Jonathan's Website

Jonathan Chang - Personal Website

Jonathan Chang, machine learning engineer with focus on LLMs and generative models

Jonathan Chang

I'm an experienced machine learning engineer with a focus on LLM and generative image models. I'm passionate about AI research and open-source projects.

email: contact at jonathanc dot net

Projects

Visual acuity test chart with letters of decreasing size for AI model evaluation

Visual Acuity Test for LLMs

Research, 2025

Evaluating AI models' ability to read fine details in high-resolution images

Performance comparison chart showing tokens per second between flex-nano-vllm and vLLM

flex-nano-vllm

Code, 2025

A minimal vLLM inference engine built from scratch using PyTorch FlexAttention

MIST robot prototype showing expressive face

Project MIST

Experiment, 2025

Building the MIST robot prototype with AI-assisted design

Visualization of Additive Rotary Embedding technique for position encoding in LLMs

Additive Rotary Embedding

Research, 2024

A competitive variant of rotary position embedding (RoPE)

Code snippet showing minLoRA implementation - minimal LoRA library in 200 lines of code

minLoRA

Code, 2023

A minimal library for LoRA (200 LoC!), supports any model in PyTorch

... View all

More Projects

Archive

Browse all projects

Blog

Dec 13, 2025

Claude Daemon

Claude Code tutorial: Running Claude in yolo mode safely using macOS user isolation and ACLs for fine-grained directory access control

Aug 7, 2025

vLLM from scratch with FlexAttention

Building a minimal vLLM inference engine using PyTorch FlexAttention and paged attention from scratch

Jul 15, 2025

MIST Bench: Building the MIST robot from Pantheon

Using AI to build a robot inspired by the animated series Pantheon

All posts

Timeline

2022 - 2024 · Taboola

Spend some time working in algorithm team, worked on feature engineering and designed experiments. Later joined the Generative AI team, where I integrated and optimized SoTA image models into our product.

2021-2022 · BigScience Project

I contributed to the BigScience project, mainly in the metadata working group. I worked on the training codebase and conducted research experiments on using metadata to improve language model performance.

2021-2022 · ASUS AICS

I spent 6 months in the AICS department, where we collaborated with local hospitals. I worked on medication recommendation models using BERT.

2020-2021 · NTU MiuLab

I worked with Prof. Yun-Nung Chen on SoTA Dialogue System based on GPT2. We participated in the Situated Interactive MultiModal Conversations (SIMMC) Challenge (DSTC9) and achieved 3rd place.

2020 · Google

Spent a summer at Google, internship was replaced with a remote project due to COVID-19. I worked on a project using NLP to recommend relevant articles to users.

2017-2021 · National Taiwan University

Completed my undergraduate studies in Computer Science, focusing on machine learning and artificial intelligence. I was a TA for the course Applied Deep Learning.