi, “Machine learning and deep learning advances for multiclass classification of ovarian pathologies using ultrasound imaging: A systematic review,” in Proc. Second Int. Conf. Artificial Intelligence, Computation, Communication and Network Security (AICCoNS 2026), Springer, 2026. (Paper Selected).
Year: 2026
P. Agrawal, S. Gandhi, P. Shah, K. Solanki, L. Prajapati, M. Shah, and P. Dudhela, “Signify: Deep learning based Indian Sign Language gesture multi-classification in the Indian scenario,” in Proc. 16th Int. Conf. Cloud Computing, Data Science & Engineering (Confluence 2026), Springer, 2026. (To be published).
Year: 2026
I. Shetty, P. Agrawal, and S. Gandhi, “Deep learning based pleural thickening detection: Performance evaluation of optimizers,” in Proc. 2nd Int. Conf. Emerging Technologies and Computing Innovations, Mar. 21–22, 2026, Springer. (Paper Selected)
Year: 2026
P. Agrawal and S. Gandhi, “PneumoSense++: An enhanced pneumonia detection with deep learning and comparative optimizer analysis,” in Proc. Int. Conf. Machine Learning and Data Engineering (ICMLDE 2025), to be published in Procedia Computer Science, Elsevier, 2025. (To be published).
Year: 2025
H. Shivnani, P. Agrawal, and S. Gandhi, “Machine learning in ovarian disease diagnosis: A systematic review,” in Proc. 4th Int. Conf. Advances in Data-driven Computing and Intelligent Systems (ADCIS 2025), Springer, Bangalore, 2025. (To be published).
Year: 2025
P. Agrawal, S. Gandhi, V. Dattani, and M. Rathod, “ShlokaSage: AI-driven emotion-based Bhagavad Gita shloka recommendation,” in Proc. Sixth Int. Conf. Advances in Computer Engineering and Communication Systems (ICACECS 2025), Springer, 2025. (To be published).
Year: 2025
P. Agrawal and S. Gandhi, “PneumoSense: Smart Pneumonia Detection Using Deep Learning,” in S. Fong, N. Dey, and A. Joshi, Eds., ICT Analysis and Applications (ICT4SD 2025), Lecture Notes in Networks and Systems, vol. 1653, Cham, Switzerland: Springer, 2026, doi: 10.1007/978-3-032-06694-7_2.
Year: 2025
P. Agrawal, S. Gandhi, V. Dattani, D. Rachchh, M. Rathod, and K. Vadher, “Using Machine Learning to Automate IT Job Role Prediction by Resume Screening,” in J. Choudrie, P. N. Mahalle, T. Perumal, and A. Joshi, Eds., ICT for Intelligent Systems (ICTIS 2025), Lecture Notes in Networks and Systems, vol. 1517, Singapore: Springer, 2026, doi: 10.1007/978-981-96-8895-1_7.
Year: 2025
I. Shetty, P. Agrawal, and S. Gandhi, “A survey on the lung diseases prediction in an Indian environment using machine learning,” in T. Senjyu, C. So-In, and A. Joshi, Eds., Smart Trends in Computing and Communications (SmartCom 2025), Lecture Notes in Networks and Systems, vol. 1460, Singapore: Springer, 2026, doi: 10.1007/978-981-96-7502-9_37.
Year: 2025
I. Shetty, P. Agrawal, and S. Gandhi, “Using machine learning for lung diseases prediction: A comprehensive review,” in Proc. 4th Int. Conf. Modeling Simulation and Optimization (CoMSO 2024), Springer, Nov. 2024.
Year: 2024
I. Shetty, P. Agrawal, and S. Gandhi, “A survey on use of machine learning in the healthcare sector,” in Manthan 2024: GLS University Doctoral and Faculty Research Colloquium, Sept. 2024. (To be published).
Year: 2024
P. Agrawal, S. Gandhi, and M. Agarwal, “DiabChatbot: A machine learning chatbot for early diagnosis of type II mellitus diabetes and diet recommendation in an Indian scenario,” in Proc. IEEE 10th Int. Conf. Advanced Computing and Communication Systems (ICACCS), 2024, pp. 1526–1531, doi: 10.1109/ICACCS60874.2024.10716933.
Year: 2024
P. Agrawal and B. Trivedi, “Social media platforms for digital marketing,” in Advances in Theory, Research and Practices in Management (GLSU-ATRPM), pp. 17–22, 2021.
Year: 2021
P. Agrawal and B. Trivedi, “AndroHealthCheck: A malware detection system for Android using machine learning,” in Computer Networks, Big Data and IoT, Singapore: Springer, 2020, pp. 35–41, doi: 10.1007/978-981-16-0965-7_4.
Year: 2020
P. Agrawal and B. Trivedi, “Evaluating machine learning classifiers to detect Android malware,” in Proc. IEEE Int. Conf. Innovative Technologies (INOCON), 2020, pp. 1–6, doi: 10.1109/INOCON50539.2020.9298290.
Year: 2020
P. Agrawal and B. Trivedi, “Machine learning classifiers for Android malware detection,” in Data Management, Analytics and Innovation, Singapore: Springer, 2021, pp. 311–322, doi: 10.1007/978-981-15-5616-6_22.
Year: 2020
P. Agrawal and B. Trivedi, “A survey on Android malware and their detection techniques,” in Proc. IEEE Conf. Electrical, Computer and Communication Technologies (ICECCT), 2019, pp. 1–6, doi: 10.1109/ICECCT.2019.8868951.
Year: 2019
R. Buyya, S. Gandhi, N. Chaubey, H. Arolkar, and P. Agrawal, Eds., Advances in Smart Computing and Applications: First International Conference, ICASCA 2025, Ahmedabad, India, February 15–16, 2025, Proceedings, Communications in Computer and Information Science, vol. 2619. Cham, Switzerland: Springer, 2026. doi: 10.1007/978-3-032-00350-8.
Year: 2025
P. Agrawal and S. Gandhi, “Intelligent learning: The AI revolution in digital education,” in Human-AI Collaboration and the Evolving Role of Educators, B. Al-Sowaidi and T. Mohammed, Eds., IGI Global Scientific Publishing, 2026. (To be published).
Year: 2026
H. Shivnani, P. Agrawal, and S. Gandhi, “Intelligent imaging: Deep learning in medical science,” in Strengthening e-Collaboration in Healthcare through AI, J. Zhao, Ed., IGI Global Scientific Publishing, 2026. (Chapter selected).
Year: 2026
P. Agrawal and S. Gandhi, “Artificial intelligence: The new ally in healthcare,” in Strengthening e-Collaboration in Healthcare through AI, J. Zhao, Ed., IGI Global Scientific Publishing, 2026. (Chapter selected).
Year: 2026
P. Agrawal and S. Gandhi, “Big data cyber security analytics,” in Advanced Cyber Security Techniques for Data, Blockchain, IoT, and Network Protection, N. Chaubey and N. Chaubey, Eds., IGI Global Scientific Publishing, 2025, pp. 21–48, doi: 10.4018/979-8-3693-9225-6.ch002.
Year: 2025
Received the Best Paper Award, Third Position at Manthan 2024, conducted at GLS University.
Year: 2024
Received the Best Student Dissertation Award, Second Position at I.M Nanavati Awards 2025, conducted at GLS University on 18th June 2025.
Year: 2025
Received the Best Faculty Student Joint Research, First Position at I.M Nanavati Awards 2025, conducted at GLS University on 18th June 2025.
Year: 2025
Received the Best Paper Award, First Position at I.M Nanavati Awards 2025, conducted at GLS University on 18th June 2025.
Year: 2025
No PhD students listed.