Skip to content
View matrix97317's full-sized avatar

Block or report matrix97317

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
matrix97317/README.md

Hi, I'm [matrix97317] 👋

AI Algorithm × AI Infra × Full-Stack Robotics

对技术有极致追求,对产品有较高审美 —— 追求极致的好看与好用。
Relentless about engineering excellence, obsessed with product aesthetics — built to be beautiful and usable.


🧭 关于我 / About Me

中文

我是一名横跨 AI 算法、AI Infra 与机器人系统 的工程师,习惯从「算法 → 框架 → 算子 → 部署 → 产品」端到端地把事情做成。

  • 🔬 AI 算法:自动驾驶感知、视频理解、行为检测
  • ⚙️ AI Infra:深度学习训练框架、算法框架、大模型训练框架、推理引擎、算子开发
  • 🤖 应用落地:全栈机器人研发(数据 → 模型 → 部署 → 机器人控制)
  • 🎨 工程审美:既是技术极客,也是产品狂,追求极致的好看与好用

我相信优秀的系统 = 扎实的底层 + 优雅的抽象 + 克制的产品设计。

English

I'm an engineer working across AI algorithms, AI Infra, and robotics systems, comfortable owning the full path from algorithm → framework → kernel → deployment → product.

  • 🔬 AI Algorithms: autonomous driving perception, video understanding, action detection
  • ⚙️ AI Infra: deep learning training frameworks, algorithm frameworks, LLM training frameworks, inference engines, kernel development
  • 🤖 Applied Systems: full-stack robotics (data → model → deployment → robot control)
  • 🎨 Engineering Taste: a technical perfectionist and product fanatic — chasing the极致 of beauty and usability

Great systems = solid foundations + elegant abstractions + restrained product design.


🛠 技术栈 / Tech Stack

AI 算法 / AI Algorithms PyTorch Computer Vision Autonomous Driving Video Understanding Action Detection

AI Infra Training Framework LLM Training Inference Engine CUDA Kernel Dev

机器人 / 应用 / Robotics & Applications Robotics Robot Control Deployment

工程 / 工具 / Engineering & Tools Python C++ Linux Docker Git


🚀 代表方向 / Core Areas

🔬 AI 算法 / AI Algorithms

  • 自动驾驶感知(检测 / 分割 / 多传感器融合)
    Autonomous driving perception (detection / segmentation / sensor fusion)
  • 视频理解(时序建模、视频表征)
    Video understanding (temporal modeling, video representation)
  • 行为检测与识别
    Action detection & recognition

⚙️ AI Infra

  • 深度学习训练框架开发
    Deep learning training framework development
  • 算法框架 / 大模型训练框架
    Algorithm frameworks / LLM training frameworks
  • 大模型推理引擎
    LLM inference engines
  • 高性能算子(CUDA / Kernel)开发
    High-performance kernel development (CUDA / Kernel)

🤖 全栈机器人 / Full-Stack Robotics

  • 数据采集与标注流水线
    Data collection & annotation pipelines
  • 模型训练与优化
    Model training & optimization
  • 端侧 / 云侧部署
    On-device / cloud deployment
  • 机器人控制集成
    Robot control integration

🎨 产品与审美 / Product & Taste

  • 追求极致的好看与好用
    Chasing极致 beauty and usability
  • 端到端产品化思维
    End-to-end product mindset
  • 工程体验与抽象设计
    Developer experience & abstraction design

📌 精选项目 / Selected Projects

  • OneNeuralNetwork — 中文:跨芯片平台的算子集合与统一神经网络库,后端基于 TVM / Triton 等深度学习编译器,目标是在异构芯片上运行 OpenMMLab、Detectron、DeepSpeed、Megatron-LM 等上层应用。
    EN: A cross-chip operator collection and unified neural network library, built on DL compiler backends (TVM, Triton) to run OpenMMLab / Detectron / DeepSpeed / Megatron-LM on heterogeneous platforms.

  • OneTensor — 中文:极简 Tensor 库,专为手写 CUDA kernel 时快速构造测试数据而设计,支持 Tensor 创建、Host/Device 数据搬运、npy/npz 加载与数据显示,相比 PyTorch/Cute 更轻量。
    EN: A minimal Tensor library for quickly creating test data when writing CUDA kernels — Tensor creation, host/device transfer, npy/npz loading, and data view, lighter than PyTorch/Cute.

  • RLink — 中文:面向分布式强化学习系统的轻量高性能通信层,解耦 Actor 采样与 Learner 训练,优化轨迹与模型参数的传输延迟。
    EN: A lightweight, high-performance communication layer for distributed RL, decoupling Actor sampling from Learner training and optimizing trajectory/model-parameter transfer latency.

  • pig-solver — 中文:一个 tiny 版本的 PyTorch。
    EN: A tiny PyTorch — a minimal deep learning framework built for learning and hacking.

  • UniRobot — 中文:一个具备训练和真机部署的全栈 robot 工程框架。
    EN: A full-stack robotics engineering framework covering both training and real-world deployment.


“把复杂留给自己,把好用留给用户。”
“Keep the complexity for myself, leave the usability to the user.”

Pinned Loading

  1. pig-solver pig-solver Public

    This is a toy deep-learning computing framework( such as Pytorch,Caffe etc.).

    C++ 1

  2. OneTensor OneTensor Public

    This is a simple and easy-to-use Tensor Library.

    Cuda 10 2

  3. OneNeuralNetwork OneNeuralNetwork Public

    This is a cross-chip platform collection of operators and a unified neural network library.

    Python 17 1

  4. Awesome-Embodied-AI Awesome-Embodied-AI Public

    This repository mainly organizes resources related to embodied intelligence, including data, models, hardware, and software infrastructure.

    10

  5. UniRobot UniRobot Public

    UniRobot is an embodied intelligent software framework that integrates the robot brain (data, models, model training) with the robot body (perception, model inference, control).

    Python 18 1

  6. RLink RLink Public

    RLink is a lightweight and efficient communication layer designed specifically for distributed reinforcement learning systems.

    Python 3