Dr Jaya Lakshmi Tangirala PhD
Lecturer
- School of Engineering and Built Environment
- School of Computing and Digital Technologies
- Industry and Innovation Ï㽶ÊÓƵ Institute
Summary
Dr. Jaya is a seasoned educator and researcher with a Ph.D. in Data Analytics, driven by a profound passion for unleashing the transformative potential of data in academia and beyond. With over two decades of experience in computer science and engineering education, her career has been shaped by a commitment to excellence in teaching, research, and innovation. This journey has afforded her the privilege of inspiring and mentoring countless students while staying attuned to the dynamic landscape of technological advancements. As both an educator and researcher, she continually strives to foster a deep appreciation for data-driven problem-solving and empower the next generation of technology professionals.
Jaya’s research focuses on exploring Data Analytics, integrating cutting-edge technologies for positive societal change. Jaya is dedicated to tackling intricate challenges across a spectrum of sectors including education, finance, and healthcare. Currently, her efforts are concentrated in two primary areas. Firstly, Jaya is delving into the problem of link prediction in social networks in various kinds of network models. Secondly, she is endeavouring to enhance customer experiences through the development of innovative algorithms for recommender systems. Furthermore, Jaya’s ongoing research encompasses the exploration of applications in Natural Language Processing, Data Mining, Big Data, and Machine Learning.
About
Dr. Jaya is a seasoned educator and researcher with a Ph.D. in Data Analytics, driven by a profound passion for unleashing the transformative potential of data in academia and beyond. With over two decades of experience in computer science and engineering education, her career has been shaped by a commitment to excellence in teaching, research, and innovation. This journey has afforded her the privilege of inspiring and mentoring countless students while staying attuned to the dynamic landscape of technological advancements. As both an educator and researcher, she continually strives to foster a deep appreciation for data-driven problem-solving and empower the next generation of technology professionals.
Jaya’s research focuses on exploring Data Analytics, integrating cutting-edge technologies for positive societal change. Jaya is dedicated to tackling intricate challenges across a spectrum of sectors including education, finance, and healthcare. Currently, her efforts are concentrated in two primary areas. Firstly, Jaya is delving into the problem of link prediction in social networks in various kinds of network models. Secondly, she is endeavouring to enhance customer experiences through the development of innovative algorithms for recommender systems. Furthermore, Jaya’s ongoing research encompasses the exploration of applications in Natural Language Processing, Data Mining, Big Data, and Machine Learning.
Lecturer
Teaching
School of Engineering and Built Environment , School of Computing and Digital Technologies
College of Business, Technology and Engineering
Subject area: Software Engineering
Courses taught:
- BSc Computer Science
- MSc Software Engineering
Modules taught:
- Algorithms and Data Structures
- Databases and Web
- Work-based Review for Apprenticeship
- Advanced Software Engineering
Publications
Journal articles
Nandini, Y.V., Jaya Lakshmi, T., Krishna Enduri, M., & Zairul Mazwan Jilani, M. (2025). Link Prediction in Complex Hyper-Networks Leveraging HyperCentrality. IEEE Access, 13, 12239-12254.
Tokala, S., Krishna Enduri, M., Tangirala, J.L., Abdul, A., & Chen, J. (2024). . IEEE Access, 12, 164028-164062.
Nandini, Y.V., Lakshmi, T.J., Enduri, M.K., & Sharma, H. (2024). . Entropy, 26 (6).
Nandini, Y.V., Tangirala, J.L., Enduri, M.K., Sharma, H., & Ahmad, M.W. (2024). . IEEE Access, 12, 51208-51222.
Sanku, S.U., Pavani, S.T., Tangirala, J.L., & Chivukula, R. (2024). . SN Computer Science, 5.
Tangirala, J.L., & Bhavani, S.D. (2023). . Computing.
Tokala, S., Enduri, M.K., Tangirala, J.L., & Sharma, H. (2023). . Entropy, 25 (9).
Kapila, R., Ragunathan, T., Saleti, S., Tangirala, J.L., & Ahmad, M.W. (2023). . IEEE Access, 11, 64324-64347.
Saleti, S., Tangirala, J.L., & Ahmad, M.W. (2022). . IEEE Access, 10, 123301-123315.
Kandula, L.R.R., Tangirala, J.L., Alla, K., & Chivukula, R. (2022). . International Journal of Safety and Security Engineering, 12 (3), 381-386.
Bojjagani, S., Rao, P.V.V., Vemula, D.R., Reddy, B.R., & Lakshmi, T.J. (2022). A secure IoT-based micro-payment protocol for wearable devices. Peer-to-Peer Networking and Applications, 15 (2), 1163-1188.
Chivukula, R., Tangirala, J.L., Uday, S.S., & Pavani, S.T. (2021). . Indonesian Journal of Electrical Engineering and Computer Science, 24 (3), 1672-1679.
Chivukula, R., Vamsi, M., Tangirala, J.L., & Harini, M. (2021). . International Journal of Advanced Computer Science and Applications, 12 (3), 509-515.
Jaya Lakshmi, T., & Durga Bhavani, S. (2017). Temporal probabilistic measure for link prediction in collaborative networks. Applied Intelligence, 47 (1), 83-95.
Tokala, S., Enduri, M.K., Lakshmi, T.J., Hajarathaiah, K., & Sharma, H. (n.d.). Empirical Analysis of Variations of Matrix Factorization in Recommender Systems. International Journal of Advanced Computer Science and Applications, 16 (1).
Conference papers
Walia, M., Raj, S., Aishwary, M., & Lakshmi, T.J. (2025). Synergizing Collaborative and Content-Based Filtering for Enhanced Movie Recommendations. In Lecture Notes in Electrical Engineering, (pp. 31-42). Springer Nature Singapore:
Nandini, Y.V., Tangirala, J.L., & Enduri, M.K. (2023). . Smart Innovation, Systems and Technologies, 371 (371), 57-67.
Sanku, S.U., Satti, T.P., Tangirala, J.L., & Nandini, Y.V. (2023). . Smart Innovation, Systems and Technologies, 371 (371), 19-29.
Mani Saketh, C.V.S.S., Pranay, K., Susarla, A., Ravi Ram Karthik, D., Tangirala, J.L., & Nandini, Y.V. (2023). . Smart Innovation, Systems and Technologies, 371 (371), 111-119.
Harsha, K., Yuva Nitya, S., Kota, S., Satyanarayana, K., & Lakshmi, J. (2023). Empirical evaluation of Amazon fine food reviews using Text Mining. 2023 IEEE 8th International Conference for Convergence in Technology (I2CT), 1-5.
Chivukula, R., Lakshmi, T.J., Sumalatha, S., & Reddy, K.L.R. (2022). Ontology Based Food Recommendation. In Smart Innovation, Systems and Technologies, (pp. 751-759). Springer Nature Singapore:
Tejaswi, D.K., Chauhan, H., Lakshmi, T.J., Swetha, R., & Sri, N.N. (2022). Investigation of Ethereum Price Trends using Machine learning and Deep Learning Algorithms. 2022 2nd International Conference on Intelligent Technologies (CONIT).
Saleti, S., Tangirala, J.L., & Thirumalaisamy, R. (2021). Distributed Mining of High Utility Time Interval Sequential Patterns with Multiple Minimum Utility Thresholds. In Lecture Notes in Computer Science, (pp. 86-97). Springer International Publishing:
Chivukula, R., & Lakshmi, T.J. (2021). Mining Heterogeneous Information Networks: A Review. 2021 IEEE Pune Section International Conference (PuneCon), 1-4.
Chivukula, R., Jaya Lakshmi, T., Ranganadha Reddy Kandula, L., & Alla, K. (2021). A Study of Cyber Security Issues and Challenges. 2021 IEEE Bombay Section Signature Conference (IBSSC), 1-5.
Lakshmi, T.J., & Bhavani, S.D. (2018). Link Prediction Measures in Various Types of Information Networks: A Review. 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 1160-1167.
Jaya Lakshmi, T., & Bhavani, S.D. (2015). Enhancement to community-based multi-relational link prediction using co-occurrence probability feature. Proceedings of the Second ACM IKDD Conference on Data Sciences, 86-91.
Lakshmi, T.J., & Prasad, C.S.R. (2014). A study on classifying imbalanced datasets. 2014 First International Conference on Networks & Soft Computing (ICNSC2014), 141-145.
Lakshmi, T.J., & Bhavani, S.D. (2014). Heterogeneous link prediction based on multi relational community information. 2014 Sixth International Conference on Communication Systems and Networks (COMSNETS), 1-4.
Book chapters
Jaya Lakshmi, T., & Durga Bhavani, S. (2017). Link Prediction in Temporal Heterogeneous Networks. In Lecture Notes in Computer Science. (pp. 83-98). Springer International Publishing: