PhD Scholar (SIRe) & Project Scientist at SCFBio, IIT Delhi.
I specialize in Computer-Aided Drug Design (CADD), applying Machine Learning and Molecular Dynamics Simulations to solve complex biological problems.
Years Experience
Publications
Complexes Analyzed
I am a researcher passionate about solving complex biological problems using high-performance computing. Currently working at SCFBio Lab, I specialize in virtual screening and creating ensembles of machine learning models to predict protein-ligand interactions.
Beyond research, I have a strong background in web technologies (PHP, JS), allowing me to build the tools that visualize and distribute my scientific findings.
SEARCH-ML is a robust framework designed for high-accuracy binding affinity prediction. It employs a Stacked Ensemble architecture, integrating four cutting-edge base learners—XGBoost, CatBoost, LightGBM, and Random Forest—weighted by a Ridge Regression meta-learner.
Optimized via Bayesian hyperparameter tuning, it addresses two critical drug discovery challenges:
