Featured Projects

A showcase of my technical expertise through real-world projects in Data Analytics, Business Analytics, Database, ML and innovative digital platforms. Each project demonstrates analytical, problem-solving skills and practical application of modern technologies.

Data Analytics & Visualization

Projects demonstrating data-driven insights and interactive visualizations

Banking Transaction & Risk Analysis

03/2026 - 03/2026

Sampled and analyzed 55,554 transactions from a 6.3M-record PaySim dataset using SQL, Python, and Power BI. Engineered fraud risk features, uncovered customer concentration patterns, and built an interactive dashboard visualizing $8.97bn+ in transaction value.

Fraud detected exclusively in TRANSFER (0.94%) and CASH_OUT (0.33%)
18% of customers drove 62% of total transaction value
Interactive Power BI dashboard with 4 KPIs and transaction-type drill-down
MySQL Python (Pandas) Power BI MS Excel
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Spotify Customer Churn Analysis

04/2026 - 04/2026

Analyzed 8,000 user records across 8 countries to identify churn drivers and build a rule-based risk segmentation model. Tested 6 behavioral features individually before reframing the problem around a combined multi-signal approach.

Uncovered 25.89% overall churn rate across 2,071 users
Built and refined segmentation model across 4 versions: 492 high-risk, 2,106 medium-risk, 5,402 low-risk
Mapped each risk tier to a targeted retention strategy for stakeholders
MySQL MS Excel Data Analysis Customer Analytics
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Layoff Trends & Workforce Analysis

11/2025 - 11/2025

Cleaned and standardized a 3,642-row raw dataset to 1,995 validated records using SQL staging tables, window functions, and Python. Identified global layoff patterns across industries, funding stages, and countries during the 2022-23 post-pandemic peak.

US most impacted country with 256,559 layoffs
Post-IPO stage highest risk with 204,132 layoffs
Resolved 1,300+ null fields using ROW_NUMBER() and staging tables
MySQL Python (Pandas) MS Excel Data Cleaning
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Mental Health Predictive Analysis

Built a logistic regression model (71% accuracy) to predict if a tech employee would seek mental health treatment. Visualized insights with Power BI.

71% prediction accuracy
Interactive Power BI dashboard
Identified key predictive factors
Scikit-learn Power BI Logistic Regression Data Visualization
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AI & Machine Learning

Advanced projects showcasing expertise in computer vision, NLP, multi-agent systems, and medical AI

Multi-AI-Agent Medical Diagnosis

Developed a sophisticated multi-agent system using TensorFlow and PyTorch, featuring specialized AI agents (Cardiologist, Psychologist, Pulmonologist) that collaborate to provide comprehensive medical diagnoses from patient reports.

Multi-threaded agent processing
LLM integration with GPT-4 agents
Deployed on HuggingFace Spaces
TensorFlow PyTorch Multi-Agent Systems Medical AI HuggingFace
Live Demo →
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Real-Time Traffic Signal Recognition

Built a YOLOv8 model in PyTorch to detect traffic signals in real-time, achieving an outstanding 72% mAP on the test dataset.

72% mAP accuracy on test dataset
Real-time processing with OpenCV
Comprehensive data augmentation pipeline
PyTorch YOLOv8 OpenCV Computer Vision
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Pneumonia Detection System by X-Ray

Advanced medical imaging AI system for pneumonia detection in chest X-rays with 96.4% sensitivity and 86% cross-operator validation accuracy. Features real-time analysis and clinical-grade reporting.

96.4% sensitivity for pneumonia detection
Cross-operator validated on 485 samples
DICOM support & PDF reports
Deep Learning Medical Imaging CNN HuggingFace Computer Vision
Live Demo →
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Instagram Sentiment Analysis

Engineered an NLP pipeline to classify comment sentiment, achieving 54% accuracy on a complex, nuanced dataset with 150+ emotion labels.

54% accuracy on complex dataset
Label standardization for 150+ emotions
86% recall for positive/negative sentiments
NLTK VADER NLP Sentiment Analysis
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Innovative Platforms

Creative digital solutions combining storytelling, cultural heritage, and emerging technologies

Darshana - Digital Storytelling Platform

Concept Phase

My innovative startup concept: A comprehensive digital platform that connects users to their cultural heritage through immersive storytelling, featuring AI-powered content curation, virtual reality experiences, and interactive cultural exploration.

Core Features

Narad AI - Intelligent story curator
360° Virtual monument visits
AR/VR cultural immersion

Content Sections

Interactive story collections
Historical monument database
Folk tales & cultural narratives

Future Roadmap

Ticket booking integration
Virtual guide assistance services
AI/ML AR/VR 360° Technology Digital Platform Cultural Heritage Startup Concept
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