Jingyang Zhang
Ph.D. candidate @ Duke
I’m currently a Machine Learning Engineer at Sciforium, focusing on the development latest multi-modal LLMs. Previously, I got my Ph.D. at Duke ECE where I have the honor to be advised by Prof. Yiran Chen and Prof. Hai (Helen) Li. I obtained my Bachelor degree in 2019 from the Department of Electronic Engineering at Tsinghua University. My dissertation research topics include adversarial machine learning and distributional shifts (specifically out-of-distribution detection). I have interned at Bosch Center for AI and Tesla over the summers.
I’m a big fan of open-source projects. Notably, I’m one of the main contributors to OpenOOD, the largest (and arguably the most well-recognized) codebase for out-of-distribution detection (on image data). I also develop lmms-finetune, a lightweight framework for fine-tuning a variety of vision LLMs on custom data.
I write technical blogs from time to time. You can find them on Medium and 知乎.
news
| Jan 06, 2025 | I start my job as a Machine Learning Engineer at Sciforium today. As one of the founding team members, I will be developing the latest byte-based, multi-modal LLMs and touching almost every aspect of the whole spectrum, including data curation, model development, training, and deployment. |
|---|---|
| Dec 15, 2023 | Excited to present our work OpenOOD v1.5 as an oral presentation at NeurIPS DistShift workshop! See [html][code][arxiv] for more details. |
| May 13, 2023 | I’m joining Tesla as a Machine Learning Intern this summer. |
| Aug 16, 2022 | Excited to share that our work MixOE (fine-grained OOD detection) has been accepted to WACV2023! See [html][code][arxiv] for more details. |
| May 23, 2022 | I’m joining Bosch Center for AI as a Machine Learning Research Intern this summer. |
