Jamshid Tursunboev, Vikas Palakonda, Il-Min Kim, Sunghwan Moon, and Jae-Mo Kang, “Multi-Objective Optimization Framework for Heterogeneous Federated Learning,” CAAI Transactions on Intelligence Technology, early access, Sep. 2025 (IF: 7.3)
Mingyu Sung, Vikas Palakonda, Il-Min Kim, Sangseok Yun, Jae-Mo Kang, "DeCo-MeSC: Deep Compression-Based Memory-Constrained Split Computing Framework for Cooperative Inference of Neural Network," in IEEE Transactions on Vehicular Technology (IF: 6.1).
Vikas Palakonda, Jamshid Tursunboev, Jae-Mo Kang, Sunghwan Moon, Metaheuristics for pruning convolutional neural networks: A comparative study", Expert Systems with Applications, Volume 268, 2025, 126326 (IF: 7.5).
Vikas Palakonda, Samira Ghorbanpour, Jae-Mo Kang and Heechul Jung, "External archive guided radial-grid multi objective differential evolution". Scientific Reports 14, 29006 (2024) (IF: 3.8).
Vikas Palakonda, Jae-Mo Kang and Heechul Jung, "Clustering-Aided Grid-Based One-to-One Selection-Driven Evolutionary Algorithm for Multi/Many-Objective Optimization," in IEEE Access, vol. 12, pp. 120612-120623, 2024 (IF: 3.4).
Chae-Won Park, Vikas Palakonda, Sangseok Yun, Il-Min Kim and Jae-Mo Kang, "OCR-Diff: A Two-Stage Deep Learning Framework for Optical Character Recognition Using Diffusion Model in Industrial Internet of Things," in IEEE Internet of Things Journal, vol. 11, no. 15, pp. 25997-26000, 1 Aug 2024 (IF: 8.2).
Jamshid Tursunboev, Vikas Palakonda, and Jae-Mo Kang, “Multi-objective evolutionary hybrid deep learning for energy theft detection,” Applied Energy, vol. 363, p. 122 847, 2024. (IF: 10.1).
Vikas Palakonda, Jae-Mo Kang and Heechul Jung, “Benchmarking real-world many-objective problems: A problem suite with baseline results,” IEEE Access, vol. 12, pp. 49275-49290, 2024 (IF: 3.4).
Seong-Hwan Kang, Vikas Palakonda, Il-Min Kim, Jae-Mo Kang, Sangseok Yun, “Enhanced non-maximum suppression for the detection of steel surface defects,” Mathematics, vol. 11, no. 18, p. 3898, 2023 (IF: 2.3).
Yosoeb Shin, Vikas Palakonda, Sangseok Yun, Il-Min Kim, Seon-Gon Kim, Sang-Mi Park, Jae-Mo Kang, “Randmixaugment: A novel unified technique for region-and image-level data augmentations,” IEEE Access, 2023 (IF: 3.4).
Vikas Palakonda and Jae-Mo Kang, “Pre-DEMO: Preference-inspired differential evolution for multi/many-objective optimization,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 12, pp. 7618-7630, Dec. 2023 (IF: 8.6).
Vikas Palakonda, Jae-Mo Kang and Heechul Jung, “An effective ensemble framework for many-objective optimization based on adaboost and k-means clustering,” Expert Systems with Applications, vol. 227, p. 120 278, 2023 (IF: 7.5).
Vikas Palakonda and Jae-Mo Kang, “Many-objective real-world engineering problems: A comparative study of state-of-the-art algorithms,” IEEE Access, vol. 11, pp. 111636-111654, 2023 (IF: 3.4).
Vikas Palakonda, Jae-Mo Kang and Heechul Jung, “An adaptive neighborhood based evolutionary algorithm with pivot-solution based selection for multi-and many-objective optimization,” Information Sciences, vol. 607, pp. 126–152, 2022 (IF: 8.1).
Vikas Palakonda, R. Mallipeddi, and P. N. Suganthan, “An ensemble approach with external archive for multi-and many-objective optimization with adaptive mating mechanism and two-level environmental selection,” Information Sciences, vol. 555, pp. 164–197, 2021 (IF: 8.1).
Vikas Palakonda and R. Mallipeddi, “An evolutionary algorithm for multi and many-objective optimization with adaptive mating and environmental selection,” IEEE Access, vol. 8, pp. 82 781–82 796, 2020 (IF: 3.4).
Vikas Palakonda and R. Mallipeddi, “Pareto dominance-based algorithms with ranking methods for many-objective optimization,” IEEE Access, vol. 5, pp. 11 043–11 053, 2017 (IF: 3.4).
Jamshid Yusupov, Vikas Palakonda, Samira Ghorbanpour, Rammohan Mallipeddi, Kalyana Chakravarthy Veluvolu. “An Generational SDE based Indicator for Multi and Many-Objective optimization.” International Conference on Artificial Intelligence in Information and Communication (ICAIIC), 2021.
Jamshid Yusupov, Vikas Palakonda, Rammohan Mallipeddi, Kalyana C Veluvolu. “Multi-objective Evolutionary Algorithm based on Ensemble of Initializations for Overlapping Community Detection.” International Conference on Electronics, Information, and Communication (ICEIC) 2021.
Samira Ghorbanpour, Vikas Palakonda, and Rammohan Mallipeddi. “Multi-Objective Optimization of SVM Parameters for Meta Classifier Design.” International conference on soft computing, 2019.
Samira Ghorbanpour, Vikas Palakonda, Fitria W. Ramlan, Rammohan Mallipeddi. “An Experimental Short Review on Color Image Quantization.” International Conference on Artificial Intelligence and Soft Computing (ICAISC), 2019.
Fitria W. Ramlan, Vikas Palakonda, Rammohan Mallipeddi “Hierarchical Approach Based Evolutionary Algorithm for Many-Objective Optimization”. International Conference on Artificial Intelligence and Soft Computing (ICAISC), 2019.
Fitria W. Ramlan, Vikas Palakonda, and Rammohan Mallipeddi, "Differential Evolutionary (DE) Based Interactive Recoloring Based on YUV Based Edge Detection for Interior Design," in 2019 International Conference on Information and Communication Technology Convergence (ICTC), 2019, pp. 597-601.
Vikas Palakonda and Rammohan Mallipeddi, "KnEA with Ensemble Approach for Parameter Selection for Many-Objective Optimization," in International Conference on Bio-Inspired Computing: Theories and Applications, 2019, pp. 703-713.
Vikas Palakonda and Rammohan Mallipeddi, "MOEA with Approximate Nondominated Sorting Based on Sum of Normalized Objectives," in Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing, ed: Springer, 2019, pp. 70-78.
Vikas Palakonda, Noor H. Awad, Rammohan Mallipeddi, Mortaza. Z. Ali, Kalyana C. Veluvolu, and P N Suganthan, "Differential Evolution with Stochastic Selection for Uncertain Environments: A Smart Grid Application," in 2018 IEEE Congress on Evolutionary Computation (CEC), 2018, pp. 1-7.
Vikas Palakonda, Samira Ghorbanpour, and Rammohan Mallipeddi, "Pareto dominance-based MOEA with multiple ranking methods for many-objective optimization," in 2018 IEEE Symposium Series on Computational Intelligence (SSCI), 2018, pp. 958-964.
Samira Ghorbanpour, Vikas Palakonda, and Rammohan Mallipeddi, "Ensemble of Pareto-based Selections for Many-objective optimization," in 2018 IEEE Symposium Series on Computational Intelligence (SSCI), 2018, pp. 981-988.
Vikas Palakonda, Trinadh Pamulapati, Rammohan Mallipeddi, Partha P. Biswas, and Kalyana. C. Veluvolu, "Nondominated sorting based on sum of objectives," in 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017, pp. 1-8.
Vikas Palakonda and Rammohan Mallipeddi, “Iterative sorting based Nondominated sorting for bi-objective optimization”, in 1st International conference on Smart Computing and Informatics, 2017.
Vikas Palakonda and Rammohan Mallipeddi, "Rank-based Nondomination Set Identification with Preprocessing," in 7th International Conference on Advances in Swarm Intelligence, ed, 2016, pp. 150-157.