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
Highlight Projects
Notable Projects
Santa Hat AI
An webapp that uses AI to place a santa hat on your profile picture, using MediaPipe
vFLUX
An optimized FLUX model inference engine
AI Shell
A transparent shell wrapper for building context-aware AI tools
Anim·E
State-of-the-art anime image generator at the time, before Stable Diffusion fine-tuned models
Other Projects
WikiMCP
A MCP server to let Claude explore random Wikipedia pages
LLMCP
A minimal MCP server for LLM to query other LLMs via LiteLLM and MCP.
Forking an AI Agent
A MVP exploring fork() pattern for AI agents
T5 FlexAttention
T5 model optimized with FlexAttention
Multi-head Latent Attention
I implemented Multi-head Latent Attention from deepseek-v2
Mixture of Depths
I implemented Mixture of Depths from Google DeepMind's paper
Flex Diffusion
I fine-tuned Stable Diffusion 2 for dynamic aspect ratio generation
DDIM inversion notebook
My popular notebook demonstrating DDIM inversion using Stable Diffusion
Blog
View allLLMProc: Thinking in Processes, Not Agents
Introducing a Unix-inspired framework for building robust, composable LLM applications
Maximizing PyTorch Throughput with FastAPI
Techniques to optimize your PyTorch inference server for maximum throughput using FastAPI
Exploring the Effective Rank of Projection Weights in Attention
A deep dive into the low-rank structure of attention projection matrices in LLMs
Additive Rotary Embedding
A competitive variant of rotary position embedding (RoPE) with interesting properties
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 medicine recommendation/prediction model using NLP.
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.