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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
contact
projects
Retinal Image Synthesis from Fundus to Fluroscein Angiography
- A Conditional Generative Network for synthesizing Fluroscein Angio images from Fundus Photography.
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
An Interpretable Catboost Model to Predict the Power of Combined Cycle Power Plants
Published in IEEE Xplore, 2021
In this study, a Catboost model which can predict the electrical energy output (EP) of a combined cycle power plant is presented. The Root Mean Square Error (RMSE) value achieved with the Catboost model is 0.0678, that is outstandingly lower in comparison with other methods in existing literature. Finally, Shapley additive explanations (SHAP) were employed to explain the inner workings of the Catboost model
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Fine Tuning the Prediction of the Compressive Strength of Concrete : A Bayesian Optimization Based Approach
Published in IEEE Xplore, 2021
This study demonstrates the efficacy of Bayesian Optimization to improve the performance of machine learning models for predicting the strength properties of concrete specimens. In the first phase of the study, five machine learning models(SVR, ABR, RFR, GBR and KNN Regressor) were compared on the basis of rmse, mae and r-squared value on the test set. Two best performing models(GBR and RFR) were selected among the five models for further improvement. In the second phase, hyperparameter tuning by Bayesian Optimization method was done on these two models. Experimental results testify that Bayesian Optimization on these two models improved their prediction performance further.
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talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.