The official implementation of "RouteExplainer: An Explanation Framework for Vehicle Routing Problem" (PAKDD 2024, oral)

An interactive dashboard for exploring mathematical research trends on arXiv

High-quality scientific PDF translation using Claude Code Max - Transform scanned academic documents from English to French with precision

Automated LLM-based Prompt Engineering for Structured Data Processing

AI-powered stock analysis and investment recommendation app using CrewAI agents, Gemini LLM, DuckDuckGo Search and real-time market data. Generates comprehensive reports, news summaries, and buy/hold/sell advice.

RAG enhances LLMs by retrieving relevant external knowledge before generating responses, improving accuracy and reducing hallucinations.

Turn plain English into Robot Framework files with AI. No dependencies, no hassle — just validated, ready-to-run tests

Successfully developed an interview preparation guide using Langchain which can effectively guide users in their interview preparation process and job search journeys by providing valuable insights and feedback regarding their performance. It generates a comprehensive list of questions pertaining to a user query as well.

Powerful framework for building applications with Large Language Models (LLMs), enabling seamless integration with memory, agents, and external data sources.

🤖 Production-ready samples for building multi-modal AI agents that understand images, documents, videos, and text using Amazon Bedrock and Strands Agents. Features Claude integration, MCP tools, streaming responses, and enterprise-grade architecture.

Augmented Intelligence Framework: Create orchestrated multi-agent AI teams for software development, user research & content creation. Features 45+ specialized agents with structured workflows delivering the full benefits of human-AI collaboration

Semantic Retrieval Engine for Contrasting Ideas and Opposing Viewpoints.

Successfully developed an LLM application which generates a summary, a list of citations and references and response to a user's query based on the research paper's content.

ScholarLens analyzes research papers using RAG with AI models from OpenAI, Anthropic, and Google. It identifies research gaps, assesses novelty, extracts key concepts, visualizes citations, and enables natural language queries of academic content. Features include PDF processing, arXiv/Semantic Scholar integration, batch processing, and intelligent

CareConnect uses state-of-the-art large language models (LLMs) to provide rapid, reliable medical guidance. This project addresses increasing wait times and health misinformation, offering timely assistance and supporting informed decision-making to alleviate the burden on the healthcare system.

A personalized career guidance agent built with FastAPI, LangGraph, and OpenAI. Provides tailored career advice, answers questions on skills and certifications, and supports real-time conversations for informed career decisions.

LLMGrep combines the precision of Semgrep's static analysis with the power of Large Language Models to deliver comprehensive security scanning, interactive vulnerability discussions, and intelligent rule generation capabilities.

A Streamlit tool for analyzing Information Security Policies by classifying keyword occurrences as "Actionable Advice" or "Other Information" to measure policy effectiveness through the "Keyword Loss of Specificity" metric.

An agent system built with LangGraph to generate, critique, and refine professional LinkedIn posts using reflection pattern.

A smart, conversational FAQ system using LangGraph and sentence-transformer embeddings that semantically retrieves answers from a CSV knowledge base and routes user queries based on confidence. Built with LangChain, FAISS, and HuggingFace for efficient semantic search.