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luoolu/README.md
Typing SVG



   



     


$ whoami

class LooLo:
    """Researcher · Vibe Coder · Agent Developer"""

    name       = "luoolu"
    alias      = "LooLo — Algorithm Architect & AGI Explorer"
    location   = "Earth (for now)"
    roles      = ["Researcher", "Vibe Coder", "Agent Developer"]
    focus      = ["AGI", "Computer Vision", "RL", "Time-Series", "LLM Agents"]
    philosophy = "The boundary between intelligence and code is dissolving — fast."
    goal       = "Build systems that think, perceive, and autonomously decide."

    currently  = {
        "researching": "Foundation models for sequential decision-making",
        "vibe_coding": "Turning ideas into reality with AI-assisted flow",
        "building":    "Multi-agent autonomous systems with tool use & planning",
    }

    open_to = [
        "research collaborations",
        "frontier AI discussions",
        "agent development partnerships",
        "interesting problems that need creative solutions",
    ]

    def __repr__(self):
        return "A mind obsessed with making machines think — and coding in the vibe."

Roles & Identities

Researcher

Exploring the frontiers of AI

AGI Computer Vision RL Time-Series Foundation Models

Deep research in machine learning, autonomous reasoning, and scientific discovery systems.

Vibe Coder

Coding in the flow state

AI-Assisted Dev Rapid Prototyping Creative Engineering

Harnessing AI tools to transform ideas into working systems at the speed of thought.

Agent Developer

Orchestrating AI swarms

LLM Agents Tool Use MCP Multi-Agent Systems

Building autonomous agents that reason, plan, use tools, and collaborate to solve problems.


Research Domains

Computer Vision

  • Large-scale self-supervised pre-training (DINOv2, MAE)
  • Fine-grained instance segmentation (Mask2Former)
  • 3D scene reconstruction & spatial understanding
  • Geological thin-section automated analysis

Time-Series Forecasting

  • AutoML ensemble pipelines (AutoGluon v1.2+)
  • Probabilistic & point forecasting at scale
  • Bayesian hyperparameter optimization (HPO)
  • RL-augmented hybrid prediction (KL-8 · v44+)

Reinforcement Learning

  • Model-based & offline RL for sample efficiency
  • Policy optimization: PPO / QR-DQN / Meta-Ensemble
  • Multi-objective & constrained policy learning
  • Sequential decision-making under uncertainty

Foundation Models & AGI

  • Vision-Language models & multimodal reasoning
  • TimesFM, FalconCore, Latent Diffusion Models
  • Autonomous agent frameworks: tool use & planning
  • Self-improving & meta-learning architectures

Agent Development

          +---------------------+
          |   Orchestrator LLM  |
          |  (Planning & Reason) |
          +----------+----------+
                     |
        +------------+------------+
        |            |            |
   +----v----+  +----v----+  +----v----+
   | Research |  |  Code   |  | Review  |
   |  Agent   |  |  Agent  |  |  Agent  |
   +----+-----+  +----+----+  +----+----+
        |            |            |
   +----v----+  +----v----+  +----v----+
   |  Web    |  |  File   |  | Security|
   | Search  |  |  System |  |  Scan   |
   |  Tools  |  |  Tools  |  |  Tools  |
   +---------+  +---------+  +---------+

Building multi-agent systems where specialized AI agents collaborate autonomously — each with distinct tools, memory, and reasoning capabilities.

Layer What I Build Stack
Orchestration Multi-agent pipelines with planning & delegation Claude Code LangGraph CrewAI
Tool Integration MCP servers, function calling, API orchestration MCP Protocol Tool Use REST/gRPC
Memory & State Persistent agent memory, context management Vector DB FAISS Redis
Evaluation Agent benchmarks, reliability testing, evals Custom Evals W&B Pytest

Vibe Coding Philosophy

Vibe Coding
  Vibe Coding Workflow
  ════════════════════

  1. IDEATE     Dream it up, describe the vision
       ↓
  2. PROMPT     Translate intent into AI instructions
       ↓
  3. GENERATE   Let AI write the first draft
       ↓
  4. CURATE     Review, refine, inject domain expertise
       ↓
  5. SHIP       Deploy and iterate at lightning speed

  Tools: Claude Code · Cursor · GitHub Copilot · v0

Current Focus

┌─────────────────────────────────────────────────────────────────────────────┐
│  ACTIVE RESEARCH & DEVELOPMENT                                              │
│                                                                             │
│  [Research]                                                                  │
│  ▸ RL-enhanced time-series forecasting for complex sequential data          │
│  ▸ Foundation model adaptation for geological computer vision               │
│  ▸ Sparse reward RL in partially-observable real-world environments         │
│                                                                             │
│  [Agent Development]                                                        │
│  ▸ Multi-agent LLM systems for autonomous scientific reasoning              │
│  ▸ Tool-augmented agents with MCP protocol integration                      │
│  ▸ Self-improving agent loops with evaluation-driven iteration              │
│                                                                             │
│  [Vibe Coding]                                                              │
│  ▸ AI-first development workflows & rapid prototyping pipelines             │
│  ▸ Claude Code extensions & custom skill development                        │
└─────────────────────────────────────────────────────────────────────────────┘

Interactive Hub — 01 Digital World

Live demos of AGI concepts and cutting-edge algorithms. Click -> explore -> fork

  Demo Description Stack
CV Machine Vision DINOv2 + Mask2Former thin-section segmentation PyTorch CUDA MMSeg
TS Time-Series KL-8 sequence prediction · AutoGluon v1.2 + RL v44 AutoGluon Ray XGBoost
RL Reinforcement Learning PPO / QR-DQN / Meta-Ensemble sequential agents SB3 Gymnasium RLlib
AGI AGI Playground Multi-agent LLM + Vision LLM co-reasoning system LangChain GPT-4V FAISS

Tech Stack

Languages

Python C++ C MATLAB JavaScript TypeScript

ML / DL Frameworks

PyTorch TensorFlow HuggingFace OpenCV scikit-learn AutoGluon

Agent & AI Tools

Claude LangChain Cursor MCP

Infrastructure & MLOps

CUDA Docker Ubuntu Git W&B Ray


A Day in the Life

Morning    Research papers, experiment design, literature review
Afternoon  Vibe coding — prototype ideas with AI assistance
Evening    Agent development — build & test multi-agent pipelines
Night      Open source contributions & community collaboration

GitHub Metrics



Connect

Email   LinkedIn   Twitter   Portfolio   WeChat


"01 Digital World" — Exploring, sharing, and co-building the future AI ecosystem.
If my work sparks an idea or saves you time, a star is the best thanks.



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