Malik Haroon Khokhar's Work | ContraWork by Malik Haroon Khokhar
Malik Haroon Khokhar

Malik Haroon Khokhar

AI engineer who builds the whole system, LLM agents, vision

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Followed by Mark B, Fadare G, and GALLERY L

Lahore, Pakistan

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Lahore, Pakistan

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Cover image for As an AI Engineer, I
As an AI Engineer, I spend most of my day working in the terminal—so I thought, why not make my portfolio look like one? 🖥️🟩 I wanted a personal site that reflects how I actually work. No flashy animations or endless scrolling, just a clean, interactive command-line interface built with React and TypeScript. In the video below, you can see how to navigate it. You can type ls projects to see the RAG systems and ML architectures I've built, or cat experience to see my background. Take it for a test drive and let me know if you discover any of the commands!
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Cover image for Understand anything, visually. I built MindMap
Understand anything, visually. I built MindMap AI, a concept for turning complex topics into interactive visual maps. Instead of getting another wall of AI-generated text, you enter a topic like: “How does a Transformer work?” and the system breaks it down into connected concepts such as Attention, Q/K/V, Encoder, Decoder, FFN, Tokenization, and Positional Encoding. You can then explore the map by selecting individual concepts to get a focused explanation, dive deeper, simplify the concept, or expand it into a submap. The interface was designed with a deliberately minimal, Apple-inspired approach: lots of whitespace, restrained typography, neutral colors, and almost no visual noise. Built around: AI-generated knowledge graphs Interactive node-based visualization Concept exploration AI explanations Expandable submaps Zooming, panning, and canvas navigation The goal was simple: make understanding complex AI concepts feel visual and intuitive.
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Cover image for SheetMind AI is a production-grade,
SheetMind AI is a production-grade, fully local Retrieval-Augmented Generation (RAG) system designed to intelligently query and analyze large Excel datasets using natural language. This project demonstrates how modern AI systems can be integrated with structured business data to create powerful, privacy-first analytics tools, without relying on cloud APIs or external services. The entire system runs locally using PostgreSQL, pgvector, FastAPI, Next.js, and Ollama models, making it suitable for enterprise environments where data privacy, cost control, and offline capability are critical.
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