Md Mahmudul Hasan Data-verified

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

Last publication 2025 Last refreshed 2026-05-23

faculty

11 h-index 79 pubs 527 cited

Biography and Research Information

OverviewAI-generated summary

Md Mahmudul Hasan's research centers on power systems, with a particular focus on renewable energy integration and power electronics. His work investigates advanced energy management schemes for microgrids, incorporating components like fuel cells and switched capacitor inverters. He also explores control strategies for electrical systems, including the application of meta-heuristic optimization techniques for induction motor control.

His publications span diverse areas, reflecting a broad range of academic interests. These include a review of bio-inspired optimization techniques in electrical systems, an analysis of glass transition temperatures in food materials relevant to drying conditions, and research on the incidence of typhoid and paratyphoid fever in South Asia. Hasan has also contributed to the development of cost-effective Bluetooth-based ventilators for respiratory support and has published on power system flexibility in scenarios with high renewable energy penetration.

With a scholarly record indicated by an h-index of 11 and nearly 500 citations across 79 publications, Hasan maintains an active research presence. He collaborates with other researchers, including Saikot Hossain Dadon at Arkansas State University, and manages an active lab website to disseminate his work.

Metrics

  • h-index: 11
  • Publications: 79
  • Citations: 527

Selected Publications

  • Reintroducing Rotational Inertia in Microgrids: Stability Enhancement Using BLDC and Synchronous Generator (2025)
  • Correction: Rahman et al. An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios. Energies 2024, 17, 6393 (2025)
  • Breast Cancer Patient Survival Prediction Using Machine Learning on An Imbalanced Dataset (2024)
  • Machine Learning-Based Wind Power Prediction for Electric Vehicle Charging Hour Optimization (2024)
    4 citations DOI OpenAlex
  • An Overview of Power System Flexibility: High Renewable Energy Penetration Scenarios (2024)
    33 citations DOI OpenAlex

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Collaboration Network

166 Collaborators 62 Institutions 16 Countries

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