A Multi-Document Summarization Dataset created to help lawyers summarize long and complex documents from lawsuits.
I am a second year PhD Student at MIT CSAIL,
working at the intersection between NLP and HCI.
On the NLP side, I am interested in language understanding in scientific, legal, or clinical text, documents that are typically authored and used by domain experts.
On the HCI side, I explore how humans, especially domain experts, and AI models, e.g., Large Language Models, can communicate and collaborate.
I also developed a suite of tools for document understanding and parsing. Please check my projects on Document Intelligence for more information.
Besides research, I've worked on various open source projects and here are a few of them:
A platform for current and past grad students to share their statement of purposes during application to help future applicants. It is a full-fledged website based on notion, and we develop an automated submission system that connects the notion database with a google form (code available here).
Also based on jekyll and bulma, the Avalanche theme can be used out-of-the box for creating an academic site beautifully displaying personal research description, publications, as well as recent news.
A JupyterLab extension that seamlessly connects GPT-4 to your coding environment. It features a code interpreter that can translate your natural language description into Python code and automatically execute it.
A Python package that seamlessly connects notion databases and pandas dataframe. It allows for easy uploading/downloading Notion databases to/from pandas dataframe.
An Obsidian plugin that streamlines bibliography management.
Whenever you have any questions regarding my research (or just want to say hi), the best email address to find me is zejiangshen^~gmail.com.