Portfolio

Welcome to My AI Innovation Lab

Welcome to my comprehensive portfolio showcasing cutting-edge projects in Machine Learning, Deep Learning, and Artificial Intelligence. From competitive data science challenges to production-ready AI applications, my work demonstrates the full spectrum of AI capabilities solving real-world problems.

Machine Learning & Deep Learning Excellence

I actively compete and collaborate on Kaggle, where I tackle complex datasets and push the boundaries of predictive modeling. My competitive journey showcases expertise in data analysis, feature engineering, and advanced model architectures.

🏆 Competitive Data Science

• Advanced statistical modeling and ensemble techniques
• Deep learning architectures for computer vision and NLP
• Feature engineering and data preprocessing pipelines
• Model optimization and hyperparameter tuning

🔗 Explore My Kaggle Profile

Production-Ready AI Applications

My AI engineering portfolio demonstrates the practical application of cutting-edge technologies to solve complex business problems. Each project represents a complete solution from research to deployment.

Featured Projects

FounderAI - Executive AI Agent Platform

Multi-Agent System for Startup Leadership

Problem Solved: Early-stage founders lack the resources for a complete C-suite team, limiting their ability to execute across marketing, product, technology, and operations.

Solution Architecture:

• Multi-Agent Orchestration - CrewAI LangGraph coordination
• Executive Persona Agents - CMO, CPO, CTO, COO specialized agents
• LangChain Integration - Advanced reasoning and tool usage
• Model Context Protocol (MCP) - Seamless model communication

Agent Capabilities:

• CMO Agents: Market intelligence, positioning, acquisition strategy, content creation
• Product Agents: Roadmap planning, A/B testing, user research
• CTO Agents: Technical architecture, development planning
• COO Agents: Operations optimization, financial modeling
• Fundraising Agents: Pitch deck generation, due diligence preparation

Technical Stack: LangChain, LangGraph, CrewAI, FastAPI, Stramlit, Langflow

View Project Repository

Technical Arsenal

My technical toolkit includes:

• Advanced ML/DL: Python, PyTorch, TensorFlow, Keras, Scikit-learn
• MLOps & Deployment: MLflow, Git Actions, Docker, Kubernetes, CI/CD pipelines
• Cloud Platforms: AWS (SageMaker, EC2, S3), Google Cloud Platform (AI Platform)
• Specialized Areas: Computer Vision, Natural Language Processing (NLP), Speech Recognition, Generative AI, Federated Learning
• AI Agent Engineering: LangChain, LangGraph, LangFlow, CrewAI, Ollama, AutoGen, LlamaIndex, Semantic Kernel, Model Context Protocol (MCP), ReAct frameworks, tool calling and function execution, multi-agent orchestration, retrieval-augmented generation (RAG), vector embeddings, agent memory systems, workflow automation, prompt engineering and optimization

AI-Driven Tourist Spot Finder

Intelligent Travel Companion with Multi-Agent Architecture

Problem Solved: Traditional travel planning lacks personalization and real-time insights, leading to suboptimal travel experiences.

Solution Architecture:

• FastAPI Production Backend - Scalable REST API architecture
• Machine Learning Recommendation Engine - Collaborative and content-based filtering
• Large Language Model Integration - GPT-powered destination descriptions
• AI Agent System - Real-time data collection and analysis
• MongoDB Database - Flexible document storage for user profiles and preferences

Key Features:

• Personalized destination recommendations based on user preferences
• Real-time weather, pricing, and availability data
• Dynamic itinerary generation with AI-powered insights
• Multi-modal data processing (text, images, location data)

Technical Stack: FastAPI, PyTorch, LangChain, MongoDB, Docker View Project Repository

Health-Conscious Food Recommendation System

Personalized Nutrition AI with OCR Integration

Problem Solved: Individuals with specific health conditions struggle to make informed dietary choices from food labels and menus.

Solution Architecture:

• Advanced OCR System - Mistral OCR for high-accuracy text extraction from food labels
• Health Analysis Engine - LLM-powered nutritional assessment
• RAG (Retrieval-Augmented Generation) - Real-time medical data integration
• Personalized Recommendation Engine - Health condition-aware food suggestions
• MongoDB Database - User health profiles and food database

Key Features:

• Instant food label analysis through camera capture
• Health condition-specific dietary recommendations
• Real-time nutritional database queries
• Personalized meal planning with health constraints
• Integration with medical dietary guidelines

Technical Stack: Mistral OCR, LangChain, RAG, MongoDB, Computer Vision View Project Repository

🎤 Bengali Text-to-Speech Synthesis

Transformer-Based Language Model Fine-tuning

Problem Solved: Limited accessibility tools for Bengali speakers due to lack of high-quality TTS systems in the Bengali language.

Solution Architecture:

• Pegasus Model Fine-tuning - Transformer architecture optimization for Bengali
• MLOps Pipeline - Automated training, validation, and deployment
• Custom Dataset Preparation - Bengali text corpus processing
• Model Optimization - Performance tuning for production deployment

Key Features:

• High-quality Bengali speech synthesis
• Natural-sounding voice generation
• Scalable inference pipeline
• MLOps-driven continuous improvement
• Production-ready API deployment

Technical Stack: Transformers, PyTorch, MLOps, Docker, Kubernetes View Project Repository

📈 Continuous Innovation

I continuously update my portfolio with cutting-edge research implementations and production-ready solutions. Each project represents not just technical capability, but practical problem-solving that creates real value.

🔗 Connect & Explore

Ready to collaborate on your next AI innovation? Let’s build the future together.