Engineering Intelligent Systems
About Me
I am a Computer Science undergraduate (B.Tech 2024-2028) at SRMIST with a core focus on the end-to-end machine learning lifecycle—from data to deployment.
My technical expertise is in building high-performance, interpretable models. I specialize in rigorous data preprocessing, advanced feature engineering, and training models like XGBoost and CatBoost. A key part of my work is ensuring transparency through interpretability techniques like SHAP, which is crucial for reliable, high-stakes AI applications.
Publications
A Dataset for Detecting Dopamine-Triggering Stimuli in Children’s YouTube Videos
Zenodo, 2024
Authored and published a manually annotated dataset to facilitate research on digital stimuli affecting children. This work serves as a foundation for my Dopamine-Stimuli-Predictive-Model project.
Featured Projects
Core Skills
ML/DL
Programming & CS
Tools & Platforms
Certifications
Machine Learning Specialization
Stanford University | DeepLearning.AI
Neural Networks and Deep Learning
DeepLearning.AI
CS50’s Introduction to Programming with Python
Harvard University
SQL for Data Science
University of California, Davis