World's Best Scientists 2026 revealed!
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Computer Science
India
2026

D-Index & Metrics

Computer Science

D-Index
82
Citations
32582
World Ranking
946
National Ranking
8

Research.com Recognitions

  • 2026 - Research.com Computer Science in India Leader Award
  • 2025 - Research.com Computer Science in India Leader Award
  • 2023 - Research.com Computer Science in India Leader Award
  • 2022 - Research.com Computer Science in India Leader Award

Overview

Swagatam Das is affiliated with the Indian Statistical Institute in India, focusing primarily on research within the domain of Computer Science. Their work spans multiple subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Electrical and Electronic Engineering, and Radiology, Nuclear Medicine and Imaging.

The main topics of research conducted by Swagatam Das cover metaheuristic optimization algorithms, advanced multi-objective optimization algorithms, evolutionary algorithms and applications, advanced clustering algorithms, face and expression recognition, Bayesian methods and mixture models, and adversarial robustness in machine learning.

Frequent co-authors collaborating with Swagatam Das include Rammohan Mallipeddi, Saptarshi Chakraborty, Debolina Paul, Arkaprabha Basu, and Abhishek Kumar.

Swagatam Das has published extensively, with notable papers including:

  • A test-suite of non-convex constrained optimization problems from the real-world and some baseline results, 2020, Swarm and Evolutionary Computation
  • An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges, 2023, Artificial Intelligence Review
  • Performance assessment of the metaheuristic optimization algorithms: an exhaustive review, 2020, Artificial Intelligence Review
  • A Benchmark-Suite of real-World constrained multi-objective optimization problems and some baseline results, 2021, Swarm and Evolutionary Computation
  • Reinforcement learning-assisted evolutionary algorithm: A survey and research opportunities, 2024, Swarm and Evolutionary Computation

Swagatam Das's work appears in several publication venues with the highest publication counts in:

  • arXiv (Cornell University)
  • IEEE Transactions on Emerging Topics in Computational Intelligence
  • Swarm and Evolutionary Computation
  • Applied Soft Computing
  • IEEE Access

In addition to research articles, Swagatam Das has contributed to scholarly books published by major scientific publishers. Notable publishers include Springer Nature, Springer Science+Business Media, Springer International Publishing, and Artificial intelligence-enhanced software and systems engineering. Titles authored encompass topics such as communication and intelligent systems, evolutionary computing, networks and autonomous systems analytics, swarm and evolutionary computing, fuzzy and neural computing, and software engineering metaheuristic techniques. Some specific books include:

  • Recent Trends in Communication and Intelligent Systems (2020, 2022, 2023), Springer Nature
  • Applications of Networks, Sensors and Autonomous Systems Analytics (2021), Springer Nature
  • Into a Deeper Understanding of Evolutionary Computing: Exploration, Exploitation, and Parameter Control (2024), Springer Nature
  • Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing (2020), Springer Science+Business Media
  • Machine Learning and Metaheuristics Algorithms, and Applications (2020), Springer Science+Business Media
  • Advances in Data-Driven Computing and Intelligent Systems (2023, 2024), Springer International Publishing
  • Meta Heuristic Techniques in Software Engineering and Its Applications (2022), Artificial intelligence-enhanced software and systems engineering

Best Publications

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

    S Das;P N Suganthan

  • Recent advances in differential evolution – An updated survey

    Swagatam Das;Sankha Subhra Mullick;Ponnuthurai N. Suganthan

  • Differential Evolution Using a Neighborhood-Based Mutation Operator

    S. Das;A. Abraham;U.K. Chakraborty;A. Konar

  • Automatic Clustering Using an Improved Differential Evolution Algorithm

    S. Das;A. Abraham;A. Konar

  • Recent Trends in the Use of Statistical Tests for Comparing Swarm and Evolutionary Computing Algorithms: Practical Guidelines and a Critical Review

    Jacinto Carrasco;Salvador García;María del Mar Rueda;S. Das

  • An Adaptive Differential Evolution Algorithm With Novel Mutation and Crossover Strategies for Global Numerical Optimization

    S. M. Islam;S. Das;S. Ghosh;S. Roy

  • Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications

    Swagatam Das;Arijit Biswas;Sambarta Dasgupta;Ajith Abraham

  • Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Perspectives

    Swagatam Das;Ajith Abraham;Amit Konar

  • Bio-inspired computation: Where we stand and what's next

    Javier Del Ser;Javier Del Ser;Eneko Osaba;Daniel Molina;Xin-She Yang

  • An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges

    Unknown

  • Two improved differential evolution schemes for faster global search

    Swagatam Das;Amit Konar;Uday K. Chakraborty

  • A test-suite of non-convex constrained optimization problems from the real-world and some baseline results

    Abhishek Kumar;Guohua Wu;Mostafa Z. Ali;Rammohan Mallipeddi

  • A Distance-Based Locally Informed Particle Swarm Model for Multimodal Optimization

    B. Y. Qu;Ponnuthurai Nagaratnam Suganthan;S. Das

  • Design of fractional-order PIλDµ controllers with an improved differential evolution

    Arijit Biswas;Swagatam Das;Ajith Abraham;Sambarta Dasgupta

  • Real-parameter evolutionary multimodal optimization — A survey of the state-of-the-art

    Swagatam Das;Sayan Maity;Bo-Yang Qu;Ponnuthurai Nagaratnam Suganthan

  • Adaptive Computational Chemotaxis in Bacterial Foraging Optimization: An Analysis

    S. Dasgupta;S. Das;A. Abraham;A. Biswas

  • Exploratory Power of the Harmony Search Algorithm: Analysis and Improvements for Global Numerical Optimization

    S Das;A Mukhopadhyay;A Roy;A Abraham

  • Multi-sensor data fusion using support vector machine for motor fault detection

    Tribeni Prasad Banerjee;Swagatam Das

  • Synergy of PSO and Bacterial Foraging Optimization — A Comparative Study on Numerical Benchmarks

    Arijit Biswas;Sambarta Dasgupta;Swagatam Das;Ajith Abraham

  • Performance assessment of the metaheuristic optimization algorithms: an exhaustive review

    A. Hanif Halim;Idris Ismail;Swagatam Das

  • Automatic kernel clustering with a Multi-Elitist Particle Swarm Optimization Algorithm

    Swagatam Das;Ajith Abraham;Amit Konar

  • Automatic image pixel clustering with an improved differential evolution

    Swagatam Das;Amit Konar

Frequent Co-Authors

Ajith Abraham
Ajith Abraham Sai University
Amit Konar
Amit Konar Jadavpur University
Bijaya Ketan Panigrahi
Bijaya Ketan Panigrahi Indian Institute of Technology Delhi
Athanasios V. Vasilakos
Athanasios V. Vasilakos University of Agder
Vaclav Snasel
Vaclav Snasel VSB – Technical University of Ostrava
Rammohan Mallipeddi
Rammohan Mallipeddi Kyungpook National University
Zhihua Cui
Zhihua Cui Taiyuan University of Science and Technology

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