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Assessing your cultural and operational fit
cross-season-image-matching
June 1, 2026 – Present
cross-season-image-matching — GitHub repository
View Projectloan-approval-ml-pipeline
April 6, 2026 – Present
End-to-end machine learning pipeline for loan approval prediction with preprocessing, model comparison, clustering, and Streamlit deployment.
View ProjectSleepSense-AI
March 3, 2026 – Present
AI-based detection of sleep breathing irregularities using physiological signals (Nasal Airflow, Thoracic Movement, SpO2) with signal processing and 1D CNN modeling.
View ProjectDelhi-Airshed-LandUse-AI-Audit
March 2, 2026 – Present
AI-based land-use audit of the Delhi Airshed using Sentinel-2 imagery and ESA WorldCover with spatial gridding and CNN classification.
View Projectair-quality-index-regression-analysis
February 7, 2026 – Present
A comprehensive study and implementation of Linear Regression models including Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, Ridge, and Lasso using Python. This project includes complete EDA, model comparison, performance evaluation (MSE, RMSE, R2), and model diagnostics as part of a Machine Learning Lab assignment.
View ProjectCloudburst-Early-Warning-and-Alarm-System
October 8, 2025 – October 8, 2025
A distributed IoT system with AI-powered anomaly detection for real-time cloudburst prediction in hilly regions. Provides early warnings to communities and authorities through multiple communication channels.
View ProjectAetherMind
February 24, 2025 – June 15, 2025
# AetherMind An AI-Driven Mental Health Chat Companion with Ethical Safeguards. ## Flowchart  <!-- Add your flowchart image here --> ## Setup 1. Clone the repo. 2. Install dependencies: `pip install -r requirements.txt`.
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards AI/ML applications, particularly in environmental monitoring, health, and general data science. This aligns well with a Data Scientist role. The diversity of projects (IoT, image processing, NLP, regression) suggests adaptability and a broad interest in applying AI/ML to different domains. However, the projects are all personal, which might indicate a lack of experience in collaborative, production-grade environments, potentially impacting cultural fit in a team setting without further information.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are clear and concise, indicating good written communication.