Tharun Reddy

Google Scholar page

Reviewer duties

  • Reviewed Papers for:
    • Review Editor for Frontiers in Neuroscience
    • IEEE Signal Processing Letters
    • IEEE Transactions on Emerging Topics in Computational Intelligence
    • IEEE Transactions on Artificial Intelligence
    • IEEE Transactions on Pattern Analysis and Machine Intelligence
    • IEEE Transactions on Neural Systems and Rehabilitation Engineering
    • IEEE Journal of Biomedical and Health Informatics
    • IEEE Transactions on Fuzzy Systems
    • IEEE Transactions on Neural Networks and Learning Systems
    • IEEE Transactions on Automation Science and Engineering
    • IEEE Access

Journal

  1. Behera, C.K., Reddy, T.K., Behera, L., Birbaumer, N. and Ika, K., 2023. A Meditation Based Cognitive Therapy (HMBCT) for Primary Insomnia: A Treatment Feasibility Pilot Study. Applied Psychophysiology and Biofeedback,pp.1-10.
  2. Tharun Kumar Reddy and Laxmidhar Behera 2022/1, ‘Driver Drowsiness Detection using Intelligent BCI ’ IEEE Systems, Man and Cybernetics Magazine, 8(1), pp.16-28.https://ieeexplore.ieee.org/document/9690567
  3. Reddy, T.K., Arora, V., Gupta, V., Biswas, R. and Behera, L., 2021. EEG-Based Drowsiness Detection With Fuzzy Independent Phase-Locking Value Representations Using Lagrangian-Based Deep Neural Networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(1), pp.101-111.
  4. Kumar, S., Reddy, T.K. and Behera, L., 2019. Divergence Framework for EEG based Multiclass Motor Imagery Brain Computer Interface. arXiv preprint arXiv:1901.07457.
  5. Reddy, T.K., Arora, V., Kumar, S., Behera, L., Wang, Y.K. and Lin, C.T., 2019. Electroencephalogram based reaction time prediction with differential phase synchrony representations using co-operative multi-task deep neural networks. IEEE Transactions on Emerging Topics in Computational Intelligence, 3(5), pp.369-379.IEEE Transactions
  6. Tharun Kumar Reddy, Vipul Arora, Rupam Biswas, Vinay Gupta and Laxmidhar Behera, ‘EEG Based Drowsiness Detection With Fuzzy Independent Phase Locking Value Representations Using Lagrangian Based Deep Neural Networks’ in second review round at IEEE transactions on Systems, Man and Cybernetics.
  7. Reddy, T.K., Arora, V., Behera, L., Wang, Y.K. and Lin, C.T., 2019. Multiclass Fuzzy Time-Delay Common Spatio-Spectral Patterns With Fuzzy Information Theoretic Optimization for EEG-Based Regression Problems in Brain–Computer Interface (BCI.IEEE Transactions on Fuzzy Systems, 27(10), pp.1943-1951.IEEE Transactions on Fuzzy Systems
  8. Reddy, T.K., Arora, V. and Behera, L., 2018. HJB-equation-based optimal learning scheme for neural networks with applications in the brain–computer interface. IEEE Transactions on Emerging Topics in Computational Intelligence, 4(2), pp.159-170.IEEE Transactions on Emerging Topics in Computational Intelligence

Conferences

  1. S. K. Varun, T. K. Reddy, S. Shrestha, “Automatic seizure detection employing machine learning-based late fusion techniques over behind-the-ear and the scalp EEG signals,” 2023 IEEE India Council International Subsections Conference (INDISCON), Mysuru, India, 2023, pp. 1-4. (has been accepted for an oral presentation).
  2. Vivek Singh, Tharun Kumar Reddy, “EEG-based Reaction Time prediction with Fuzzy Common Spatial Patterns and Phase Cohesion using Deep Autoencoder based data fusion”, 2023 IEEE India Council International Subsections Conference (INDISCON) IEEE, 2023 (has been accepted for an oral presentation on 15/06/2023).
  3. S. Singh V. Gupta, S.K. Varun, T.K. Reddy and V. Arora, “EEG Based Mental Workload Classification Using End To End Riemannian Geometry and Restricted Boltzmann Machine based Data Fusion” submitted at ICONIP 2022
  4. Reddy, Tharun Kumar, Yu-Kai Wang, CT Lin and Javier Andreu-Perez. ‘Joint Approximate Diagonalization Divergence based scheme for EEG Drowsiness Detection Brain Computer Interfaces.’ accepted as an oral presentation paper at Fuzz-IEEE 2021, Luxembourg), 2021.
  5. Tharun Kumar Reddy, Vipul Arora, Laxmidhar Behera, Yu-Kai Wang and CT Lin, ‘Optimal cooperative learning and spatial filtering with deep neural networks in EEG reaction time prediction for drowsiness estimation’, presented at BCI meeting 2021 (top tier conference in brain computer interfaces, held once in two-three years) June, Brussels, Belgium.
  6. Tushar P. Kendre, Tharun K. Reddy, Madhur D. Jain, Satyam Kumar and Laxmidhar Behera, ‘Online SSVEP based Controller using Adaptive Riemannian Geometry’, presented at BCI meeting 2021 (top tier conference in brain computer interfaces, held once in two-three years) June, Brussels, Belgium.
  7. Passive BCI Hackathon NEC-2021 Submission of team-iBCI, S Singh, V Gupta, TK Reddy, V Arora - presented at NEC, Nov 2021
  8. Reddy, Tharun Kumar, Vipul Arora, Laxmidhar Behera, Yukai Wang, and CT Lin. ‘Fuzzy Divergence Based Analysis For EEG Drowsiness Detection Brain Computer Interfaces.’ published as an oral presentation paper at FUZZ-IEEE 2020 (Glasgow, UK),IEEE WCCI, 2020.
  9. Satyam Kumar, Tharun Kumar Reddy, Laxmidhar Behera, ‘Formulating Divergence Framework for Multiclass Motor Imagery EEG Brain Computer Interface’, published as a paper in the proceedings of IEEE conference on Acoustics, Speech and Signal Processing (ICASSP), 14 May 2020
  10. Reddy, Tharun Kumar, Vinay Gupta, and Laxmidhar Behera. ‘Autoencoding Convolutional Representations for Real-Time Eye-Gaze Detection.’ In Computational Intelligence: Theories, Applications and Future Directions Volume II, pp. 229-238. Springer, Singapore, 2019.
  11. Satyam Kumar, Tharun Kumar Reddy, Laxmidhar Behera, ‘EEG based motor imagery classification using instan-taneous phase difference sequence’, published in the proceedings at IEEE conference on Systems, Man and Cybernetics, 2018
  12. Arora, Vipul, Laxmidhar Behera, Tharun Kumar Reddy, and Ajay Pratap Yadav. ‘HJB equation based learning scheme for neural networks.’ In 2017 International Joint Conference on Neural Networks (IJCNN), pp. “2298– 2305”. IEEE, 2017.
  13. Reddy, Tharun Kumar, and Laxmidhar Behera. ‘Online eye state recognition from EEG data using deep architectures.’ In 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 000712-000717. IEEE, 2016.
  14. Behera, Chandan Kumar, Tharun Kumar Reddy, Laxmidhar Behera, and Bishakh Bhattacarya. ‘Artificial neural network based arousal detection from sleep electroencephalogram data.’ In 2014 International Conference on Computer, Communications, and Control Technology (I4CT), pp. 458-462. IEEE, 2014.
  15. V. Gupta, T. Kendre, T.K. Reddy and V.Arora, ‘Comparative Performance Analysis of Scalp EEG and Ear EEG Based P300 Ambulatory Brain-Computer Interfaces Using Riemannian Geometry and Convolutional Neural Networks.’ accepted and presented In 2022 IEEE, National conference on communications
  16. V. Gupta, S. Swaminathan, T.K.Reddy, ‘Performance Study of Neural Structured Learning Using Riemannian Features for BCI Classification.’ accepted and presented In 2022 IEEE, National conference on communications
  17. Swati Singh, Vinay Gupta, T.K. Reddy, ‘Meditation and Cognitive Enhancement: A Machine Learning Based Classification Using EEG’ submitted at IEEE SMC 2022
  18. Singh, Vivek, and Tharun Kumar Reddy. “Eeg-based reaction time prediction with fuzzy common spatial patterns and phase cohesion using deep autoencoder based data fusion.” 2023 IEEE 4th Annual Flagship India Council International Subsections Conference (INDISCON). IEEE, 2023.
  19. K. Gaurav, S. D. Reddy and T. Kumar Reddy, “Entropy based EEG irregularity quantification in Single-Channel SSVEP-based BCIs,” 2023 IEEE Silchar Subsection Conference (SILCON), Silchar, India, 2023, pp. 1-6, doi: 10.1109/SILCON59133.2023.10404149.
  20. S. D. Reddy, K. Gaurav and T. K. Reddy, “Schizophrenia and Bipolar Psychosis Classification with rsfMRI Functional Connectivity Feature Fusion technique using Super Learner,” 2023 IEEE Silchar Subsection Conference (SILCON), Silchar, India, 2023, pp. 1-6, doi: 10.1109/SILCON59133.2023.10404202.

Book Chapters

  1. A. Kumar Chaudhary, V. Gupta, K. Gaurav, T. Kumar Reddy, and L. Behera, ‘EEG Control of a Robotic Wheelchair’, Human-Robot Interaction - Perspectives and Applications. IntechOpen, May 10, 2023. doi: 10.5772/intechopen.110679.

  2. “Riemannian Deep Feature Fusion with auto-encoder for MEG Depression Classification in Smart Healthcare applications” chapter in the book entitled “Data Fusion Techniques and Applications for Smart Healthcare” to be published by Book Series Intelligent Data-Centric Systems, Elsevier. (In Press)

  3. “Regularized Riemannian-based Intelligent System for Dementia Screening using MEG Signals “ chapter in the book Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing to be published by CRC Press. (In Press)
  4. “Machine Learning for Health 4.0” in Application of ML and AI in Engineering and healthcare, NOAA Academic Publishers. In Review.
  5. “Epileptic Spike Localization using MEG MRI modality Fusion for Intelligent Smart Healthcare” in Data Fusion Techniques and Applications for Smart Healthcare, edited by Stefano Berretti and Amit Kumar Singh, part of the book series Intelligent Data-Centric Systems, Book Series Intelligent Data-Centric Systems, Elsevier.

Patents

Systems and methods for sensor integration and control of a brain controlled wheelchair.
(in process)