Rishit Puri Email & Phone Number

United States

Bloomington, Indiana, Us

Bloomington, Indiana, Us

• Designed a normalized MySQL database with advanced window functions and pivoting techniques, and developed a custom API for enhanced data retrieval, ensuring optimized query performance.• Developed an automated pipeline to preprocess over 100+ GB of Alzheimer’s disease-related image data, reducing manual efforts by 70%. Leveraged SPM12, FSL, FSLnets and Nilearn to handle fMRI, MRI, and DTI image data.• Devised an architecture using DINO V2, BEIT, and LlaMA for image classification and segmentation, and performed ICA along with correlations on rs-fMRI images, enabling innovative applications in medical imaging.• Generated interactive dashboards using Power BI, enhancing data interpretation and usability with a 50% increase in efficiency,improving decision-making and stakeholder engagement.

Indianapolis, In, Us

• Implemented Sparse CCA, Procrustes Analysis, and Lasso Regression to analyze correlations between gene expression and microbiome data using R Studio and Excel; enhanced Data Visualization using Tableau to create interactive dashboards.• Engineered ETL (Extract, Transform, Load) pipelines utilizing AWS Glue to process and migrate over 30+ GB of data into Amazon Redshift, enhancing data accessibility and optimizing workflow efficiency.• Recognized as the Runner-Up for the Best Project Presentation and Data Visualization Award.• Leveraged PySpark with MLlib and integrated GraphX analytics to enhance predictive analytics capabilities, achieving a 60% increase in data interpretation accuracy, thereby significantly improving decision-making processes.

Houston, Texas, Us

• Led the deployment efforts, by orchestrating the entire project’s migration to Azure through the utilization of Azure Web Apps and Docker for containerization and conducted API testing across 6 endpoints using Azure API management and Postman..• Collaborated on a team project to develop a brain tumor segmentation model using UNet architecture, successfully achieving 93% accuracy in precisely localizing tumor positions within brain imaging data

Singapore, Sg

• Led a project to predict Optimal Sleep Time using Health factors, employing various ML and DL models (Random Forest,XG BoostLSTM and GRU) with Amazon EMR for model building and S3 for data storage, advancing personalized health insights.• Conducted exploratory data analysis to visualize trends and relationships, and optimized model parameters using Grid Search on Amazon SageMaker, boosting performance by 15% for the study on optimal sleep prediction.• Streamlined 3 major ETL pipelines using Azure Data Factory, resulting in $100,000 cost savings for potential clients through enhanced data processing efficiency and reduced operational expenses.

Master Of Science - Ms, Data Science

Semester Abroad, Statistics And Comp Sci

Bachelor Of Technology - Btech, Electronics And Communications Engineering

Science