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dawdameet/README.md

Meet Dawda | AI-Native Systems Engineer & Cybersecurity Enthusiast

I’m Meet, a systems programmer and AI/ML researcher focused on low-level engineering, AI-native tools, and modern compiler design. From building operating systems and optimizing compilers to designing fast inference APIs and embedded AI runtimes, I enjoy working at the intersection of software performance and intelligent systems.


Projects & Focus Areas

1. Low-Latency AI API (Rust on Windows)

A custom-built AI inference API optimized for real-time use cases, significantly faster than Flask/FastAPI for production deployment.

2. AI-Native Programming Language (Rust & LLVM)

Designing a new language tailored for machine learning workloads:

  • Built-in tensor support and autodiff
  • GPU acceleration
  • Lightweight, YAML-inspired syntax

3. Bare-Metal AI Accelerator (Rust + Assembly)

A minimal AI runtime running directly on hardware—no OS—targeted for embedded inference systems.

4. Compiler Optimization via AI

Research into LLVM IR optimization using AI/ML models to improve runtime performance of ML pipelines.

5. Decentralized Version Control (Rust + Solidity)

An experimental GitHub alternative built with smart contracts, Rust, and Ethers.js, focusing on decentralized code collaboration.

6. TensorDB (Rust + JNI)

A high-performance JNI-integrated tensor computation library for Java applications.


Technical Expertise

Domain Skills & Tools
Systems & OS Development Rust, x86 Assembly, bootloaders, kernel design, memory mgmt
Compilers & Optimization LLVM, MLIR, JIT interpreters, Rust backends
AI/ML Applications PyTorch, ONNX, embedded ML, AI-first language design
Networking & Security Raw sockets, DPI, exploit research, Tor, DNS, WebRTC
Web3/Blockchain Solidity, Ethers.js, smart contract dev

Highlighted Projects

Project Description
Rust-Based JIT Compiler Built a fast JIT interpreter using Rust and LLVM
Raw Socket Sniffer A packet sniffer for low-level traffic inspection
AI Ambulance System Routing system for rural India using React Native + ML
Fraud Detection App Android app using RandomForest for transaction fraud detection
Kapitan Contribution Added HTTPS/Git-based remote inventory fetching
TensorDB JNI-based tensor library for Java using Rust backend
Stock Prediction Model ML pipeline for Indian stock time-series prediction

Currently Exploring

  • Advanced Rust for OS and compiler internals
  • MLIR and AI-based compiler optimization
  • WebRTC and P2P networking
  • Embedded AI runtime on bare metal
  • Mobile AI apps with React Native

Contact


"The best way to predict the future is to invent it."

Pinned Loading

  1. assembly-elf-i386 assembly-elf-i386 Public

    JavaScript 5

  2. kairo-backend kairo-backend Public

    Python 1

  3. NeuroScribe NeuroScribe Public

    Python 1

  4. VPN VPN Public

    C

  5. hardhat-git3 hardhat-git3 Public

    TypeScript

  6. alteredit alteredit Public

    C