🎓 M.Tech in Computer Science & Engineering from BIT Mesra, Ranchi

💻 B.Tech in Computer Science from NIST University, Berhampur, Odisha

📊 Passionate about Data Analytics, Machine Learning, Artificial Intelligence, and Business Intelligence

🔍 Interested in solving real-world problems using data-driven and AI-powered approaches

📈 Experienced in transforming raw data into actionable insights, dashboards, predictions, and business recommendations

🤖 Currently building practical AI-powered applications and intelligent workflow solutions

🔬 Published/accepted research work in Pathological Voice Disorder Detection

🚀 Interested in opportunities across Data Analytics, Business Intelligence, Machine Learning, and AI

• 📊 Data Analytics & Exploratory Data Analysis
• 🗃️ SQL, Data Cleaning & Data Preprocessing
• 📈 Power BI, DAX, Power Query & Business Intelligence
• 🐍 Python for Data Analytics & Machine Learning
• 🤖 Machine Learning & Artificial Intelligence
• 🧠 AI-powered workflow and decision-support systems
• 🎙️ Pathological Voice Disorder Detection Research
• 📌 Building end-to-end analytical and AI applications
• 💼 Data Analyst, Business Intelligence & Machine Learning opportunities

Research Highlights:

• Developed a Progressive Acoustic Stacking (PAS) framework
• Combined acoustic feature groups progressively
• Used MFCC, LPCC, Formant and Voice Quality features
• Applied speaker-level evaluation
• Used posterior probability aggregation across utterances
• Evaluated multiple machine learning models
• SVM selected for the final classification system
• Achieved 87.32% speaker-level accuracy
• Research accepted at IEEE ETAACT'26

Tech Stack:

Python Librosa NumPy Pandas Scikit-learn SVM MFCC LPCC Formants Jitter Shimmer HNR

Techniques:

MFCC LPCC Formant Analysis Jitter Shimmer HNR Acoustic Feature Engineering

EDA Data Cleaning Data Preprocessing Statistical Analysis Trend Analysis Forecasting KPI Reporting

MySQL Joins Subqueries CTEs Window Functions Aggregations Query Optimization

Dashboard Development Power Query DAX Data Modeling KPI Design Business Reporting

Classification Regression Feature Engineering Model Evaluation Cross-Validation Hyperparameter Tuning SHAP

LLM Integration AI Workflow Design AI-Assisted Decision Support Human-in-the-Loop AI Confidence-Aware AI AI Copilot

Built an AI Project Stand-up & Risk Assistant using:

React Vite FastAPI Python OpenAI API Tailwind CSS SQLite

The application demonstrates:

• AI-powered stand-up analysis
• Task and blocker extraction
• Risk assessment
• Confidence-aware insights
• Human validation
• Project health monitoring
• AI Copilot
• Leadership metrics
• Controlled escalation

Working on machine learning approaches for pathological voice disorder detection using acoustic feature engineering and speaker-level evaluation.

Key techniques include:

MFCC LPCC Formants Jitter Shimmer HNR SVM Progressive Acoustic Stacking

Building end-to-end analytics projects involving:

Python SQL Excel Power BI DAX Data Cleaning EDA KPI Analysis

• Advanced Machine Learning
• Artificial Intelligence & LLM Applications
• AI-Powered Workflow Automation
• Advanced SQL
• Advanced Power BI & DAX
• Data Engineering Fundamentals
• Production-oriented AI Application Development