Assistant Professor
Ph.D. in Biomedical Signal Processing
Indian Institute of Technology Kharagpur, Kharagpur
Email:kasturibarik.iitkgp@gmail.com
LinkedIn:https://www.linkedin.com/in/kasturi-barik-094b7966/
GoogleScholar:https://scholar.google.com/citations?user=CzXQz5sAAAAJ&hl=en
Ph.D.:Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur
M.S. (by Research):Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur
B.Tech.:Department of Electronics and Communication Engineering,
West Bengal University of Technology, West Bengal
Professional Engagements:
April 2024 – Present: Assistant Professor, Centre for Data Science, JIS Institute of Advanced Studies and Research, Kolkata, India.
January – April 2019; 2020; 2021; 2022; 2023: Teaching Assistant, NPTEL SWAYAM, India.
April 2015 – June 2018: Junior Project Officer (JPO), IIT Kharagpur, Ministry of Human Resource Development, Govt. of India (MHRD), India.
November 2013–March2015: Junior Project Officer (JPO), IIT Kharagpur, Ministry of Health and Family Welfare, Govt.of India (MoHFW), India.
Research Topics:
Neuro-signal processing, Machine learning, Bio-medical signal, Statistical methods, Deep learning, Cognitiveneuroscience, Pattern recognition, Digital SignalProcessing.
Summary of Research Activities:
- Machine Learning Approach for Autism Detection in Young Children using Magnetoencephalogram Signals
- Acquired domain knowledge of physiology of neuro-signals and manifestation of Autism in them.
- To study and analyze how the underlying neural mechanisms of autistic children differ from normal childrenusing MEG signals based on machine learning framework.
- Proposed a novel phase-based spectral domain feature which performed better than power spectral densitybased feature to identify autistic children, using a pattern classification approach.
- Using the complementary characteristics of power and phase based feature, fusion based model is analyzed inthe autism detection.
- To identify the possible cortical spatial pattern behind the autism spectral disorder, we have introduced commonspatial pattern (CSP) based machine learning approach for autism detection in young children.
- Introduced envelop of imaginary coherence and proposed envelop of complex coherency functional connectivityanalysis using complex coherency based features to understand the interactions between different brain regionsof a neural system.
Awards & Achievements:
- Awarded fellowship from Ministry of HRD, Govt. of India for PhD (July 2018- June 2023).
- Awarded GATE fellowship from Ministry of HRD, Govt. of India for M.Tech (May 2013- November 2013).
- Reviewer of Medical & Biological Engineering & Computing (MBEC), Springer.
- Reviewer of Frontiers in Psychiatry, Frontiers.
- Served as Vice Chair of IEEE Signal Processing Society, Student Branch Chapter, IIT Kharagpur (2021 tenure).
- Served as Treasurer of IEEE Signal Processing Society, Student Branch Chapter, IIT Kharagpur (2020 tenure).
Publications:
Journal:
- Barik, K., Daimi, S. N., Jones, R., Bhattacharya, J., and Saha, G., 2019. “A machine learning approach to predict perceptual decisions: an insight into face pareidolia”. Brain Informatics, 6 (1), pp.1-16. SpringerOpen.
- Barik, K., Watanabe, K., Bhattacharya, J. and Saha, G., 2022. A fusion-based machine learning approach for autism detection in young children using magnetoencephalography signals. Journal of Autism and Developmental Disorders, pp.1-19.
- Barik, K., Watanabe, K., Bhattacharya, J. and Saha, G., 2023. Functional connectivity based machine learning approach for autism detection in young children using MEG signals. Journal of Neural Engineering.
Conferences:
- Barik, K., Watanabe, K., Bhattacharya, J., and Saha, G., 2020, “Classification of autism in young children by phase angle clustering in magnetoencephalogram signals”. In 2020 Twenty Sixth National Conference on Communications (NCC), IIT Kharagpur, India, 21-23 February, (pp. 1-6). IEEE.
- Barik, K., Jones, R., Bhattacharya, J., and Saha, G., 2019, “Investigating the Influence of Prior Expectation in Face Pareidolia using Spatial Pattern”. International Conference on Machine Intelligence and Signal Processing (MISP), IIT Indore, India, (pp. 437-451). Machine Intelligence and Signal Analysis, Springer.
- Barik, K., Daimi, S. N., Jones, R., Saha, G., and Bhattacharya, J., 2017, “Seeing faces in noise: Predicting perceptual decision by prestimulus brain oscillations”. International Workshop on Brain Dynamics on Multiple Scales, Dresden, Germany, 19-23 June, (Poster).
- Barik, K., Watanabe, K., Hirosawa, T., Yoshimura, Y., Kikuchi, M., Bhattacharya, J., and Saha, G., 2023, “Autism detection in Children using Common Spatial Patterns of MEG signals”. In 45th IEEE Engineering in Medicine & Biology Society (EMBC), pp. 1-4. Sydney, Australia, 24-28 July 2023.
Saha, U., Barik, K., De, A., 2023, “Fusion of Spectral and Connectivity Features to Detect Depressive Disorder using EEG Signals”. In 3rd IEEE Conference on Applied Signal Processing (ASPCON), West Bengal, India, 25-26 November 2023.
- “Hybridization of Fuzzy Theory and Nature-Inspired Optimization for Medical Report Summarization”, Nature-Inspired Optimization
Methodologies in Biomedical and Health Care, 2022
Journal:
- “Evolutionary Algorithm based Ensemble Extractive Summarization for Developing Smart Medical System”, Interdisciplinary Sciences: Computational Life Sciences 2021.
DOI : https://doi.org/10.1007/s12539-020-00412-5
- “Ensemble summarization of bio-medical articles integrating clustering and multi-objective evolutionary algorithms”, Applied Soft Computing, 2021
DOI : https://doi.org/10.1016/j.asoc.2021.107347
Conferences:
- “An Unsupervised COVID-19 Report Summarizer for Developing Smart Healthcare System”, Computational Intelligence in Pattern Recognition 2021. ISBN : 978-981-16-25 43-5
- “A Game Theoretic Approach on Semantic Segmentation Along with Transfer Learning”, Computational Intelligence in Pattern Recognition, 2021. ISBN : 978-981-16-2543-5
- “Deep learning-based automated feature engineering for rice leaf disease prediction”, Computational Intelligence in Pattern Recognition 2020. DOI : https://doi.org/10.1007/978-981-15-2449-3_11
- “A graph based approach on extractive summarization”, Emerging Technologies in Data Mining and Information Security 2019. DOI: https://doi.org/10.1007/978-981-13-1498-8_16}
- “Extractive summarization of a document using lexical chains”, Soft Computing in Data Analytics, 2019. DOI : https://doi.org/10.1007/978-981-13-0514-6_78
- “Graph-based text summarization using modified TextRank”, Soft Computing in Data Analytics, 2019. DOI : https://doi.org/10.1007/978-981-13-0514-6_14