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Computer Science

D-Index
47
Citations
9485
World Ranking
6462
National Ranking
66

Overview

Sundaram Suresh is affiliated with the Indian Institute of Science in India and has made contributions primarily in the field of Computer Science. Their research spans several subfields including Computer Vision and Pattern Recognition, Computer Networks and Communications, Neurology, Artificial Intelligence, and Biomedical Engineering.

Their work addresses a variety of topics centered on Context-Aware Activity Recognition Systems, Neurological disorders and treatments, IoT and Edge/Fog Computing, Epilepsy research and treatment, Non-Invasive Vital Sign Monitoring, Anomaly Detection Techniques and Applications, and EEG and Brain-Computer Interfaces.

Among their recent papers are:

  • DeepTransHHAR: Inter-subjects Heterogeneous Activity Recognition Approach in the Non-identical Environment Using Wearable Sensors (2022, National Academy Science Letters)
  • Deep-HAR: an ensemble deep learning model for recognizing the simple, complex, and heterogeneous human activities (2023, Multimedia Tools and Applications)
  • Efficacy of neuromodulation of the pulvinar nucleus for drug-resistant epilepsy (2025, Epilepsia)
  • DeepTransHAR: a novel clustering-based transfer learning approach for recognizing the cross-domain human activities using GRUs (Gated Recurrent Units) Networks (2023, Internet of Things)
  • FLAAP: An Open Human Activity Recognition (HAR) Dataset for Learning and Finding the Associated Activity Patterns (2022, Procedia Computer Science)

Frequent publication venues for Sundaram Suresh include:

  • National Academy Science Letters
  • Multimedia Tools and Applications
  • Procedia Computer Science
  • IETE Technical Review
  • SN Computer Science

Their frequent co-authors include Prabhat Kumar, Sandipan Pati, Ganne Chaitanya, Nisha Singh, and Yosefa A. Modiano. Collaboration with these researchers reflects ongoing multi-author efforts primarily in activity recognition and related systems.

Best Publications

  • Reversible Watermarking Algorithm Using Sorting and Prediction

    V. Sachnev;Hyoung Joong Kim;Jeho Nam;S. Suresh

  • Self regulating particle swarm optimization algorithm

    M.R. Tanweer;S. Suresh;N. Sundararajan

  • No-reference image quality assessment using modified extreme learning machine classifier

    S. Suresh;R. Venkatesh Babu;H. J. Kim

  • Particle swarm optimization approach for multi-objective composite box-beam design

    S. Suresh;P.B. Sujit;A.K. Rao

  • Performance enhancement of extreme learning machine for multi-category sparse data classification problems

    S. Suresh;S. Saraswathi;N. Sundararajan

  • Multi-UAV Oxyrrhis Marina-Inspired Search and Dynamic Formation Control for Forest Firefighting

    K. Harikumar;J. Senthilnath;Suresh Sundaram

  • Human action recognition using Meta-Cognitive Neuro-Fuzzy Inference System

    K. Subramanian;S. Suresh

  • Prediction of unconfined compressive strength of soft grounds using computational intelligence techniques: A comparative study

    B.S. Narendra;P.V. Sivapullaiah;S. Suresh;S.N. Omkar

  • Risk-sensitive loss functions for sparse multi-category classification problems

    S. Suresh;N. Sundararajan;P. Saratchandran

  • A sequential learning algorithm for self-adaptive resource allocation network classifier

    S. Suresh;Keming Dong;H. J. Kim

  • Meta-cognitive Neural Network for classification problems in a sequential learning framework

    G. Sateesh Babu;S. Suresh

  • Lift coefficient prediction at high angle of attack using recurrent neural network

    S. Suresh;S.N. Omkar;V. Mani;T.N. Guru Prakash

  • A Metacognitive Neuro-Fuzzy Inference System (McFIS) for Sequential Classification Problems

    Kartick Subramanian;Sundaram Suresh;Narasimhan Sundararajan

  • A fully complex-valued radial basis function network and its learning algorithm.

    Ramaswamy Savitha;Sundaram Suresh;N. Sundararajan

  • A meta-cognitive sequential learning algorithm for neuro-fuzzy inference system

    K. Subramanian;S. Suresh

  • Parallel implementation of back-propagation algorithm in networks of workstations

    S. Suresh;S.N. Omkar;V. Mani

  • Identification of crack location and depth in a cantilever beam using a modular neural network approach

    S Suresh;S N Omkar;Ranjan Ganguli;V Mani

  • Sequential Projection-Based Metacognitive Learning in a Radial Basis Function Network for Classification Problems

    G. S. Babu;S. Suresh

  • Metacognitive learning in a fully complex-valued radial basis function neural network

    R. Savitha;S. Suresh;N. Sundararajan

  • No-reference JPEG-image quality assessment using GAP-RBF

    R. Venkatesh Babu;S. Suresh;Andrew Perkis

Frequent Co-Authors

Narasimhan Sundararajan
Narasimhan Sundararajan Nanyang Technological University
R. Venkatesh Babu
R. Venkatesh Babu Indian Institute of Science
Narasimalu Srikanth
Narasimalu Srikanth Nanyang Technological University
Monique Thonnat
Monique Thonnat French Institute for Research in Computer Science and Automation - INRIA
François Brémond
François Brémond French Institute for Research in Computer Science and Automation - INRIA
Yun Q. Shi
Yun Q. Shi New Jersey Institute of Technology
Hyoung Joong Kim
Hyoung Joong Kim Korea University
Mahardhika Pratama
Mahardhika Pratama University of South Australia
D. Roy Mahapatra
D. Roy Mahapatra Indian Institute of Science
Jianliang Wang
Jianliang Wang Beihang University

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