Souvik Pore

About Me

I am Souvik Pore, a researcher specializing in machine learning-based cheminformatics modeling of ecotoxicological and pharmacokinetic parameters. I am currently a member of the Drug Theoretics and Cheminformatics (DTC) Laboratory, where I contribute to cutting-edge research in computational drug discovery.

My work focuses on leveraging advanced machine learning techniques to predict and analyze chemical and biological interactions, aiming to accelerate the development of safer and more effective therapeutics.

My Projects

RSL: Regression-based Machine Learning Modeller

Developed different types of regression-based supervised machine learning models.

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CSL: Classification-based Machine Learning Modeller

Developed different types of classification-based supervised machine learning models.

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Tuning+CV: Hyperparameter optimizer and Cross-Validation metrics calculator

Perform hyperparameter optimization and cross-validation for different types of machine learning models.

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Data Balancer: Perform data balancing for unbalanced data

This tool is utilized for balancing the unbalanced data by undersampling or oversampling the dataset.

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Activity Landscape: Find activity cliff and structural outliers

This tool is used to identify outliers (response and Structural) of a dataset through SALI index.

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Divider: Random divider and model selecter

This tool perform random dataset division, then perform feature selection using mlxtend and develop models.

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Research & Publications