Swagatam Das

28.6k citations

388 papers · 20.2k indexed · 11 hit papers · h-index 64

Artificial Intelligence top 0.02%
Computational Theory and Mathematics top 0.01%
Electrical and Electronic Engineering top 1%
Control and Systems Engineering top 0.2%
Computer Vision and Pattern Recognition top 0.2%

Co-authors: Ponnuthurai Nagaratnam Suganthan Amit Konar Ajith Abraham Sankha Subhra Mullick Uday K. Chakraborty Shounak Datta Subhodip Biswas Boyang Qu
Topics: Metaheuristic Optimization Algorithms Research (164 papers)Advanced Multi-Objective Optimization Algorithms (121 papers)Evolutionary Algorithms and Applications (117 papers)
Cited by: Computational Theory and Mathematics Artificial Intelligence Computer Vision and Pattern Recognition
Journals: SHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine Intelligence European Journal of Operational Research
Partner nations: India United States Singapore

In The Last Decade

Swagatam Das

377 papers receiving 19.5k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Differential Evolution: A Survey of the State-of-the-Art

2010 3.9k citations Swagatam Das, Ponnuthurai Nagaratnam Suganthan profile →
Recent advances in differential evolution – An updated survey

2016 1.2k citations Swagatam Das, Sankha Subhra Mullick et al. profile →
Differential Evolution Using a Neighborhood-Based Mutation Operator

2009 919 citations Swagatam Das, Ajith Abraham et al. profile →
Automatic Clustering Using an Improved Differential Evolution Algorithm

2007 561 citations Swagatam Das, Ajith Abraham et al. profile →
An Adaptive Differential Evolution Algorithm With Novel Mutation and Crossover Strategies for Global Numerical Optimization

2011 492 citations Swagatam Das, Ponnuthurai Nagaratnam Suganthan et al. profile →
Bio-inspired computation: Where we stand and what's next

2019 438 citations Swagatam Das, Ponnuthurai Nagaratnam Suganthan et al. profile →
A test-suite of non-convex constrained optimization problems from the real-world and some baseline results

2020 380 citations Abhishek Kumar, Rammohan Mallipeddi et al. profile →
A Distance-Based Locally Informed Particle Swarm Model for Multimodal Optimization

2012 330 citations Ponnuthurai Nagaratnam Suganthan, Swagatam Das et al. profile →
An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges

2023 287 citations Swagatam Das et al. profile →
A Benchmark-Suite of real-World constrained multi-objective optimization problems and some baseline results

2021 177 citations Abhishek Kumar, Rammohan Mallipeddi et al. profile →
Reinforcement learning-assisted evolutionary algorithm: A survey and research opportunities

2024 52 citations Ponnuthurai Nagaratnam Suganthan, Swagatam Das et al. profile →

Peers

Countries citing papers authored by Swagatam Das

Since Specialization

Citations

This map shows the geographic impact of Swagatam Das's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Swagatam Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Swagatam Das more than expected).

Fields of papers citing papers by Swagatam Das

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Swagatam Das. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Swagatam Das. The network helps show where Swagatam Das may publish in the future.

Co-authorship network of co-authors of Swagatam Das

This figure shows the co-authorship network connecting the top 25 collaborators of Swagatam Das. A scholar is included among the top collaborators of Swagatam Das based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Swagatam Das. Swagatam Das is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Investigating the microstructure and mechanical properties of L-shaped structure of TM-B9 HSLA steels using WAAM process 2025 ·Results in Surfaces and Interfaces ·Rakesh Chaudhari,(unknown),(unknown),(unknown),Swagatam Das,Jay Vora,Subraya Krishna Bhat	1
2	From constraints fusion to manifold optimization: A new directional transport manifold metaheuristic algorithm 2024 ·Information Fusion ·Václav Snåšel,Lingping Kong,Swagatam Das	2
3	Exploring the Horizons of Meta-Learning in Neural Networks: A Survey of the State-of-the-Art 2024 ·IEEE Transactions on Emerging Topics in Computational Intelligence ·(unknown),Swalpa Kumar Roy,Swagatam Das,Paramartha Dutta	0
4	Into a Deeper Understanding of Evolutionary Computing: Exploration, Exploitation, and Parameter Control 2024 ·Abdul Halim,Swagatam Das,Idris Ismail	1
5	Advances in Data-Driven Computing and Intelligent Systems 2023 ·Lecture notes in networks and systems ·Swagatam Das,Snehanshu Saha,Carlos A. Coello Coello,Jagdish Chand Bansal	1
6	UEQMS: UMAP Embedded Quick Mean Shift Algorithm for High Dimensional Clustering 2023 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Abhishek Kumar,Swagatam Das,Rammohan Mallipeddi	2
7	Two-Phase Evolutionary Convolutional Neural Network Architecture Search for Medical Image Classification 2023 ·IEEE Access ·(unknown),Nanda Dulal Jana,Swagatam Das,Rammohan Mallipeddi	16
8	Robust Principal Component Analysis: A Median of Means Approach 2023 ·IEEE Transactions on Neural Networks and Learning Systems ·(unknown),(unknown),Swagatam Das	8
9	Implicit Annealing in Kernel Spaces: A Strongly Consistent Clustering Approach 2022 ·IEEE Transactions on Pattern Analysis and Machine Intelligence ·(unknown),(unknown),Swagatam Das,Jason Xu	3
10	Impact of chaotic dynamics on the performance of metaheuristic optimization algorithms: An experimental analysis 2021 ·Information Sciences ·Ivan Zelinka,(unknown),Václav Snåšel,Swagatam Das,Giacomo Innocenti,A. Tesi,Fabio Schoen,Н. В. Кузнецов	20
11	On the uniform concentration bounds and large sample properties of clustering with Bregman divergences 2021 ·Stat ·(unknown),(unknown),Swagatam Das	3
12	Self-Organizing Migrating Algorithm with narrowing search space strategy for robot path planning 2021 ·Applied Soft Computing ·(unknown),Thanh Cong Truong,Swagatam Das,Ivan Zelinka	10
13	Detecting Meaningful Clusters From High-Dimensional Data: A Strongly Consistent Sparse Center-Based Clustering Approach 2020 ·IEEE Transactions on Pattern Analysis and Machine Intelligence ·(unknown),Swagatam Das	34
14	Boosting with Lexicographic Programming: Addressing Class Imbalance without Cost Tuning 2019 ·IEEE Transactions on Knowledge and Data Engineering ·Shounak Datta,(unknown),Swagatam Das	29
15	Self-Organizing Migrating Algorithm Pareto 2019 ·SHILAP Revista de lepidopterología ·(unknown),Ivan Zelinka,Swagatam Das	11
16	On the strong consistency of feature‐weighted k‐means clustering in a nearmetric space 2019 ·Stat ·(unknown),Swagatam Das	8
17	Multiobjective Support Vector Machines: Handling Class Imbalance With Pareto Optimality 2018 ·IEEE Transactions on Neural Networks and Learning Systems ·Shounak Datta,Swagatam Das	32
18	Adaptive Learning-Based $k$ -Nearest Neighbor Classifiers With Resilience to Class Imbalance 2018 ·IEEE Transactions on Neural Networks and Learning Systems ·Sankha Subhra Mullick,Shounak Datta,Swagatam Das	98
19	Evolutionary multiobjective optimization in dynamic environments: A set of novel benchmark functions 2014 ·Subhodip Biswas,Swagatam Das,Ponnuthurai Nagaratnam Suganthan,Carlos A. Coello Coello	62
20	An Intelligent Lossless Data Compressor Implementation using Reconfigurable Hardware. 2011 ·J. Inf. Hiding Multim. Signal Process. ·(unknown),Amit Konar,Swagatam Das,Ajith Abraham	2

About Swagatam Das

Swagatam Das is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 388 papers that have together received 20.2k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (164 papers), Advanced Multi-Objective Optimization Algorithms (121 papers) and Evolutionary Algorithms and Applications (117 papers). The work is most often cited by research in Computational Theory and Mathematics (6.8k citations), Artificial Intelligence (12.0k citations) and Computer Vision and Pattern Recognition (2.6k citations). Swagatam Das has collaborated with scholars based in India, United States and Singapore. Frequent co-authors include Ponnuthurai Nagaratnam Suganthan, Amit Konar, Ajith Abraham, Sankha Subhra Mullick, Uday K. Chakraborty, Shounak Datta, Subhodip Biswas, Boyang Qu, Sambarta Dasgupta and Arijit Biswas. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and European Journal of Operational Research.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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