Sagar Dhakal
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
Faculty Researcher
Research Areas
Biography and Research Information
OverviewAI-generated summary
Sagar Dhakal's research interests encompass advanced neural network applications and cardiovascular function. He has published on topics such as using spiking neural networks for electrocardiogram (ECG) classification and anomaly detection. Dhakal has also investigated fault tolerance in electrical systems, including work on the voltage control and braking system of a doubly fed induction generator (DFIG) during faults. His scholarly activity includes 11 publications, with a total of 210 citations and an h-index of 5. He has collaborated with researchers at Arkansas Tech University, including Tolga Ensarı, Robin Ghosh, and Sachin Bhandari, on shared publications. Dhakal's recent work indicates continued engagement in research, with publications dated as recently as 2025.
Metrics
- h-index: 5
- Publications: 11
- Citations: 210
Selected Publications
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SmartSpend: A Unified Artificial Intelligence Powered Personal Finance Dashboard Integrating Fraud Detection, Spending Forecasting and Budget Recommendation (2026)
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Multimodal Neuromorphic Computing for Cancer Diagnosis: Architecture, Clinical Fusion and Energy Analysis (2026)
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The Advanced Health Risk Predictor: Ensemble Machine Learning System for Multi Disease Clinical Decision Support (2026)
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Spiking Neural Networks for ECG Classification and Anomaly Detection (2025)
Collaboration Network
Top Collaborators
- Spiking Neural Networks for ECG Classification and Anomaly Detection
- Spiking Neural Networks for ECG Classification and Anomaly Detection
- Spiking Neural Networks for ECG Classification and Anomaly Detection
- Spiking Neural Networks for ECG Classification and Anomaly Detection
- Spiking Neural Networks for ECG Classification and Anomaly Detection
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