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About Me

I build AI systems that ship — not just experiments in notebooks. I design and deploy production-grade GenAI applications end-to-end, from model architecture to deployed API.

I've built LLM-powered assistants, automated assessment systems with AI-based scoring, RAG pipelines backed by vector databases, and computer vision systems for real-world safety applications — all served through FastAPI and integrated into live workflows.

I specialize at the intersection of:

NLP & Generative AI

LLMs, RAG systems, LangChain, prompt engineering

Computer Vision

CNNs, transfer learning, OpenCV, object detection

ML Engineering

Model training, evaluation pipelines, FastAPI deployment

Agentic AI

LangChain agents, Ollama, Groq, multimodal systems

Currently in my final year of B.E. Computer Science (AI & ML) at Lords Institute of Engineering & Technology, Hyderabad. I stay current with emerging research in machine learning, computer vision, and large language models — and I build things to understand them, not just read about them.

Open to AI Engineer, ML Engineer, and Computer Vision Engineer roles where I can work on production systems that solve real problems.

Technical Skills

My core stack — tools I use to build and ship real AI systems

💬

NLP & Generative AI

Large Language Models
RAG Systems
Prompt Engineering
LangChain
Embeddings & Vectors
Ollama & Groq
🧠

Computer Vision & DL

CNNs & Transfer Learning
OpenCV
Object Detection (YOLOv8)
PyTorch
TensorFlow & Keras
Grad-CAM & Explainability
⚙️

ML Engineering

Scikit-learn
Model Training & Evaluation
Feature Engineering
Hugging Face Transformers
Streamlit
FastAPI
💻

Programming

Python
SQL
REST APIs
Django
Pandas & NumPy
Matplotlib
📊

Data & Analysis

Data Preprocessing
Exploratory Data Analysis
Data Visualization
Scikit-learn Pipelines
Jupyter Notebooks
Anaconda
🛠️

Tools & Deployment

Git & GitHub
Vercel
Render
Railway
Hugging Face Spaces
VS Code
5
Live Projects
2
Internships
4
AI Systems Deployed

Featured Projects

AI systems built end-to-end and deployed to production

🫁
Medical AI

PulmoScan AI – Tuberculosis Detection System

An advanced deep-learning system for automated tuberculosis detection from chest X-rays, featuring real-time Grad-CAM heatmap visualizations and seamless deployment on HuggingFace Spaces.

PulmoScan AI is a complete end-to-end diagnostic pipeline built for early and accurate TB screening. It uses a custom-trained CNN architecture (TBNet) to analyze chest X-rays, highlights infected regions through Grad-CAM heatmaps, and generates professional PDF diagnostic reports. The system features a FastAPI backend, optimized inference pipeline, and an intuitive web interface hosted on HuggingFace Spaces.
PyTorchFastAPIHuggingFaceComputer VisionCNNGrad-CAM
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AI Applications

Doubt Tutor – AI Study Assistant

A fully interactive, AI-powered study assistant supporting multiple AI models with PDF, image, and document uploads — offering real-time doubt-solving with contextual memory and multi-modal reasoning.

Built a fully functional AI tutor capable of analyzing images, PDFs, and text files using Llama 3, Qwen-VL (vision), and Groq models. Includes chat history export, file previews, secure secret handling, and custom UI components.
StreamlitGroq APIHuggingFaceQwen-VLLangChainPython
🎓
AI Applications

PTEra – AI-Powered PTE Mock Assessment

A full-scale PTE mock test platform with adaptive difficulty, real-time scoring, section timers, and professional exam-style UI.

Developed an advanced PTE Academic mock assessment system with Aptitude, Listening, and Reading modules. Features include automated question generation using Groq & Gemini models, strict time tracking, dynamic content validation, analytics-driven scoring, and a premium custom UI. Deployed on HuggingFace Spaces with secure API handling and modular code architecture.
GradioGroq APIGoogle GeminiHuggingFace SpacesPython
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Machine Learning

TruthLens — Fake News Detector

Dual-AI system combining CNN-LSTM deep learning with Gemini API to detect fake news with 94.2% accuracy.

🧠

CNN-LSTM Hybrid

Custom NLP architecture

📊

Analytics Dashboard

Chart.js real-time stats

🔌

REST API

POST /api/predict endpoint

🔐

Admin Auth

Session-based login

🗄️

SQLite + ORM

Persistent prediction logs

📈

94.2% Accuracy

40,000+ article dataset

Trained on 40,000+ news articles. Features real-time predictions, analytics dashboard, prediction history, and dual-model verification using both a custom neural network and Gemini AI.
CNN-LSTMFlaskGemini AISQLiteREST API
🔥
Machine Learning

Building Safety Smoke Detection

Major college project — dual-module intelligent fire and smoke detection system combining 7 ML classifiers on 62,630 IoT sensor readings (AUC-ROC > 0.999) with MobileNetV2 CNN (96.98% accuracy) and YOLOv8 bounding-box detection, deployed as a Django web application.

B.E. Major Project at Lords Institute of Engineering & Technology, Hyderabad. Trains 7 classifiers (Random Forest, SVM, Gradient Boosting, AdaBoost, Logistic Regression, Decision Tree, KNN) on real IoT sensor data. MobileNetV2 CNN fine-tuned via transfer learning achieves 96.98% validation accuracy. YOLOv8 draws real-time bounding boxes around fire and smoke regions on uploaded images. Full-stack Django app with role-based user management, live ML training, sensor prediction, and CNN+YOLO inference — deployed on Railway.
DjangoTensorFlowYOLOv8Scikit-LearnMobileNetV2OpenCVRailway
5
Projects
3
Categories
5
Live Demos

Experience

Building and shipping production AI systems

🤖

Artificial Intelligence Intern

TechZone Software Academy for Training & Research

Hyderabad, India

March 2025 - June 2025
4 monthsInternship

Key Achievements

  • Architected and deployed 4 production-grade AI systems for a live ed-tech platform serving students and educators across Hyderabad
  • Engineered a RAG-powered AI tutoring system using LangChain and vector databases, delivering contextual real-time academic support
  • Designed and shipped an automated PTE mock-test engine with LLM-based scoring across reading, writing, and listening modules
  • Built an MCQ generation and attendance automation system, eliminating manual academic tracking across departments
  • Delivered all systems as production-ready FastAPI services with REST-based orchestration and continuous prompt optimization

Technologies Used

PythonFastAPILangChainOpenAI APIRAGVector DatabasesPrompt Engineering
4
AI Systems Deployed
3
LLM Applications
1
RAG Pipeline Built
🎓

AI/ML Intern

RAM Innovative Infotech

Hyderabad, India

November 2024
1 monthCollege Training Program

Key Achievements

  • Completed an intensive AI/ML training program organized in collaboration with Lords Institute CSE-AIML department
  • Developed a disease prediction ML model using Python and Scikit-learn, applying supervised learning classification on medical datasets
  • Gained hands-on exposure to Django for web-based AI integration and data preprocessing pipeline design

Technologies Used

PythonScikit-learnDjangoMachine LearningData Preprocessing
1
ML Model Built
5
Algorithms Explored
1
Web App Integrated

Get In Touch

Feel free to reach out for collaborations, opportunities, or just a friendly chat!

✉️

Send a Message

📍Based in Hyderabad, India