0000-0001-8448-2729 Employment
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Publications (18)
- Predicting power conversion efficiency in donor-acceptor pairs for organic solar cells using machine learning ensemble models Save
- Predicting Debye Temperature and Thermal Conductivity of Transition Metals Using Machine Learning Ensemble Models Save
- Predicting thermal conductivity of transition metals using machine learning gaussian process regression models Save
- Leveraging optimized machine learning regression models for measuring the Stokes shift of fluorescent organic dyes Save
- Breast Cancer Prediction Using Oversampling Technique, Particle Swarm Optimization, and Fuzzy Logic Save
- Predicting Förster critical distance using machine learning techniques Save
- Stokes shift prediction of fluorescent organic dyes using machine learning based hybrid cascade models Save
- Optimized Machine learning techniques Enable prediction of organic dyes photophysical Properties: Absorption Wavelengths, emission Wavelengths, and quantum yields Save
- Machine learning based hybrid ensemble models for prediction of organic dyes photophysical properties: Absorption wavelengths, emission wavelengths, and quantum yields Save
- Absorption and emission maxima prediction of fluorescent organic materials using optimized neural network models Save