Projects per year
Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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Dive into the research topics where Umer Amir Khan is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Projects
- 1 Active
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High Voltage Superconducting Cables for Urban Power Grids: Addressing Stability and Renewable Energy Challenges in Expanding Saudi Cities
Khan, U. A. (PI) & Memon, A. (CoI)
1/01/25 → 31/12/25
Project: Research
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Electric Field Augmentation on Surfaces of Field Aged Composite Insulators Under Varying Contamination Conditions
Badwey, M. A., Asif, M. & Khan, U. A., 2025, In: IEEE Access. 13, p. 160048-160066 19 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Experimental validation of machine learning for contamination classification of polluted high voltage insulators using leakage current
Khan, U. A., Asif, M., Zafar, M. H. & Alhems, L., Dec 2025, In: Scientific Reports. 15, 1, 13246.Research output: Contribution to journal › Article › peer-review
Open Access1 Scopus citations -
Toward Real-Time Monitoring of High-Voltage Insulators: Progressive Flashover Classification Using Quantized Deep Learning
Khan, U. A., 2025, In: IEEE Open Journal of Industry Applications. 6, p. 630-646 17 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Analysis of deep learning models for estimation of MPP and extraction of maximum power from hybrid PV-TEG: A step towards cleaner energy production
Khan, N. M., Khan, U. A., Asif, M. & Zafar, M. H., Jun 2024, In: Energy Reports. 11, p. 4759-4775 17 p.Research output: Contribution to journal › Article › peer-review
Open Access15 Scopus citations -
Feature Extraction Techniques from Contaminated-Insulator Leakage Current Data for Deep Learning Applications in Condition Monitoring of High Voltage Insulators
Amir Khan, U., Asif, M., Jung, J., Alhems, L. & Lee, B. W., 2024, 2024 10th International Conference on Condition Monitoring and Diagnosis, CMD 2024. Institute of Electrical and Electronics Engineers Inc., p. 608-611 4 p. (2024 10th International Conference on Condition Monitoring and Diagnosis, CMD 2024).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
1 Scopus citations