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Leafyte/README.md


๐Ÿ—‚๏ธ ย ๐™ฐ๐š‹๐š˜๐šž๐š ๐™ผ๐šŽ

CS Engineering student at VVCE, Mysuru, building under DebugLeaf. Focused on Edge AI, TinyML, full-stack AI systems, and computer vision. Currently researching offline conversational AI for resource-constrained devices. Open to SWE / AI-ML / Backend / Research internships.

๐Ÿš€ ย ๐™ต๐šŽ๐šŠ๐š๐šž๐š›๐šŽ๐š ๐™ฟ๐š›๐š˜๐š“๐šŽ๐šŒ๐š๐šœ

PRISM โ€” offline conversational AI on a Raspberry Pi 4B, subject of an accepted ICIDTSM 2026 paper ๐Ÿท๏ธ Edge AI NLP Embedded

SkySentinel โ€” browser-based AI drone disaster-response simulator with A* pathfinding & swarm coordination ๐Ÿท๏ธ Next.js Three.js Swarm AI

DebugLeaf โ€” my build identity, spanning research, full-stack AI, and hackathon prototypes ๐Ÿท๏ธ Systems Full-Stack AI

๐Ÿ”ฌ ย ๐š๐šŽ๐šœ๐šŽ๐šŠ๐š›๐šŒ๐š‘ & ๐™ฟ๐šž๐š‹๐š•๐š’๐šŒ๐šŠ๐š๐š’๐š˜๐š—๐šœ

๐Ÿ“„ A Hybrid Contextual Reasoning Architecture for Fully Offline Conversational AI on Resource-Constrained Edge Devices โ€” extended abstract on PRISM, accepted at ICIDTSM 2026, IIT Madras Co-authors: Kiran A V, Om M Doddamani, Kishor A V, Jeevan Nullipady Mallya, A B Rajendra

๐Ÿงช ML Model Compression for Embedded Systems โ€” CNN/Transformer compression pipeline (low-rank factorization, quantization, dynamic scaling) ๐Ÿท๏ธ LoRA MCUNet Tucker Decomposition HAWQ-V2 Once-for-All

๐Ÿ“š ย ๐™ป๐šŽ๐šŠ๐š›๐š—๐š’๐š—๐š ๐™น๐š˜๐šž๐š›๐š—๐šŽ๐šข

โ˜• Java โ€” OOP fundamentals via projects like a Java Airline Reservation System & Smart Delivery Route Optimizer ๐Ÿงฎ DSA โ€” ongoing practice, incl. a Graph Theory / Dijkstra's seminar with interactive demos โš™๏ธ Backend Dev โ€” Flask, Supabase, SQLite across ML APIs & full-stack platforms ๐Ÿ† Hackathons โ€” regular participant, shipping full products in 24-hour windows ๐Ÿ‡ฏ๐Ÿ‡ต Japanese โ€” learning alongside technical work

๐Ÿ† ย ๐™ฐ๐šŒ๐š‘๐š’๐šŽ๐šŸ๐šŽ๐š–๐šŽ๐š—๐š๐šœ
  • Extended abstract on PRISM accepted at ICIDTSM 2026, IIT Madras
  • Full academic research paper on ML model compression for embedded systems
  • Graph Theory / Dijkstra's algorithm seminar for VVCE's Math Tea Club
  • Multiple hackathon builds shipped end-to-end under tight deadlines
๐Ÿ“Š ย ๐™ถ๐š’๐š๐™ท๐šž๐š‹ ๐š‚๐š๐šŠ๐š๐š’๐šœ๐š๐š’๐šŒ๐šœ



Snake animation powered by a Platane/snk GitHub Action โ€” see workflow below.

โ–ธ snake workflow yaml
name: snake
on:
  schedule: [{cron: "0 */6 * * *"}]
  push: {branches: [main]}
  workflow_dispatch: {}
permissions:
  contents: write
jobs:
  generate:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: Platane/snk@v3
        with:
          github_user_name: leafyte
          outputs: dist/github-contribution-grid-snake-dark.svg?palette=github-dark
      - uses: crazy-max/ghaction-github-pages@v4
        with: {target_branch: output, build_dir: dist}
        env: {GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}}
๐Ÿ“ก ย ๐™ฒ๐š˜๐š—๐š๐šŠ๐šŒ๐š


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