Jyoti Kataria is an Indian Computer Science academic, researcher, and educator currently serving as an Assistant Professor in the Computer Science and Engineering (Artificial Intelligence and Machine Learning) Department at Accurate Group of Institutions. She holds an M.Tech. from Maharshi Dayanand University, Rohtak, an MCA from the Department of Computer Science and Applications, Maharshi Dayanand University, and a BCA from Guru Jambheshwar University of Science and Technology, Hisar. She is currently pursuing a Ph.D. in Computer Science at Starex University, Gurugram and has qualified UGC-NET in Computer Science. She has several years of teaching experience across institutions including NIET, B. S. Anangpuria Institute of Technology and Management, Starex University, and Manav Institute of Technology and Management. Her academic expertise includes Artificial Intelligence, Machine Learning, Deep Learning, Computer Science, Data Mining, Network Security, Internet of Things, Python Programming, and Software Development. She has also undertaken professional development in Generative AI, Agentic AI, Machine Learning, Deep Learning, Power BI, research methodology, intellectual property, and AI ethics, and has served in academic responsibilities including timetable coordination, class coordination, and external examination.Her research interests focus on Artificial Intelligence, Machine Learning, Deep Learning, Cybersecurity, Network Security, IoT, Blockchain, Data Mining, Healthcare Technology, and Intelligent Computing. Her research and publications include work on diabetic data analysis using machine learning and neural networks, routing attacks and black-hole attack mitigation in MANETs and IoT environments, AI-driven network security, blockchain and IoT, facial-recognition-based conferencing, machine-learning applications in healthcare, and AI-based data security in emerging networks. She has presented research at international conferences, published in academic journals, authored a book on problem solving and Python programming, and contributed to several patent applications involving machine learning, healthcare systems, image-data control, and network security. Her combination of teaching experience, research activity, technical expertise, and professional training makes her well suited for research and peer review in Computer Science, Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Cybersecurity, Network Security, Internet of Things, Blockchain Technology, Data Mining, Healthcare Informatics, Python Programming, Software Engineering, and Emerging Computing Technologies.