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ChristianLin0420/README.md

Hi 👋, I'm Christian Lin

A passionate Machine Learning Engineer and Researcher from Taiwan

Hey there, I'm Cyristian!

WHO AM I ?

A dedicated Machine Learning Engineer with a strong academic background from National Tsing Hua University (Master's GPA: 3.99). I specialize in developing scalable ML solutions and have experience in both cutting-edge research and practical applications. Currently pursuing research exchange at UCLA, I'm passionate about pushing the boundaries of AI technology through collaborative innovation.

MY EXPERIENCES

Machine Learning Engineer, NVIDIA --- 2025.Mar - Present

  • Currently contributing to NVIDIA's machine learning initiatives

Machine Learning Engineer Intern, Google --- 2023.Jul - 2023.Oct

  • Developed a high-performance Convolutional-Recurrent model for touchpad gesture and mouse movement recognition
  • Achieved 98% average accuracy with optimized memory usage using TensorRT
  • Built end-to-end ML pipeline using TensorFlow's C++ API for rapid development and deployment

Cloud Solution Architect Intern, Microsoft --- 2022.Aug - 2023.Jun

  • Integrated Azure Cognitive Services and OpenAI services (GPT-3.5, GPT-4) into enterprise solutions
  • Optimized Large Language Models using DeepSpeed framework for enhanced production efficiency
  • Implemented custom solutions for Microsoft Teams using Azure OpenAI services

ELSA Laboratory Researcher, NTHU --- 2021.Sep - 2024.Dec

  • Developed "Transfermer," a novel Transformer-based MARL framework achieving 50% improved training efficiency
  • Integrated few-shot and zero-shot learning techniques into pre-trained Multi-agent Reinforcement Learning models

HMI Laboratory Researcher, NTHU --- 2020.Sep - 2022.Aug

  • Advanced brain signal simulation using GPT2 model, achieving 25% improved accuracy
  • Developed innovative GPT2xCNN architecture for enhanced signal generation quality

PUBLICATIONS

"HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network" (ICML 2024, First Author)

CURRENT WORKS & CONTACT INFORMATION

CERTIFICATIONS

  • Deep Learning Specialization (DeepLearning.AI)

  • TensorFlow: Advanced Techniques Specialization (DeepLearning.AI)

  • Getting Started with Accelerated Computing in CUDA C/C++ (Nvidia)

  • Project Management Specialization (Google)

  • Love to learn neuroscience in order to create a real AI!!!!

Connect with me:

bor jiun lin christian lin （林柏均） imchristianbutnotchristian christianlin christianlin_0420

PROFICIENCY

Languages and Tools:

arduino c cplusplus css3 figma firebase git java javascript linux matlab mysql opencv pandas postgresql postman python pytorch react scikit_learn seaborn swift tensorflow

christianlin0420

 christianlin0420

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  1. universalMARL Public

    This project mainly focus on how to transfer agents' knowledge in order to improve the flexibility of the MARL model and the training efficiency.

    Python 2

  2. HGAP Public

    Official implementation for ICML 2024 paper "HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network".

    Python 4 1

  3. state-space-model-universal Public

    A research project implementing state-of-the-art sequence modeling architectures, focusing on State Space Models (SSMs) and their variants.

    Python 1

  4. multi-agent-universal Public

    A comprehensive Multi-Agent Reinforcement Learning framework for research and development, featuring distributed training and multiple environment support.

    Python 1 1

  5. alphastar-rebuild Public

    A comprehensive PyTorch implementation of DeepMind's AlphaStar, an AI system that achieved Grandmaster level in StarCraft II. This project reimagines the groundbreaking architecture with modern PyT…

    Python 2

  6. diffusion-model-universal Public

    A comprehensive PyTorch-based framework for training and experimenting with various diffusion models. This project provides a modular and flexible implementation of multiple diffusion model variant…

    Python 1