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Dr. Mrinalini Bhagawati

Assistant Professor, Department of Electronics and Communication Engineering, School of Engineering, Amaravati.

Qualification: Ph.D
m_bhagawati@av.amrita.edu
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Research Interest: AI in Healthcare, Biomedical Engineering, Computational Biology, Biomedical Instrumentation,

Bio Publications Research Talks Invited Talks Membership Awards Conferences
Bio

Dr. Mrinalini Bhagawati currently serves as Assistant Professor at Department of Electronics and Communication Engineering, School of Engineering, Amaravati.

Dr. Mrinalini Bhagawati is a biomedical engineering academic and researcher specializing in Artificial Intelligence for healthcare and biomedical applications. She holds a PhD in Biomedical Engineering and has extensive research experience in cardiovascular disease risk stratification and AI-driven clinical decision support. With 23 Scopus/SCI-indexed publications and teaching experience, she is passionate about integrating computational intelligence with biomedical sciences. Her interests include AI in healthcare, medical image analysis, computational biology, and data-driven biomedical research.

Publications

Journal Article

Year : 2025

Attention-based hybrid deep learning models and its scientific validation for cardiovascular disease risk stratification

Cite this Research Publication : Mrinalini Bhagawati, Siddharth Gupta, Sudip Paul, Laura Mantella, Amer M. Johri, John R. Laird, Ekta Tiwari, Narendra N. Khanna, Andrew Nicolaides, Rajesh Singh, Mustafa Al-Maini, Luca Saba, Jasjit S. Suri, Attention-based hybrid deep learning models and its scientific validation for cardiovascular disease risk stratification, Biomedical Signal Processing and Control, Elsevier BV, 2025, https://doi.org/10.1016/j.bspc.2025.107824

Publisher : Elsevier BV

Year : 2024

Cardiovascular Disease Risk Stratification Using Hybrid Deep Learning Paradigm: First of Its Kind on Canadian Trial Data

Cite this Research Publication : Mrinalini Bhagawati, Sudip Paul, Laura Mantella, Amer M. Johri, Siddharth Gupta, John R. Laird, Inder M. Singh, Narendra N. Khanna, Mustafa Al-Maini, Esma R. Isenovic, Ekta Tiwari, Rajesh Singh, Andrew Nicolaides, Luca Saba, Vinod Anand, Jasjit S. Suri, Cardiovascular Disease Risk Stratification Using Hybrid Deep Learning Paradigm: First of Its Kind on Canadian Trial Data, Diagnostics, MDPI AG, 2024, https://doi.org/10.3390/diagnostics14171894

Publisher : MDPI AG

Year : 2024

Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort

Cite this Research Publication : Mrinalini Bhagawati, Sudip Paul, Laura Mantella, Amer M. Johri, John R. Laird, Inder M. Singh, Rajesh Singh, Deepak Garg, Mostafa M. Fouda, Narendra N. Khanna, Riccardo Cau, Ajith Abraham, Mostafa Al-Maini, Esma R. Isenovic, Aditya M. Sharma, Jose Fernandes E. Fernandes, Seemant Chaturvedi, Mannudeep K. Karla, Andrew Nicolaides, Luca Saba, Jasjit S. Suri, Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort, The International Journal of Cardiovascular Imaging, Springer Science and Business Media LLC, 2024, https://doi.org/10.1007/s10554-024-03100-3

Publisher : Springer Science and Business Media LLC

Year : 2023

Cardiovascular disease/stroke risk stratification in deep learning framework: a review

Cite this Research Publication : Mrinalini Bhagawati, Sudip Paul, Sushant Agarwal, Athanasios Protogeron, Petros P. Sfikakis, George D. Kitas, Narendra N. Khanna, Zoltan Ruzsa, Aditya M. Sharma, Omerzu Tomazu, Monika Turk, Gavino Faa, George Tsoulfas, John R. Laird, Vijay Rathore, Amer M. Johri, Klaudija Viskovic, Manudeep Kalra, Antonella Balestrieri, Andrew Nicolaides, Inder M. Singh, Seemant Chaturvedi, Kosmas I. Paraskevas, Mostafa M. Fouda, Luca Saba, Jasjit S. Suri, Cardiovascular disease/stroke risk stratification in deep learning framework: a review, Cardiovascular Diagnosis and Therapy, AME Publishing Company, 2023, https://doi.org/10.21037/cdt-22-438

Publisher : AME Publishing Company

Year : 2023

UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias

Cite this Research Publication : Jasjit S. Suri, Mrinalini Bhagawati, Sushant Agarwal, Sudip Paul, Amit Pandey, Suneet K. Gupta, Luca Saba, Kosmas I. Paraskevas, Narendra N. Khanna, John R. Laird, Amer M. Johri, Manudeep K. Kalra, Mostafa M. Fouda, Mostafa Fatemi, Subbaram Naidu, UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias, IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), 2023, https://doi.org/10.1109/access.2022.3232561

Publisher : Institute of Electrical and Electronics Engineers (IEEE)

Year : 2022

A Powerful Paradigm for Cardiovascular Risk Stratification Using Multiclass, Multi-Label, and Ensemble-Based Machine Learning Paradigms: A Narrative Review

Cite this Research Publication : Jasjit S. Suri, Mrinalini Bhagawati, Sudip Paul, Athanasios D. Protogerou, Petros P. Sfikakis, George D. Kitas, Narendra N. Khanna, Zoltan Ruzsa, Aditya M. Sharma, Sanjay Saxena, Gavino Faa, John R. Laird, Amer M. Johri, Manudeep K. Kalra, Kosmas I. Paraskevas, Luca Saba, A Powerful Paradigm for Cardiovascular Risk Stratification Using Multiclass, Multi-Label, and Ensemble-Based Machine Learning Paradigms: A Narrative Review, Diagnostics, MDPI AG, 2022, https://doi.org/10.3390/diagnostics12030722

Publisher : MDPI AG

Year : 2022

Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review

Cite this Research Publication : Jasjit S. Suri, Mrinalini Bhagawati, Sudip Paul, Athanasios Protogeron, Petros P. Sfikakis, George D. Kitas, Narendra N. Khanna, Zoltan Ruzsa, Aditya M. Sharma, Sanjay Saxena, Gavino Faa, Kosmas I. Paraskevas, John R. Laird, Amer M. Johri, Luca Saba, Manudeep Kalra, Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review, Computers in Biology and Medicine, Elsevier BV, 2022, https://doi.org/10.1016/j.compbiomed.2021.105204

Publisher : Elsevier BV

Research Talks

Contributed as a Resource Person cum Speaker at the One Week ISTE Approved Online Workshop on “EMERGING SIGNIFICANCE OF ARTIFICIAL INTELLIGENCE IN BIOMEDICAL, INDUSTRY 5.0, CYBERSECURITY & DIGITAL FORENSICS” from August 26th – 31st, 2024, Jointly Organized by the ‘Computer, Electronics & Computer, Instrumentation & Mechanical Engineering Department’ of ‘VPM’s Maharshi Parshuram College of Engineering, Velneshwar.

Invited Talks

Contributed as a Resource Person cum Speaker at the One Week ISTE Approved Online Workshop on “EMERGING SIGNIFICANCE OF ARTIFICIAL INTELLIGENCE IN BIOMEDICAL, INDUSTRY 5.0, CYBERSECURITY & DIGITAL FORENSICS” from August 26th – 31st, 2024, Jointly Organized by the ‘Computer, Electronics & Computer, Instrumentation & Mechanical Engineering Department’ of ‘VPM’s Maharshi Parshuram College of Engineering, Velneshwar.

Membership

Indian Academy of Neuroscience, IEEE, World Women in Neuroscience

Awards

Awards

  • IAN Travel Award

Conferences

  • List is attached separately below.
Conferences
  • Bhagawati, M., & Paul, S. (2025, December 17–19). Cardiovascular Disease Risk Prediction in Bidirectional Deep Learning Paradigm [Paper accepted for presentation]. International Conference on Recent Advances in Medical Science and Technology (RedMed-2025), Indian Institute of Technology Kharagpur, India.
  • Presented at the 5th International Conference on Innovative Trends in Information Technology (ICITIIT) organized by IIIT Kottayam, Keralam, in 2024.
  • Presented at the 2nd International Conference on Data, Electronics, and Computing (ICDEC) organized by Mizoram University and NIT Mizoram, Aizawl, in 2023.
  • Presented in the 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) organized by AMITY University, Nodia in 2021.
  • Participated in the 3-day International Conference on “Drug Discovery” organized by BITS- Pilani, Hyderabad, in 2020.
  • Attended a national workshop on “Molecular Crystallography” organized by the Centre for Bioinformatics, Pondicherry University, Puducherry in 2019.
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