A Multi-Document Summarization Dataset created to help lawyers summarize long and complex documents from lawsuits.
I am a first 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.
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.