Journals
Materwala, Huned, Shraddha M. Naik, Aya Taha, Tala Abdulrahman Abed, and Davor Svetinovic. “Maximal Extractable Value in Decentralized Finance: Taxonomy, Detection, and Mitigation”, EEE Transactions on Services Computing (2024). https://doi.org/10.1109/TSC.2025.3620604
Chakraborty, Tanujit, Swarup Chattopadhyay, Suchismita Das, Shraddha M. Naik, and Chittaranjan Hens. “Learning from Biological Networks: A Compounded Burr Probability Model”, Chaos: An Interdisciplinary Journal of Nonlinear Science (2025). https://arxiv.org/abs/2407.04465v1
Naik, Shraddha M., Tanujit Chakraborty, Madhurima Panja, Abdenour Hadid, and Bibhas Chakraborty. “Skew Probabilistic Neural Networks for Learning from Imbalanced Data.”, Pattern Recognition (2025): 111677. https://doi.org/10.1016/j.patcog.2025.111677
Chakraborty, Tanujit, Ujjwal Reddy KS, Shraddha M. Naik, Madhurima Panja, and Bayapureddy Manvitha. “Ten years of generative adversarial nets (GANs): a survey of the state-of-the-art.” Machine Learning: Science and Technology 5, no. 1 (2024): 011001. https://doi.org/10.1088/2632-2153/ad1f77
Naik, Shraddha M., Chinnamuthu Subramani, Ravi Prasad K. Jagannath, and Anand Paul. “Exponential filtering technique for Euclidean norm-regularized extreme learning machines.” Pattern Analysis and Applications 26, no. 3 (2023): 1453-1462. https://doi.org/10.1007/s10044-023-01174-8
Goona, Nithin Kumar, Shraddha M. Naik, Saidi Reddy Parne, and Anand Paul. “DssPyLib: An opensource python FEM software to solve Poisson equation in 2-D using distributed source scheme.” SoftwareX 21 (2023): 101308. https://doi.org/10.1016/j.softx.2023.101308
Lolaev, Musulmon, Shraddha M. Naik, Anand Paul, and Abdellah Chehri. ”Heuristic Weight Initialization for Diagnosing Heart Diseases Using Feature Ranking.” Technologies 11, no. 5 (2023): 138. https://doi.org/10.3390/technologies11050138
Subramanian, Barathi, Bekhzod Olimov, Shraddha M. Naik, Sangchul Kim, Kil-Houm Park, and Jeonghong Kim. “An integrated mediapipe-optimized GRU model for Indian sign language recognition.” Scientific Reports 12, no. 1 (2022): 11964. https://doi.org/10.3390/technologies11050138
Manjunatha, P. T., Ali J. Chamkha, R. J. Punith Gowda, R. Naveen Kumar, B. C. Prasannakumara, and Shraddha M. Naik. “Significance of stefan blowing and convective heat transfer in nanofluid flow over a curved stretching sheet with chemical reaction.” Journal of Nanofluids 10, no. 2 (2021): 285-291. https://doi.org/10.1166/jon.2021.1786
Naik, Shraddha M., Ravi Prasad K. Jagannath, and Venkatnareshbabu Kuppili. “Bat algorithm-based weighted Laplacian probabilistic neural network.” Neural Computing and Applications 32, no. 4 (2020): 1157-1171. https://doi.org/10.1007/s00521-019-04475-4
Naik, Shraddha M., Ravi Prasad K. Jagannath, and Venkatanareshbabu Kuppili. “An automatic estimation of the ridge parameter for extreme learning machine.” Chaos: An Interdisciplinary Journal of Nonlinear Science 30, no. 1 (2020). https://doi.org/10.1063/1.5097747
Naik, Shraddha M., Ravi Prasad K. Jagannath, and Venkatanareshbabu Kuppili. “Fractional Tikhonov regularization to improve the performance of extreme learning machines.” Physica A: Statistical Mechanics and its Applications 551 (2020): 124034. https://doi.org/10.1016/j.physa.2019.124034
Naik, Shraddha M., Ravi Prasad K. Jagannath, and Venkatanareshbabu Kuppili. “Iterative minimal residual method provides optimal regularization parameter for extreme learning machines.” Results in Physics 13 (2019): 102082. https://doi.org/10.1016/j.rinp.2019.02.018
Naik, Shraddha M., Ravi Prasad K. Jagannath, and Venkatanareshbabu Kuppili. “Estimation of the smoothing parameter in probabilistic neural network using evolutionary algorithms.” Arabian Journal for Science and Engineering 45, no. 4 (2020): 2945-2955. https://doi.org/10.1007/s13369-019-04227-5
Naik, Shraddha M. and Sankhya Nayak, “Text detection and character extraction in natural scene images,” International Journal of Emerging Technology and Advanced Engineering, 5(2),pp. 1–5, 2015.
Conference Proceedings
Naik, Shraddha M., and Ravi Prasad K. Jagannath. ”Accurate validation of GCV-based regularization parameter for extreme learning machine.” In 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1727-1731. IEEE, 2017. https://doi.org/10.1109/ICACCI.2017.8126093
Naik, Shraddha M., and Ravi Prasad K. Jagannath. ”GCV-based regularized extreme learning machine for facial expression recognition.” In Advances in Machine Learning and Data Science: Recent Achievements and Research Directives, pp. 129-138. Springer Singapore, 2018. https://doi.org/10.1007/978-981-10-8569-7_14
Naik, Shraddha M., Ravi Prasad K. Jagannath, and Venkatanareshbabu Kuppili. ”Optimized Laplacian Generalized Classifier Neural Network.” In 2018 9th IEEE International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2018 https://doi.org/10.1109/ICCCNT.2018.8494187