Personal profile
Professional Information
Department SLCM Coordinator, Co-Coordinator of Student Research Activity Committee
Experience
▪ Working as Assistant Professor in the School of Computer Engineering at Manipal Institute of Technology Bengaluru, MAHE from 12 April 2023 to present.
▪ Worked as an Assistant Professor in the Department of Computational Intelligence, School of Computing at SRM Institute of Science and Technology, Kattankulathur Campus, Chennai, India from January 2023 to March 2023.
▪ Worked as an Assistant Professor in the Department of Computer Science and Engineering, GITAM School of Technology, Gandhi Institute of Technology and Management, Bengaluru, India from August 2022 to January 2023.
Awards and Recognition
▪UGC-SRF-NET (Senior Research Fellowship) in Computer Science and Applications – January 2020
▪UGC-JRF-NET (Junior Research Fellowship) in Computer Science and Applications - January 2018
▪All India Rank 1311 in Graduate Aptitude Test in Engineering (GATE) - March 2015
▪UGC-NON-NET Fellowship from 2015 to 2017
▪President Guide - February 2008
Research interests
Machine Learning, Deep Learning, Support Vector Machine for Classification and Regression, Computer Vision
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Collaborations and top research areas from the last five years
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FLSVR: Solving Lagrangian Support Vector Regression Using Functional Iterative Method
Meena, Y., Anagha, P. & Balasundaram, S., 08-2025, In: Neural Processing Letters. 57, 4, 71.Research output: Contribution to journal › Article › peer-review
Open Access -
Predictive Modeling Techniques of Social Dynamics in Multilayer Social Networks: A Survey
Jaya Krishna, R., Vamshi Krishna, B., Gopalakrishnan, T., Anagha, P., Kumar Sharma, V. & Prasad Sharma, D., 2024, Smart Systems: Innovations in Computing - Proceedings of SSIC 2023. Somani, A. K., Mundra, A., Gupta, R. K., Bhattacharya, S. & Mazumdar, A. P. (eds.). Springer Science and Business Media Deutschland GmbH, p. 621-630 10 p. (Smart Innovation, Systems and Technologies; vol. 392 SIST).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Robust Pinball Twin Bounded Support Vector Machine for Data Classification
Prasad, S. C., Anagha, P. & Balasundaram, S., 04-2023, In: Neural Processing Letters. 55, 2, p. 1131-1153 23 p.Research output: Contribution to journal › Article › peer-review
12 Link opens in a new tab Citations (Scopus) -
On Twin Bounded Support Vector Machine with Pinball Loss
Anagha, P. & Balasundaram, S., 2022, Advanced Machine Intelligence and Signal Processing. Gupta, D., Sambyo, K., Prasad, M. & Agarwal, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 177-190 14 p. (Lecture Notes in Electrical Engineering; vol. 858).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Link opens in a new tab Citation (Scopus) -
L1-Norm Support Vector Regression in Primal Based on Huber Loss Function
Puthiyottil, A., Balasundaram, S. & Meena, Y., 2020, Proceedings of ICETIT 2019 - Emerging Trends in Information Technology. Singh, P. K., Panigrahi, B. K., Suryadevara, N. K., Sharma, S. K. & Singh, A. P. (eds.). Springer, p. 195-205 11 p. (Lecture Notes in Electrical Engineering; vol. 605).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
2 Link opens in a new tab Citations (Scopus)