Venkata Naga Teja Neelisetty

About

B.Tech CSE (AI/ML) and B.S. Data Science student with hands-on experience in machine learning, predictive modeling, data preprocessing, feature engineering, and model evaluation. Has worked on industrial ML and remote sensing projects using Python, scikit-learn, and geospatial tools.

Experience

• Remote Sensing & GIS Intern
  India Space Academy
  May 2026 – Jul 2026
• Machine Learning Intern
  InternVision Technology Pvt. Ltd.
  Dec 2025 – Feb 2026

Education

• B.Tech
  Vellore Institute of Technology, Chennai
  Computer Science Engineering (AI/ML) · May 2029
• B.S.
  IIT Madras
  Data Science and Applications · May 2025 – May 2029

Skills

• SQL
• C
• FastAPI
• Python
• Machine Learning
• Prompt Engineering
• Java
• JavaScript
• Decision Trees
• Feature Engineering
• Matplotlib
• Model Evaluation
• NumPy
• Pandas
• scikit-learn
• Hypothesis Testing
• Flask
• TypeScript
• Seaborn
• Scipy
• LLM evaluation
• LangChain
• Random Forest
• API Integration Understanding
• RAG
• Gradient Boosting
• Sentence Transformers
• Logistic Regression ( in progress )

Projects

• Urban Heat Island Analysis — Chennai (Remote Sensing & GIS) ↗
  JavaScript, Google Earth Engine, Landsat 8 Imagery

  Derived NDVI, NDBI, and Land Surface Temperature from Landsat 8 imagery to analyze the Urban Heat Island effect across Chennai. Processed multi-band geospatial data to relate land-cover change to urban surface-temperature patterns.

• AI-Assisted Crop Pattern Mapping (Remote Sensing & GIS) ↗
  JavaScript, Google Earth Engine, Sentinel-2 Satellite Imagery, Random Forest Classification

  Developed an AI-assisted crop classification pipeline using multi-season Sentinel-2 imagery and Random Forest in Google Earth Engine. Applied NDVI-based multi-season features and generated geospatial classification outputs for agricultural monitoring and analysis.

• Loan Approval Prediction — Hypothesis Testing & Statistical ML Analysis ↗
  Python, Pandas, NumPy, SciPy, Scikit-learn, Matplotlib, Seaborn

  Built an end-to-end loan-approval classification pipeline combining inferential statistics with supervised ML on a 614-record applicant dataset. Preprocessed financial data, applied feature selection, validated relationships using T-Test and Chi-Square tests, and trained Logistic Regression and Decision Tree classifiers.

• Vexadoc — Enterprise RAG Document Intelligence Platform ↗
  Python, FastAPI, LangChain, Sentence Transformers, ChromaDB, Next.js, React

  Built the core RAG pipeline with PDF parsing, metadata extraction, and intelligent text chunking. Implemented a FastAPI backend with a modular retrieval layer over a persistent ChromaDB vector store, and is developing the Next.js/React frontend and LLM response-generation layer.

Courses & certifications

• Industrial Training – Machine Learning · InternVision Technology Pvt. Ltd., DPIIT Recognised · 2026
• Remote Sensing & GIS Internship · India Space Academy, in collaboration with VIT Chennai · 2026
• Foundational Level in Programming & Data Science · IIT Madras, Centre for Outreach and Digital Education · 2026
• AWS Academy Graduate — Cloud Foundations · Amazon Web Services (AWS) Training and Certification