Spiritually grounded, driven by AI β creating with purpose, not just code.
Specialized in Generative AI, LLMs, NLP, and RAG.
Building AI-powered systems that matter.
I'm an AI Engineer Specialist leading teams in AI research and product development. Experienced in Generative AI, NLP, and RAG β with deep proficiency in Python, LLM fine-tuning, and multimodal applications.
Skilled in implementing AI-driven solutions including chatbot systems and object detection pipelines. Strong foundation in data analytics using SQL and Tableau. Proven track record of executing successful AI strategies across industry projects.
Delivered a production-ready AI-powered real-time chatbot for NTS Green School, integrating Dialogflow NLP models with a Socket.IO + FastAPI backend. Implemented 10-message free trial system and Stripe-powered premium upgrade flow. Collaborated with web dev team on API integration, demo frontend, and deployment.
🏆 Awarded Official Letter of Recommendation View LOR βDelivered and deployed 6 ML applications using Python, Scikit-learn, TensorFlow/Keras β including CNN-based transfer learning (MobileNetV2) for image classification achieving ~85β92% accuracy. Deployed on Hugging Face Spaces, Streamlit, and Gradio.
Implemented 'News Genre Prediction on Headline' project. Led a team in successfully delivering a complex DL project on time. Streamlined project workflows enhancing overall performance. Received Govt. Recognition for leading & delivering an accurate ML model.
Managed project timelines, reducing delivery times by 60%. Collaborated with cross-functional teams. Led a team in delivering the project on time, enhancing project success rates by 90%.
Medical knowledge retrieval system using Google Gemini 2.0-Flash LLM. RAG pipeline with Hugging Face embeddings & Pinecone. AWS infrastructure for deployment.
High-accuracy multi-PDF chatbot achieving >98% answer relevance, tested by 40+ real users for precise document understanding and intelligent querying.
Chatbot with persistent memory using ChromaDB & LangChain. Google embedding model for semantic understanding. RAG pipeline with LangChain & Pinecone.
Automated Reddit bot using Python, Groq AI, and Llama-3-70B. Integrated PRAW API for content posting and scheduling with error logging and authentication.
ConvLSTM model using UCF50 dataset to classify 50 human actions. Preprocessed video frames with OpenCV, tuned hyperparameters. Achieved 94% accuracy.
Pipeline using Whisper and gTTS for speech transcription and synthesis. Automated media processing with FFmpeg. Video synthesis using MoviePy.
Voice-controlled assistant with speech recognition and TTS. Integrated Wikipedia API, SMTP, and camera control with OpenCV.
NLP-based classifier for news headlines using scraped data. Used TF-IDF, CountVectorizer, and ensemble models. Evaluated with classification metrics.
Aritra delivered a high-performing news classification model with over 88% accuracy. His solution was recognized by senior officials for its real-world relevance and timely execution.
MediBot answered my medical queries faster and more accurately than I expected. The memory feature made the conversation feel natural β like chatting with a real doctor assistant!
This bot saved me hours! I used it to understand multiple research PDFs in one place. Super useful during exam prep β highly recommend to fellow students.
I value meaningful, impactful conversations β whether it's bold ideas in AI, tech innovation, or a collaboration in the making π«±π»βπ«²π½