Hi! 👋
I am a Postdoctoral Researcher in Geospatial Artificial Intelligence (GeoAI) at the Convergence Geospatial Intelligence Lab, Kumoh National Institute of Technology, South Korea. My research focuses on Artificial Intelligence, with particular emphasis on Neural Network Optimization, Edge AI, Evolutionary AI, Multi-objective Optimization, Federated Learning, and Computer Vision. I develop efficient and interpretable AI systems that address complex real-world problems.
Previously, I worked as a Postdoctoral Researcher at Kyungpook National University, South Korea (2021–2025), where I also earned my Ph.D. from the School of Electronics and Electrical Engineering in 2021, with my doctoral research focused on multi-objective evolutionary algorithms. I also hold an M.Sc. from the same university.
Updates
- Jun 2026: Paper on Symbolic Regression survey accepted in Archives of Computational Methods in Engineering
- Mar 2026: Serving as Guest Editor for Special Issue on Data Mining in Graph Neural Networks, Big Data and Cognitive Computing (MDPI)
- Dec 2025: Paper on multi-objective federated learning published in CAAI Transactions on Intelligence Technology
- Aug 2025: Paper on deep compression for split computing published in IEEE Transactions on Vehicular Technology
- Apr 2025: Paper on metaheuristics for CNN pruning published in Expert Systems with Applications
- Nov 2024: Paper on radial-grid multi-objective differential evolution published in Scientific Reports
Background
Work Experience
February 2026 - Present
Postdoctoral Researcher
Convergence Geospatial Intelligence Lab, Kumoh National Institute of Technology, South Korea
Research Focus: Geospatial Artificial Intelligence (GeoAI), neural network optimization, Edge AI, evolutionary AI, and multi-objective optimization
April 2024 - January 2026
Postdoctoral Researcher
Department of Mathematics, Kyungpook National University, South Korea
Research Focus: Mathematical optimization frameworks, hybrid intelligent systems, symbolic regression, and federated learning with evolutionary computation
April 2021 - February 2024
Postdoctoral Researcher
Department of Artificial Intelligence, Kyungpook National University, South Korea
Research Focus: Multi/many-objective evolutionary algorithms, ensemble optimization methods, neural network pruning, and computer vision applications (OCR, defect detection, data augmentation)
Education
Ph.D. in Electronics and Electrical Engineering
Kyungpook National University, South Korea (2017-2021)
Thesis: Multi-objective Evolutionary Algorithms with Application to Community Network Detection
GPA: 3.80/4.30
M.Sc. in Electronic Engineering
Kyungpook National University, South Korea (2015-2017)
Thesis: Sorting-based Techniques for Pareto-dominance based Multi-objective Optimization
GPA: 4.10/4.30
B.Tech in Electronics and Communication Engineering
GMR Institute of Technology, India (2011-2015)
Project: Anti-Symmetric Biorthogonal Wavelet Based Image Edge Detection
Aggregate: 83.07%
Publications
Journal Articles (18)
A Comprehensive Survey on Symbolic Regression: State-of-the-Art Approaches, Key Applications, Benchmark Evaluations, and Future Research Directions
Archives of Computational Methods in Engineering, early access
2026 • V. Palakonda, S. Ghorbanpour, S. Yun, I.-M. Kim, J.-M. Kang, S. MoonQ1 Top 1%IF: 12.9
Metaheuristics for pruning convolutional neural networks: A comparative study
Expert Systems with Applications, vol. 262, p. 126326
2025 • V. Palakonda, J. Tursunboev, J.-M. Kang, S. MoonQ1IF: 7.5
Multi-objective optimisation framework for heterogeneous federated learning
CAAI Transactions on Intelligence Technology
2025 • J. Tursunboev, V. Palakonda, I.-M. Kim, S. Moon, J.-M. KangQ1IF: 7.3
DeCo-MeSC: Deep compression-based memory-constrained split computing framework
IEEE Transactions on Vehicular Technology
2025 • M. Sung, V. Palakonda, I.-M. Kim, S. Yun, J.-M. KangQ1IF: 7.1
External archive guided radial-grid multi objective differential evolution
Scientific Reports, vol. 14, no. 1, p. 29006
2024 • V. Palakonda, S. Ghorbanpour, J.-M. Kang, H. JungQ1IF: 3.9
Clustering-aided grid-based one-to-one selection-driven evolutionary algorithm
IEEE Access, vol. 12, pp. 120612–120623
2024 • V. Palakonda, J.-M. Kang, H. JungQ2IF: 3.6
OCR-diff: A two-stage deep learning framework for OCR using diffusion model in IIoT
IEEE Internet of Things Journal, vol. 11, no. 15, pp. 25997–26000
2024 • C.-W. Park, V. Palakonda, S. Yun, I.-M. Kim, J.-M. KangQ1IF: 8.9
Multi-objective evolutionary hybrid deep learning for energy theft detection
Applied Energy, vol. 363, p. 122847
2024 • J. Tursunboev, V. Palakonda, J.-M. KangQ1IF: 11.0
Benchmarking real-world many-objective problems: A problem suite with baseline results
IEEE Access
2024 • V. Palakonda, J.-M. Kang, H. JungQ2IF: 3.6
Enhanced non-maximum suppression for the detection of steel surface defects
Mathematics, vol. 11, no. 18, p. 3898
2023 • S.-H. Kang, V. Palakonda, I.-M. Kim, J.-M. Kang, S. YunQ2IF: 2.2
RandMixAugment: A novel unified technique for region-and image-level data augmentations
IEEE Access
2023 • Y. Shin, V. Palakonda, et al.Q2IF: 3.6
Many-objective real-world engineering problems: A comparative study
IEEE Access
2023 • V. Palakonda, J.-M. KangQ2IF: 3.6
Pre-DEMO: Preference-inspired differential evolution for multi/many-objective optimization
IEEE Transactions on Systems, Man, and Cybernetics: Systems
2023 • V. Palakonda, J.-M. KangQ1IF: 8.7
An effective ensemble framework for many-objective optimization based on AdaBoost and K-means
Expert Systems with Applications, vol. 227, p. 120278
2023 • V. Palakonda, J.-M. Kang, H. JungQ1IF: 7.5
An adaptive neighborhood based evolutionary algorithm with pivot-solution based selection
Information Sciences, vol. 607, pp. 126–152
2022 • V. Palakonda, J.-M. Kang, H. JungQ1IF: 6.8
An ensemble approach with external archive for multi-and many-objective optimization
Information Sciences, vol. 555, pp. 164–197
2021 • V. Palakonda, R. Mallipeddi, P. N. SuganthanQ1IF: 6.8
An evolutionary algorithm for multi and many-objective optimization with adaptive mating
IEEE Access, vol. 8, pp. 82781–82796
2020 • V. Palakonda, R. MallipeddiQ2IF: 3.6
Pareto dominance-based algorithms with ranking methods for many-objective optimization
IEEE Access, vol. 5, pp. 11043–11053
2017 • V. Palakonda, R. MallipeddiQ2IF: 3.6
Conference Papers (11)
An generational SDE based indicator for multi and many-objective optimization
ICAIIC, IEEE, pp. 203–209
2021 • J. Yusupov, V. Palakonda, S. Ghorbanpour, R. Mallipeddi, K. C. Veluvolu
Multi-objective evolutionary algorithm based on ensemble of initializations for community detection
ICEIC, IEEE, pp. 1–7
2021 • J. Yusupov, V. Palakonda, R. Mallipeddi, K. C. Veluvolu
KnEA with ensemble approach for parameter selection for many-objective optimization
BIC-TA, Springer, pp. 703–713
2020 • V. Palakonda, R. Mallipeddi
MOEA with approximate nondominated sorting based on sum of normalized objectives
SEMCCO, Springer, pp. 70–78
2020 • V. Palakonda, R. Mallipeddi
Differential evolutionary (DE) based interactive recoloring based on YUV based edge detection
ICTC, IEEE, pp. 597–601
2019 • F. W. Ramlan, V. Palakonda, R. Mallipeddi
Ensemble of Pareto-based selections for many-objective optimization
IEEE SSCI, pp. 981–988
2018 • S. Ghorbanpour, V. Palakonda, R. Mallipeddi
Differential evolution with stochastic selection for uncertain environments: A smart grid application
IEEE CEC, pp. 1–7
2018 • V. Palakonda, N. H. Awad, R. Mallipeddi, M. Z. Ali, K. C. Veluvolu, P. N. Suganthan
Pareto dominance-based MOEA with multiple ranking methods for many-objective optimization
IEEE SSCI, pp. 958–964
2018 • V. Palakonda, S. Ghorbanpour, R. Mallipeddi
Iterative sorting-based non-dominated sorting algorithm for bi-objective optimization
SCI, Springer, pp. 133–141
2018 • V. Palakonda, R. Mallipeddi
Nondominated sorting based on sum of objectives
IEEE SSCI, pp. 1–8
2017 • V. Palakonda, T. Pamulapati, R. Mallipeddi, P. P. Biswas, K. C. Veluvolu
Rank-based nondomination set identification with preprocessing
ICSI, Springer, pp. 150–157
2016 • V. Palakonda, R. Mallipeddi
Skills & Activities
Technical Skills
Programming
PythonMATLABC/C++Java
AI/ML Tools
TensorFlowPyTorchscikit-learnOpenCV
Other Tools
GitLaTeXLinux/UnixHPC
Soft Skills
Research LeadershipTechnical WritingMentoringPresentation
Professional Activities
Editorial Activities
- 2026: Guest Editor, Special Issue on Data Mining in Graph Neural Networks, Big Data and Cognitive Computing (MDPI) — co-edited with Samira Ghorbanpour
- 2023-2025: Guest Editor, Special Issue on Machine Learning and AI with Applications, Information Journal
- 2023-2024: Guest Editor, Special Issue on AI-Based Mathematical Modeling Optimization, AIMS Mathematics Journal
Reviewer for Journals (22+)
IEEE Trans. Evolutionary Computation
IEEE Trans. Systems, Man, and Cybernetics
IEEE Trans. Neural Networks and Learning Systems
IEEE Computational Intelligence Magazine
IEEE Trans. Emerging Topics in Computing
IEEE Access
Swarm and Evolutionary Computation
Information Sciences
Applied Soft Computing
Expert Systems with Applications
Neural Networks
Neurocomputing
Artificial Intelligence Reviews
Journal of Machine Learning and Cybernetics
Journal of Big Data
Scientific Reports
Cluster Computing
Evolutionary Intelligence
The Journal of Supercomputing
Memetic Computing
Teaching Experience
Signals and Systems
Teaching Assistant
March 2018 - June 2018 | Kyungpook National University
Conducted tutorial sessions, graded assignments, and assisted students with MATLAB implementations
Logic Circuits
Teaching Assistant
March 2017 - June 2017 | Kyungpook National University
Assisted in lab sessions, evaluated circuit designs, and provided guidance to students
How to Write Research Papers
Teaching Assistant
September 2015 - January 2016 | Kyungpook National University
Provided feedback on draft papers, taught LaTeX typesetting, guided students on scientific writing
