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Desineni Subbaram Naidu, PhD, Life Fellow IEEE

Desineni Subbaram Naidu, PhD, Life Fellow IEEE

Advisory Editorial Board · Professor -Electrical Engineering

Advisory Editorial Board

Desineni Subbaram Naidu, PhD, Life Fellow IEEE

Professor -Electrical Engineering

ORCID ID

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Contact & Affiliation

Address: University of Minnesota Duluth (UMD) 273 MWAH, 1023 University Drive, Duluth, MN 55812-3009, USA.
E-Mail: [email protected]
Country: United States

Research Area

Life (& Biomedical) SciencesArts (& Humanities)PLANETPower and EnergyControl Systems EngineeringCyber Physical Control SystemsResilient Control SystemsIntelligent Control SystemsNonlinear Control SystemsMarine Control SystemsLinear Control SystemsOptimal Control: Theory and Applications Biomedical Sciences and Engineering(Prosthetics and Infectious Diseases): Advanced Control Strategies Large Scale Systems and Singular PerturbationsTime Scales (SPaTS): Control Theory and ApplicationsModern Control Strategies for Nuclear Reactors GuidanceControl of Aerospace Systems: Aero assisted Orbital Transfer:Mars missionUninhabited Aerial Vehicles (UAVs)Advanced Control Strategies for Heating Ventilation & Air-Conditioning (HVAC)Modeling Sensing and Control of Gas Metal Arc Welding (GMAW).

Publications

Kumar, A., Aelgani, V., Vohra, R., D. S. Naidu, et al. Artificial intelligence bias in medical system designs: a systematic review. Multimed Tools Appl (Published online 22 July 2023). https://doi.org/10.1007/s11042-023-16029-x Khanna, N.N., et-al, D.S. Naidu, “Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment”, Healthcare 2022, 10, 2493, 09 December 2022.https://doi.org/10.3390/healthcare10122493. Khanna, N.N., et-al, D.S. Naidu, “Cardiovascular/Stroke Risk Stratification in Diabetic Foot Infection Patients Using Deep Learning-Based Artificial Intelligence: An Investigative Study”, Journal of Clinical Medicine, November(11), 2022. Suri, J.S. et. al, D.S. Naidu, “Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinsons Disease Affected by COVID-19: A Narrative Review. Diagnostics 2022, 12, 1543. https://doi.org/10.3390/diagnostics12071543 Suri, J.S. et al D. S. Naidu, “COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans, Diagnostics 2022, 12, 1482.https://doi.org/10.3390/diagnostics12061482 Suri. J.S. et.al, D.S. Naidu, “COVLIAS 1.0 Lesion vs. MedSeg: An Artificial Intelligence Framework for Automated Lesion Segmentation in COVID-19 Lung Computed Tomography Scans, Diagnostics Journal, Vol., 12, Nr. 5, Article Number 1283, 2022. URL = https://www.mdpi.com/2075-4418/12/5/1283, ISSN =2075-4418, DOI = 10.3390/diagnostics12051283. J. S. Suri et al. and D. S. Naidu, “Five Strategies for Bias Estimation in Artificial Intelligence-based Hybrid Deep Learning for Acute Respiratory Distress Syndrome COVID-19 Lung Infected Patients using AP(ai)Bias 2.0: A Systematic Review,” in IEEE Transactions on Instrumentation and Measurement, May 2022 doi: 10.1109/TIM.2022.3174270. Munjral, S., et.al, and D.S. Naidu, “Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/non-COVID-19 Frameworks using Artificial Intelligence Paradigm: A Narrative Review, JOURNAL = Diagnostics, VOLUME = 12, NUMBER = 5, ARTICLE-NUMBER = 1234, YEAR = 2022. URL = https://www.mdpi.com/2075-4418/12/5/1234, DOI= 10.3390/diagnostics12051234. Suri, J.S., et al, and D.S. Naidu, “COVLIAS 1.0 vs. MedSeg: Artificial IntelligenceBased Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts”, Special Issue: Spectral CT Techniques and Functional Applications in Disease Diagnosis, Diagnostics 2021, 11, 2367. https://doi.org/10.3390/diagnostics11122367 J. Suri et al. and D.S. Naidu, ”Inter-Variability Study of COVLIAS 1.0: Hybrid Deep Learning Models for COVID-19 Lung Segmentation in Computed Tomog-raphy,” in Diagnostics, 01 November 2021.https://doi.org/10.3390/diagnostics11112025

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