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Dr. Mahesh Maindarkar

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Dr. Mahesh Maindarkar

Dr. Mahesh Maindarkar

Associate Professor

Overview

Dr. Mahesh Maindarkar is a researcher and academic with a strong background in Biomedical and Electronics Engineering, specializing in computer vision, machine learning, and deep learning applications. His research focuses on developing AI-driven systems for real-time cardiovascular disease (CVD) risk assessment, particularly in patients with complex comorbidities such as Parkinson’s disease,COVID-19, diabetes, chronic kidney disease, and rheumatoid arthritis. He has also contributed to robotics-assisted vascular interventions, including angioplasty. Beyond healthcare, Dr. Maindarkar’s work spans data science, machine learning, deep learning, and computer vision across multidisciplinary domains. His expertise includes AI model development, statistical analysis, pattern recognition, bioelectromagnetics, and health economics.

Qualifications
  • Post-Doctoral Research Associate in Artificial Intelligence-Biomedical Engineering, North Eastern Hill University (Central University, Government of India), Shillong, Meghalaya, India.| 2022
  • Doctor of Philosophy in Electronics and Communication Engineering from Oriental University, Indore,India | 2020.
  • Master of Engineering in Digital Communications from Dr. Babasaheb Ambedkar Marathwada University, Chhatrapati Sambhajinagar, India |2012
  • Bachelor of Engineering in Electronics Engineering from Shivaji University, Kolhapur, India | 2009
Teaching: 13 years
Industry: 1 years
Research: 3 years

Publications

International Journals

  • Bhongale, M., Maindarkar, M., Vyas, A. et al. Patch-based U-NET model and MSqueezeNet-PyramidNet for efficient segmentation and classification of tuberculosis, pneumonia, and COVID-19. Multimed Tools Appl (2025). https://doi.org/10.1007/s11042-025-20788-0. (Q1)
  • Kumari, V., Katiyar, A., Bhagawati, M., Maindarkar, M., Gupta, S., Paul, S., Chhabra, T., Boi, A., Tiwari, E., Rathore, V. and Singh, I.M., 2025. Transformer and Attention-Based Architectures for Segmentation of Coronary Arterial Walls in Intravascular Ultrasound: A Narrative Review. Diagnostics, 15(7), p.848.
  • Mahesh Maindarkar, Narendra N. Khanna, Anudeep Puvvula, Gavino Faa, Esma Isenovic, Amer Johri, Mostafa M. Fouda, Ekta Tiwari, Manudeep K. Kalra, Jasjit S. Suri. An Artificial Intelligence-Based Non-Invasive Approach for Cardiovascular Disease Risk Stratification in Obstructive Sleep Apnea Patients: A Narrative Review. Rev. Cardiovasc. Med. 2024, 25(12), 463. (Q2)
  • Tiwari, E., Shrimankar, D., Maindarkar, M. et al. Artificial intelligence-based cardiovascular/stroke risk stratification in women affected by autoimmune disorders: a narrative survey. Rheumatol Int 45, 14 (2025) (Q2)
  • Saba, L., Maindarkar, M., Johri, A.M., Mantella, L., Laird, J.R., Khanna, N.N., Paraskevas, K.I., Ruzsa, Z., Kalra, M.K., Fernandes, J.F.E. and Chaturvedi, S., 2024. UltraAIGenomics: Artificial Intelligence- Based Cardiovascular Disease Risk Assessment by Fusion of Ultrasound-Based Radiomics and GenomicsFeatures for Preventive, Personalized and Precision Medicine: A Narrative Review. Reviews in Cardiovascular Medicine, 25(5), p.184. (Q1)
  • Khanna NN, Singh M, Maindarkar M, Kumar A, Johri AM et al. “Polygenic Risk Score for Cardiovascular Diseases in Artificial Intelligence Paradigm: A Review.” J Korean Med Sci. 2023 Nov 27;38(46):e395. doi: 10.3346/jkms.2023.38.e395. PMID: 38013648; PMCID: PMC10681845. (Q1, Impact Factor:4.05)
  • Saba, Luca, Mahesh Maindarkar, Narendra N. Khanna, Amer M. Johri, Laura Mantella, John R. Laird, Kosmas I. Paraskevas et al. “A Pharmaceutical Paradigm for Cardiovascular Composite Risk Assessment Using Novel Radiogenomics Risk Predictors in Precision Explainable Artificial Intelligence Framework: Clinical Trial Tool.” Frontiers in Bioscience-Landmark 28, no. 10 (2023): 248. (Q1, Impact Factor:3.05).
  • Al-Maini, Mustafa, Mahesh Maindarkar, George D. Kitas, Narendra N. Khanna, Durga Prasanna Misra, Amer M. Johri, Laura Mantella et al. “Artificial intelligence-based preventive, personalized and precision medicine for cardiovascular disease/stroke risk assessment in rheumatoid arthritis patients: a narrative review.” Rheumatology International (2023): 1-18. (Q1, Impact Factor:4.02).
  • N. N. Khanna, M. A. Maindarkar, V. Viswanathan, J. F. E. Fernandes, S. Paul, M. Bhagawati, P. Ahluwalia, Z. Ruzsa, A. Sharma, and R. Kolluri, “Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment,” Healthcare, vol. 10, no. 12, p. 2493, 2022, (Q1, Impact Factor: 3.10). Received best paper award for the year 2022 by MDPI
  • N. N. Khanna, M. A. Maindarkar, V. Viswanathan, A. Puvvula, S. Paul, M. Bhagawati, P. Ahluwalia, Z. Ruzsa, A. Sharma, and R. Kolluri, “Cardiovascular/Stroke Risk Stratification in Diabetic Foot Infection Patients Using Deep Learning-Based Artificial Intelligence: An Investigative Study,” Journal of Clinical Medicine, vol. 11, no. 22, p. 6844, 2022, (Q1, Impact Factor: 5.01).
  • M. Kuanr, P. Mohapatra, S. Mittal, M. Maindarkar, M. M. Fouda, L. Saba, S. Saxena, and J. S. Suri, “Recommender System for the Efficient Treatment of COVID-19 Using a Convolutional Neural Network Model and Image Similarity,” J Diagnostics, vol. 12, no. 11, p. 2700, 2022, (Q1, Impact Factor: 3.99).
  • N. N. Khanna, M. Maindarkar, A. Puvvula, S. Paul, M. Bhagawati, P. Ahluwalia, Z. Ruzsa, A. Sharma,S. Munjral, and R. Kolluri, “Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report,” Journal of Cardiovascular Development Disease, vol. 9, no. 8, p. 268, 2022, (Q1, Impact Factor: 4.50).
  • J. S. Suri, M. A. Maindarkar, S. Paul, P. Ahluwalia, M. Bhagawati, L. Saba, G. Faa, S. Saxena, I. M. Singh, and P. S. Chadha, “Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson’s Disease Affected by COVID-19: A Narrative Review,” J Diagnostics, vol. 12, no. 7, p. 1543, 2022, (Q1, Impact Factor: 3.99).
  • N. N. Khanna, M. Maindarkar, A. Saxena, P. Ahluwalia, S. Paul, S. K. Srivastava, E. Cuadrado-Godia, Sharma, T. Omerzu, and L. Saba, “Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review,” J Diagnostics, vol. 12, no. 5, p. 1249, 2022, (Q1, Impact Factor: 3.99).
  • S. Munjral, M. Maindarkar, P. Ahluwalia, A. Puvvula, A. Jamthikar, T. Jujaray, N. Suri, S. Paul, R. Pathak, and L. Saba, “Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review,” J Diagnostics, vol. 12, no. 5, p. 1234, 2022, (Q1, Impact Factor: 3.99).
  • J. S. Suri, S. Paul, M. A. Maindarkar, A. Puvvula, S. Saxena, L. Saba, M. Turk, J. R. Laird, N. N. Khanna, K. Viskovic, I. M. Singh, M. Kalra, P. R. Krishnan, A. Johri, and K. I. Paraskevas, “Cardiovascular/Stroke Risk Stratification in Parkinson’s Disease Patients Using Atherosclerosis Pathway and Artificial Intelligence Paradigm: A Systematic Review,” Metabolite MDPI, vol. 12, no. 4, p. 312, 2022, (Q1, Impact Factor: 5.59).
  • S. Paul, M. Maindarkar, S. Saxena, L. Saba, M. Turk, M. Kalra, P. R. Krishnan, and J. S. Suri, “Bias Investigation in Artificial Intelligence Systems for Early Detection of Parkinson’s Disease: A Narrative Review,” Diagnostics, MDPI., vol. 12, no. 1, p. 166, 2022, (Q1, Impact Factor: 3.99).

International Conferences

  • M. A. Maindarkar, Dr. Pragya Nema “Different types of substrate material used in rectenna design for RF energy harvesting –A survey”, International Conference on Material and Environment Science (ICMES- 2018), Shivaji University, Kolhapur, India, 7th – 8th December 2018.
  • M. A. Maindarkar, Dr. Pragya Nema “A Feasibility Study on RF energy rectenna for upcoming Smart Cities in India”, National Conference on Sustainable development of Clean and Green India, Oriental University Indore, India, 26th – 27th October 2018.
  • Mahesh A. Maindarkar and Dr. Pragya Nema, “A state of the art RF Energy Harvesting Rectenna for upcoming smart cities in India”, International Conference on Smart Systems (ICSS-2018), School of Engineering, Ajeenkya DY Patil University, Pune, India, 27th – 28th September 2018.
  • Mahesh A. Maindarkar, “AI in telecommunications”, International Conference Telecommuniqe-2013, held at Symbiosis International University, Pune. in Apr. 2012.

Patent

  • Published Patent on “RF Rectenna for Energy Harvesting at 1.8 GHz to 5.8 GHz to reduce energy crises”, Patent ID 202021036496, The Patent Office Journal No. 09/2022, Part 2, Dated 04/03/2022.
  • Published Patent on “Machine Learning and Internet of Thing approach for solar plant control system and fault detection with energy prediction”, Patent ID 202021036499, The Patent Office Journal No. 09/2022, Part-2, Dated 04/03/2022.
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