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
T5 FlexAttention
T5 model optimized with FlexAttention
AI Shell
A transparent shell wrapper for building context-aware AI tools
minLoRA
A minimal library for LoRA (200 LoC!), supports any model in PyTorch
Anim·E
State-of-the-art anime image generator at the time, before Stable Diffusion fine-tuned models
Mini Projects
Mixture of Depths
I implemented Mixture of Depths from Google DeepMind's paper
Multi-head Latent Attention
I implemented Multi-head Latent Attention from deepseek-v2
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
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.