Dr. Preeti Yadav is an accomplished academician, researcher, and educator serving as an Associate Professor in the Department of Computer Science and Information Technology, Institute of Engineering & Technology, Mahatma Jyotiba Phule Rohilkhand University (MJPRU), Bareilly, Uttar Pradesh, India. With nearly two decades of experience in higher education, she has established herself as a leading researcher in Wireless Sensor Networks (WSNs), Machine Learning, Internet of Things (IoT), Artificial Intelligence, and Blockchain Technologies. She earned her Ph.D. in Computer Science & Engineering from the Indian Institute of Technology (IIT) Roorkee in 2023. Her doctoral research focused on the development of efficient localization techniques for Wireless Sensor Networks using Machine Learning. She completed her M.Tech. in Computer Science & Engineering from Integral University, Lucknow, with specialization in Natural Language Processing, and received her B.Tech. in Computer Science & Engineering from S.R.M.S. College of Engineering & Technology, affiliated with UPTU. Dr. Yadav has over 18 years of teaching and research experience, during which she has taught a wide range of undergraduate and postgraduate courses, including Machine Learning, Data Structures, Database Management Systems, Cryptography & Network Security, and Wireless and Mobile Communication. Her dedication to quality education and student mentorship has significantly contributed to academic excellence within the university. Her research spans interdisciplinary domains including Artificial Intelligence, IoT, Blockchain, Smart Agriculture, Cyber Security, Intelligent Healthcare, and Wireless Sensor Networks. She has authored more than 60 research publications, including papers in prestigious SCI/SCIE, Scopus, and ESCI indexed journals, IEEE conferences, book chapters, and technical books. Her work has gained international recognition for advancing intelligent networking systems and AI-driven solutions. An active innovator, Dr. Yadav holds 13 patents in emerging technologies such as IoT, Blockchain, Artificial Intelligence, Smart Healthcare, Smart Cities, Environmental Monitoring, and Educational Technologies. She has also successfully completed and is currently leading several externally funded research projects supported by organizations including UPCST, TEQIP, and the Government of Uttar Pradesh, focusing on AI-enabled livestock monitoring, pharmaceutical supply chain security using blockchain, and land-use analysis through deep learning. Beyond research, Dr. Yadav actively contributes to academic administration and curriculum development. She has served in numerous leadership roles including Student Advisor, B.Tech First Year Coordinator, Seminar Coordinator, Project Lab In-charge, IEEE Women in Engineering Affinity Group Convenor, and member of several university committees such as IQAC, Board of Studies, AI Syllabus Committee, RTI Committee, and Distance & Online Education Cell. As a research supervisor, she has successfully guided Ph.D. scholars and M.Tech dissertations, mentoring students in cutting-edge research areas such as Machine Learning, Federated Learning, Healthcare AI, and Smart Agriculture. She regularly delivers keynote lectures, invited talks, faculty development programs, and international workshops on Artificial Intelligence, Data Science, Deep Learning, and Emerging Technologies. Dr. Yadav's academic excellence has been recognized through several prestigious awards, including the Women in Engineering Excellence Award, Best Research Award, and recognition for highly viewed research publications. She currently serves as a Women in Data Science (WiDS) Ambassador and is an active member of professional organizations including IEEE and ACM, continuously promoting collaborative research, innovation, and women empowerment in STEM education. Driven by a passion for research, innovation, and student success, Dr. Preeti Yadav continues to contribute to the advancement of intelligent computing technologies while fostering an environment of academic excellence and impactful research.
Development of an Efficient Localization Scheme in Wireless Sensor Networks using Machine Learning
Natural Language Processing
Computer Science & Engineering
Assistant Professor (AGP 8000). Teaching and Research.
Assistant Professor (AGP 7000). Teaching and Research.
Teaching and Research.
IT Officer / Assistant Manager. April 2008 to August 2008.
Teaching. July 2007 to March 2008.