International Conference on Artificial Intelligence and Cybersecurity

Shruti Aggarwal

Biography

Shruti Aggarwal, is working as Assistant Professor in the Department of Computer Science and Engineering at Thapar Institute of Engineering and Technology. She has worked as Associate Professor and Head at Chandigarh University and has pursued her doctorate in software engineering domain from N.I.T., Jalandhar. She has earned her Master?s degree from U.I.E.T., Panjab University, in 2011 and B.Tech. (C.S.E.) from Kurukshetra University in 2008. In more than 15 years of her teaching career at reputed institutes like N.IT., Kurukshetra University, etc; she has guided 36 research scholars, published more than 120+ research papers in various Journals and Conferences of national and international repute. She has conducted numerous technical and non-technical events, supported various industrial projects, and has given talks in Data Mining and Software Engineering domain. She is the reviewer of various prestigious journals and she has hosted session chairs in various international conferences. She has 17 patents and has been awarded with several awards like Abdul Kalam Innovation Special Appreciation Award, 50 Eminent Researchers of 2021, Research Excellence Award, Womonator Award, 100 Eminent Academicians of 2021, Global Femina Excellence Award, etc. from various reputed international and national organizations. She also has 2 licensed copyright on CMS and text to speech conversion. She is currently working on book chapters, research projects and patents in the domain of data science and generative AI.

Research Interest

Abstract

Artificial Intelligence (AI) is no longer a futuristic concept but a transformative force in modern healthcare. This talk explores how AI technologies?ranging from deep learning and natural language processing to multi-modal data fusion?are revolutionizing diagnostics, drug discovery, patient monitoring, and personalized treatment plans. Drawing on real-world case studies and current research, the session highlights how AI models can detect diseases at early stages, streamline clinical workflows, and enhance decision-making for healthcare professionals. Emphasis will be placed on explainable AI (XAI), ethical implications, and the integration of AI with electronic health records (EHRs), imaging, and wearable data. Attendees will gain insights into the challenges and opportunities of deploying AI in clinical settings, including data privacy, regulatory compliance, and clinician trust. Whether you're a researcher, clinician, or technologist, this session will provide a forward-looking perspective on the role of AI in creating smarter, more responsive, and equitable healthcare systems.