Junho Park

Building intelligent systems that matter |

Machine Learning Deep Learning MLOps NLP Computer Vision

01. Latest Posts

Deep Learning 2026.01.05

Scaling Transformers: A Practical Guide

This article explores methods and optimization techniques for efficiently scaling Transformer models in production environments.

PyTorch Optimization Distributed
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MLOps 2026.01.02

Building Robust ML Pipelines with Kubeflow

A practical guide to building stable and scalable machine learning pipelines in Kubernetes-based infrastructures.

Kubernetes CI/CD Pipeline
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Computer Vision 2025.12.28

Real-time Object Detection at the Edge

An in-depth introduction to model compression and optimization strategies for real-time object detection on edge devices.

YOLO TensorRT Edge AI
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NLP 2025.12.20

Fine-tuning LLMs: Best Practices

A comprehensive overview of effective methodologies and key considerations for fine-tuning large language models for specific domains.

LLM Fine-tuning PEFT
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Research 2025.12.15

Understanding Diffusion Models

A deep dive into the mathematical foundations and practical implementations of Diffusion Models, a core technology behind modern generative AI.

Generative AI Diffusion Theory
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Tools 2025.12.10

My AI Development Toolkit 2025

A curated overview of essential tools and development environment setups that AI engineers rely on in their daily workflows.

Tools Productivity DevOps
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02. Featured Projects

01

TCN–SNN for sEMG Gesture

Spiking-based temporal models for sEMG-driven neuroprosthetic control.

Python PyTorch snnTorch sEMG
Project preview
02

Spike-based Navigation for Mobile Robots

Production-ready template for neuromorphic edge robotics (ROS2 + snnTorch + FastAPI + Docker).

ROS2 snnTorch Matlab Docker FastAPI
Project preview
03

Efficient Spatiotemporal World Model

In-progress latency-aware world model for long-horizon prediction in autonomous systems.

World Model Temporal Modeling Efficiency MLflow
Project preview
04

Job Agent

Browser-extension–driven job application assistant.

Chrome Extension LLM Analytics ATS Scoring
Project preview

03. About Me

Junho Park | MSc Cybersecurity & AI (Merit) · University of Sheffield, UK

Hello, I’m an Applied AI Engineer who enjoys translating AI technologies into practical solutions for real-world challenges.

I am highly interested in building end-to-end AI systems, from machine learning model development to production deployment. In particular, I have a strong interest in Deep Learning, Natural Language Processing, and Computer Vision, and I enjoy solving the practical challenges that arise when applying state-of-the-art research to real-world services.

Technical Skills

AI/ML

  • PyTorch
  • TensorFlow
  • Scikit-learn
  • Hugging Face

MLOps

  • Docker
  • Kubernetes
  • MLflow
  • Kubeflow

Backend

  • Python
  • FastAPI
  • PostgreSQL
  • Redis

Cloud

  • AWS
  • GCP
  • Azure
  • Terraform
~/profile.py
class AIEngineer:
    def __init__(self):
        self.name = "Junho Park"
        self.role = "Applied AI Engineer"
        self.interests = [
            "Deep Learning",
            "NLP",
            "Computer Vision",
            "MLOps"
        ]
    
    def get_passion(self):
        return "Building AI that matters"

# Initialize
engineer = AIEngineer()
print(engineer.get_passion())