Vijayalakshmi Kakulapati

Sreenidhi Institute of Science and Technology

Prof. Vijayalakshmi Kakulapati received a Ph.D. in Computer Science and Engineering from Jawaharlal Nehru Technological University (JNTU), Hyderabad. She is currently a professor in the Department of Information Technology, Sreenidhi Institute of Science and Technology, Hyderabad. She has twenty-six years of industry and teaching experience and is a member of various professional bodies, including the Institute of Electrical and Electronics Engineer (IEEE), Association for Computing Machinery (ACM), Computer Science Teachers Association (CSTA), LMISTE, LMCSI, International Association of Computer Science and Information Technology (IACSIT), FIETE, and more. She has more than 110 publications in national and international journals and conferences, 30 book chapters, and 2 books to her credit. She has received numerous awards, including Excellence in Research, Best Reviewer, appreciation awards, and more. Her areas of research include theoretical and practical information retrieval problems as well as machine learning applied to large-scale textual applications. Her research has focused on retrieval models, query/document representations, term weighting, term proximity models, and learning to rank (machine-learned ranking functions). She is also passionate about seeing research problems applied to real-world problems, especially those dealing with large, complex data sets. Along these lines, she is working with evaluating and designing novel search algorithms for web search and summarization. Currently, Dr. Kakulapati is working with big data analytics, health informatics, the Internet of Things, deep learning, artificial intelligence, and data sciences.

1books edited

1chapters authored

Latest work with IntechOpen by Vijayalakshmi Kakulapati

Open data is freely usable, reusable, or redistributable by anybody, provided there are safeguards in place that protect the data’s integrity and transparency. This book describes how data retrieved from public open data repositories can improve the learning qualities of digital networking, particularly performance and reliability. Chapters address such topics as knowledge extraction, Open Government Data (OGD), public dashboards, intrusion detection, and artificial intelligence in healthcare.

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