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Dr. E. A. Gopalakrishnan

Associate Professor, Center for Computational Engineering & Networking

Qualification: B-Tech, M.Tech, Ph.D
ea_gopalakrishnan@cb.amrita.edu
Orcid ID
Google Scholar Profile
Scopus Author ID
Research Interest: Combustion Instabilities, Complex Systems, Nonlinear Dynamics and Stochastic Systems

Bio

Dr. Gopalakrishnan joined the Center for Computational Engineering & Networking in 2016 after completing his PhD from Indian Institute of Technology Madras. Dr. Gopalakrishnan obtained his B-Tech (Hons) in Mechanical Engineering from University of Calicut and did his M-Tech in Engineering Design from Amrita School of Engineering Coimbatore.

His research interests are Complex Systems, Nonlinear Dynamics, Stochastic Systems and Artificial Intelligence. He is currently pursuing research in the application of AI tools to detect transitions that occur in a variety of complex systems such as stock markets, human body, climate systems, power grids etc. Dr. Gopalakrishnan has published articles in prestigious journals such as Nature Scientific Reports, Journal of Fluid Mechanics, Proceedings of Combustion Institute, Physical Review E, IEEE Transactions, Chaos etc.

Dr. Gopalakrishnan has established an active collaboration with globally renowned scientists Prof. Jurgen Kurths and Prof. Elena Surovyatkina (Potsdam Institute, Berlin, Germany). Further he has an active collaboration with Dr. Vivek Mohan (NIT Trichy), Dr. Sirshendu Mondal (NIT Durgapur) and Dr. Venkatramani Jagadish (SNU, Delhi).

Publications

Journal Article

Year : 2021

Explainable Deep Learning-Based Approach for Multilabel Classification of Electrocardiogram

Cite this Research Publication : G. M., Vinayakumar Ravi, Sowmya V., Dr. E. A. Gopalakrishnan, and Dr. Soman K. P., “Explainable Deep Learning-Based Approach for Multilabel Classification of Electrocardiogram”, IEEE Transactions on Engineering Management (IF: 6.146 Citescore: 4.3 Q1: 76 percentile), pp. 1-13, 2021.

Publisher : IEEE Transactions on Engineering Management

Year : 2020

Explainable Artificial Intelligence for Heart Rate Variability in ECG Signal

Cite this Research Publication : Sowmya V., Sanjana, K., Gopalakrishnan, E. A., and Dr. Soman K. P., “Explainable Artificial Intelligence for Heart Rate Variability in ECG Signal”, Healthcare Technology Letters, vol. 7, no. 6, pp. 146 (IF:1.157, CiteScore: 3.1, Q2- 64 percentile), 2020.

Publisher : Healthcare Technology Letters

Year : 2020

Rate-induced transitions and advanced takeoff in power systems

Cite this Research Publication : K. S. Suchithra, Dr. E. A. Gopalakrishnan, Surovyatkina, E., and Kurths, J., “Rate-induced transitions and advanced takeoff in power systems”, Chaos: An Interdisciplinary Journal of Nonlinear ScienceChaos: An Interdisciplinary Journal of Nonlinear Science, vol. 30, no. 6, p. 061103, 2020.

Publisher : Chaos: An Interdisciplinary Journal of Nonlinear ScienceChaos: An Interdisciplinary Journal of Nonlinear Science, American Institute of Physics,

Year : 2020

Glottal Activity Detection from the Speech Signal Using Multifractal Analysis

Cite this Research Publication : Jyothish Lal G., Dr. E. A. Gopalakrishnan, and Dr. Govind D., “Glottal Activity Detection from the Speech Signal Using Multifractal Analysis”, Circuits, Systems, and Signal Processing, vol. 39, no. 4, pp. 2118 - 2150, 2020.

Publisher : Circuits, Systems, and Signal Processing

Year : 2019

Interplay Between Random Fluctuations and Rate Dependent Phenomena at Slow Passage to Limit-cycle Oscillations in a Bistable Thermoacoustic System

Cite this Research Publication : V. R. Unni, Dr. E. A. Gopalakrishnan, Syamkumar, K. S., Sujith, R. I., Surovyatkina, E., and Kurths, J., “Interplay Between Random Fluctuations and Rate Dependent Phenomena at Slow Passage to Limit-cycle Oscillations in a Bistable Thermoacoustic System”, Chaos, vol. 29, no. 3, p. 031102, 2019.

Publisher : Chaos

Year : 2018

Accurate Estimation of Glottal Closure Instants and Glottal Opening Instants from Electroglottographic Signal Using Variational Mode Decomposition

Cite this Research Publication : Jyothish Lal G., Dr. E. A. Gopalakrishnan, and Dr. Govind D., “Accurate Estimation of Glottal Closure Instants and Glottal Opening Instants from Electroglottographic Signal Using Variational Mode Decomposition”, Circuits, Systems, and Signal Processing, vol. 37, pp. 810–830, 2018.

Publisher : Circuits, Systems, and Signal Processing

Year : 2018

Epoch Estimation from Emotional Speech Signals Using Variational Mode Decomposition

Cite this Research Publication : Jyothish Lal G., Dr. E. A. Gopalakrishnan, and Dr. Govind D., “Epoch Estimation from Emotional Speech Signals Using Variational Mode Decomposition”, Circuits, Systems, and Signal Processing, vol. 37, pp. 3245–3274, 2018.

Publisher : Circuits, Systems, and Signal Processing

Year : 2017

Recurrence networks to study dynamical transitions in a turbulent combustor

Cite this Research Publication : V. Godavarthi, Unni, V. R., Dr. E. A. Gopalakrishnan, and Sujith, R. I., “Recurrence networks to study dynamical transitions in a turbulent combustor”, Chaos, vol. 27, 2017.

Publisher : Chaos, American Institute of Physics Inc

Year : 2017

Experimental investigation on preconditioned rate induced tipping in a thermoacoustic system

Cite this Research Publication : J. Tony, Subarna, S., Syamkumar, K. S., Sudha, G., Akshay, S., Dr. E. A. Gopalakrishnan, Surovyatkina, E., and Sujith, R. I., “Experimental investigation on preconditioned rate induced tipping in a thermoacoustic system”, Scientific Reports, vol. 7, 2017.

Publisher : Scientific Reports, Nature Publishing Group,

Year : 2016

Stochastic Bifurcations In A Prototypical Thermoacoustic System

Cite this Research Publication : Dr. E. A. Gopalakrishnan, Tony, J., Sreelekha, E., and Sujith, R. I., “Stochastic Bifurcations In A Prototypical Thermoacoustic System”, Phys. Rev. E, vol. 94, no. 2, 2016.

Publisher : Phys. Rev. E

Year : 2016

Early warning signals for critical transitions in a thermoacoustic system

Cite this Research Publication : Dr. E. A. Gopalakrishnan, Yogita, S., Tony, J., Dutta, P., and Sujith, R. I., “Early warning signals for critical transitions in a thermoacoustic system”, Scientific Reports Nature, In Press, 2016.

Publisher : Scientific Reports Nature, In Press.

Year : 2015

Effect of external noise on the hysteresis characteristics of a thermoacoustic system

Cite this Research Publication : Dr. E. A. Gopalakrishnan and Sujith, R. I., “Effect of external noise on the hysteresis characteristics of a thermoacoustic system”, Journal of Fluid Mechanics, vol. 776, pp. 334-353, 2015.

Publisher : Journal of Fluid Mechanics

Year : 2015

Detecting Deterministic Nature Of Pressure Measurements From A Turbulent Combustor

Cite this Research Publication : J. Tony, Dr. E. A. Gopalakrishnan, Sreelekha, E., and Sujith, R. I., “Detecting Deterministic Nature Of Pressure Measurements From A Turbulent Combustor”, Physical Review E, vol. 92, no. 6, 2015.

Publisher : Physical Review E

Year : 2014

Influence of System Parameters on the Hysteresis Characteristics of a Horizontal Rijke Tube

Cite this Research Publication : Dr. E. A. Gopalakrishnan and Sujith, R. I., “Influence of System Parameters on the Hysteresis Characteristics of a Horizontal Rijke Tube”, International Journal of Spray and Combustion Dynamics , vol. 6, pp. 293-316, 2014.

Publisher : International Journal of Spray and Combustion Dynamics

Conference Paper

Year : 2021

Performance Improvement of Deep Residual Skip Convolution Neural Network for Atrial Fibrillation Classification

Cite this Research Publication : S. K., Sowmya, V., Gopalakrishnan, E. A., and Dr. Soman K. P., “Performance Improvement of Deep Residual Skip Convolution Neural Network for Atrial Fibrillation Classification”, in Evolution in Computational Intelligence, Singapore, 2021.

Publisher : Springer Singapore

Year : 2021

Noise Reduction of ECG using Chebyshev filter and Classification using Machine Learning Algorithms

Cite this Research Publication : B. M. Prakash, V, S., A, G. E., and Dr. Soman K. P., “Noise Reduction of ECG using Chebyshev filter and Classification using Machine Learning Algorithms”, in 2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), Greater Noida, India, 2021.

Publisher : IEEE

Year : 2020

An Approach to Detect and Classify Defects in Cantilever Beams Using Dynamic Mode Decomposition and Machine Learning

Cite this Research Publication : K. Nagarajan, Ananthu, J., Menon, V. Krishna, Dr. Soman K. P., Gopalakrishnan, E. A., and Dr. Ajith Ramesh, “An Approach to Detect and Classify Defects in Cantilever Beams Using Dynamic Mode Decomposition and Machine Learning”, in Smart Innovation, Systems and Technologies, Singapore, 2020.

Publisher : Springer Singapore

Year : 2019

Rate Dependent Transitions in Power Systems

Cite this Research Publication : K. S. Suchithra and Dr. E. A. Gopalakrishnan, “Rate Dependent Transitions in Power Systems”, in Proceedings of the Conference on the Industrial and Commercial Use of Energy, ICUE, 2019, vol. 2018-October.

Publisher : Proceedings of the Conference on the Industrial and Commercial Use of Energy, ICUE

Year : 2019

A Data-Driven Model Approach for DayWise Stock Prediction

Cite this Research Publication : N. A. Unnithan, Dr. E. A. Gopalakrishnan, Menon, V. Krishna, and Dr. Soman K. P., “A Data-Driven Model Approach for DayWise Stock Prediction”, in Emerging Research in Electronics, Computer Science and Technology, Singapore, 2019, vol. 545, pp. 149-158.

Publisher : Springer Singapore

Year : 2019

Part-of-Speech Tagger for Biomedical Domain Using Deep Neural Network Architecture

Cite this Research Publication : A. Gopalakrishnan, Dr. Soman K. P., and B. Premjith, “Part-of-Speech Tagger for Biomedical Domain Using Deep Neural Network Architecture”, in 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Kanpur, India, 2019.

Publisher : 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT)

Year : 2019

A complex network approach for plant growth analysis using images

Cite this Research Publication : Sajith Variyar V. V., Dr. E. A. Gopalakrishnan, Sowmya, and Dr. Soman K. P., “A complex network approach for plant growth analysis using images”, in Proceedings of the 2019 IEEE International Conference on Communication and Signal Processing, ICCSP 2019, Melmaruvathur; India, 2019.

Publisher : Proceedings of the 2019 IEEE International Conference on Communication and Signal Processing, ICCSP 2019

Year : 2018

NSE Stock Market Prediction Using Deep-Learning Models

Cite this Research Publication : H. M, Dr. E. A. Gopalakrishnan, Vijay Krishna Menon, and Dr. Soman K. P., “NSE Stock Market Prediction Using Deep-Learning Models”, in Procedia Computer Science, 2018, vol. 132, pp. 1351 - 1362.

Publisher : Procedia Computer Science,.

Year : 2017

Stock Price Prediction using LSTM, RNN and CNN-sliding Window Model

Cite this Research Publication : S. Selvin, Vinayakumar, R., Dr. E. A. Gopalakrishnan, Menon, V. K., and Dr. Soman K. P., “Stock Price Prediction using LSTM, RNN and CNN-sliding Window Model”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017.

Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

Year : 2017

A first order phase transition model for Rijke oscillations

Cite this Research Publication : Dr. E. A. Gopalakrishnan, Kumar, A., Verma, M. K., and Sujith, R. I., “A first order phase transition model for Rijke oscillations”, in Accepted for presentation in 24th International Congress on Sound & Vibration, London, 2017.

Publisher : Accepted for presentation in 24th International Congress on Sound & Vibration, London, 2017.

Year : 2017

Stock price prediction using dynamic mode decomposition

Cite this Research Publication : D. P. Kuttichira, Dr. E. A. Gopalakrishnan, Menon, V. K., and K. P. Soman, “Stock price prediction using dynamic mode decomposition”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.

Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

Year : 2017

Classification of states of bi-stable oscillator using deep learning

Cite this Research Publication : R. Mohan, Dr. E. A. Gopalakrishnan, and K. P. Soman, “Classification of states of bi-stable oscillator using deep learning”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.

Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI),

Year : 2017

Instantaneous heart rate as a robust feature for sleep apnea severity detection using deep learning

Cite this Research Publication : Rahul K Pathinarupothi, Vinaykumar R, Ekanath Srihari Rangan, Dr. E. A. Gopalakrishnan, and Dr. Soman K. P., “Instantaneous heart rate as a robust feature for sleep apnea severity detection using deep learning”, in IEEE International Conference on Biomedical and Health Informatics, Orlando, Florida, 2017, pp. 293-296.

Publisher : IEEE International Conference on Biomedical and Health Informatics, Orlando, Florida.

Year : 2015

Hybrid CFD/ low order modeling of thermoacoustic limit cycles

Cite this Research Publication : S. Jaensch, Merk, M., Dr. E. A. Gopalakrishnan, Bomberg, S., Emmert, T., Sujith, R. I., and Polifke, W., “Hybrid CFD/ low order modeling of thermoacoustic limit cycles”, in Sonderforschungsbereich/Transregio 40 – Summer Program Report 2015, 2015.

Publisher : Sonderforschungsbereich/Transregio 40 – Summer Program Report 2015 (2015)

Year : 2007

Interference effects on flow induced oscillations of rectangular cylinders

Cite this Research Publication : G. R. Sabareesh, Dr. E. A. Gopalakrishnan, Ajithkumar, R., and Gowda, B. H. L., “Interference effects on flow induced oscillations of rectangular cylinders”, in 12th International Conference on Wind Engineering and Industrial Aerodynamics, Cairns, Australia, 2007.

Publisher : 12th International Conference on Wind Engineering and Industrial Aerodynamics

Conference Proceedings

Year : 2016

Hybrid CFD/ low-order modeling of nonlinear thermoacoustic oscillations

Cite this Research Publication : S. Jaensch, Merk, M., Dr. E. A. Gopalakrishnan, Bomberga, S., Emmert, T., Sujith, R. I., and Polifke, W., “Hybrid CFD/ low-order modeling of nonlinear thermoacoustic oscillations”, 36th Combustion Symposium. 2016.

Publisher : 36th Combustion Symposium

Year : 2016

Early warning measures for tipping points in a thermoacoustic system

Cite this Research Publication : Dr. E. A. Gopalakrishnan, Sharma, Y., John, T., Dutta, P. Sharathy, and Sujith, R. I., “Early warning measures for tipping points in a thermoacoustic system”, Conference on Nonlinear Systems & Dynamics, December 16-18, IISER Kolkata. 2016.

Publisher : Conference on Nonlinear Systems & Dynamics,

Year : 2015

Hurst exponent and translation error as discriminating measures to identify the chaotic nature of an experimental time series

Cite this Research Publication : Dr. E. A. Gopalakrishnan, Tony, J., Sreelekha, E., and Sujith, R. I., “Hurst exponent and translation error as discriminating measures to identify the chaotic nature of an experimental time series”, Conference on Nonlinear Systems and Dynamics, Mar. 13-15, 2015, Mohali, India. 2015.

Publisher : Conference on Nonlinear Systems and Dynamics, Mar. 13-15, 2015, Mohali, India

Year : 2015

Hurst exponent and translation error as discriminating measures to identify a chaotic nature of an experimental time series

Cite this Research Publication : J. Tony, Dr. E. A. Gopalakrishnan, Sreelekha, E., and Sujith, R., “Hurst exponent and translation error as discriminating measures to identify a chaotic nature of an experimental time series”, Bifurcations and Instabilities in Fluid Dynamics, July 15-17, 2015, Paris, France. 2015.

Publisher : Bifurcations and Instabilities in Fluid Dynamics, July 15-17, 2015, Paris, France

Year : 2014

Noise induced transition in a horizontal Rijke tube

Cite this Research Publication : Dr. E. A. Gopalakrishnan and Sujith, R. I., “Noise induced transition in a horizontal Rijke tube”, 10th European Fluid Mechanics Conference, Sep. 14-18, 2014, Copenhagen, Denmark. 2014.

Publisher : 10th European Fluid Mechanics Conference, Sep. 14-18, 2014, Copenhagen, Denmark

Year : 2014

Influence of external noise on the nature of transition of a thermoacoustic system

Cite this Research Publication : Dr. E. A. Gopalakrishnan and Sujith, R. I., “Influence of external noise on the nature of transition of a thermoacoustic system”, Dynamic Days Asia Pacific-08, July 21-24, 2014, Chennai, India. Chennai, India, 2014.

Publisher : Dynamic Days Asia Pacific-08, July 21-24, 2014, Chennai, India

Year : 2013

Influence of system parameters and external noise on hysteresis characteristics of a horizontal Rijke tube.

Cite this Research Publication : Dr. E. A. Gopalakrishnan and Sujith, R. I., “Influence of system parameters and external noise on hysteresis characteristics of a horizontal Rijke tube.”, n3l - Int’l Summer School and Workshop on Non-Normal and Nonlinear Effects in Aero- and Thermoacoustics, June 18-21, 2013, Munich, Germany. Munich, Germany, 2013.



Publisher : n3l - Int’l Summer School and Workshop on Non-Normal and Nonlinear Effects in Aero- and Thermoacoustics, June 18-21, 2013, Munich, Germany.

Book Chapter

Year : 2020

Transferable Approach for Cardiac Disease Classification using Deep Learning

Cite this Research Publication : P. Gopika, Sowmya V., Gopalakrishnan, E. A., and Dr. Soman K. P., “Transferable Approach for Cardiac Disease Classification using Deep Learning”, in Deep Learning Techniques for Biomedical and Health Informatics, B. Agarwal, Balas, V. Emilia, Jain, L. C., Poonia, R. Chandra, and Manisha,, Eds. Academic Press, 2020, pp. 285-303, Academic Press.

Publisher : Deep Learning Techniques for Biomedical and Health Informatics, Academic Press

Year : 2020

Single-layer Convolution Neural Network for Cardiac Disease Classification using Electrocardiogram Signals

Cite this Research Publication : P. Gopika, Krishnendu, C. S., M. Chandana, H., Ananthakrishnan, S., Sowmya V., Gopalakrishnan, E. A., and Soman, K. P., “Single-layer Convolution Neural Network for Cardiac Disease Classification using Electrocardiogram Signals”, in Deep Learning for Data Analytics, H. Das, Pradhan, C., and Dey, N., Eds. Academic Press, 2020, pp. 21-35, Academic Press.

Publisher : Deep Learning for Data Analytics, Academic Press

Year : 2019

A Deep Learning Approach for Patch-based Disease Diagnosis from Microscopic Images

Cite this Research Publication : A. Simon, Vinayakumar, R., Sowmya V., Soman, K. Padannayil, and Gopalakrishnan, E. Anathanara, “A Deep Learning Approach for Patch-based Disease Diagnosis from Microscopic Images”, in Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis, N. Dey, Ed. Academic Press, 2019, pp. 109-127, Academic Press.

Publisher : Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis, Academic Press

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