Welcome to the page of LEAF Lab!
LEAF represents four types of skills that are invaluable in the machine learning related research,
including Learning, Exploring, Analyzing, and Formulating.
In LEAF lab, we are interested in data mining, machine learning and natural language processing with
particular applications in healthcare domain. We conduct fundamental research and develop advanced methods
to solve challenges in healthcare. We perform data annotations and create high-quality data for the community
to design and test advanced machine learning models.
We also develop tools to support and demonstrate our research and
make them fun and easy to use for people to learn and explore.
If you are interested in learning more about our research, collaborating, or joining the LEAF lab, please feel free to email
Dr. Ping Wang at ping.wang [at] stevens.edu.
- 09/2023: Paper about Semi-Structured Automatic ICD Coding accepted by NeurIPS 2023.
- 08/2023: Paper about multi-label clinical time-series generation via conditional GAN by TKDE.
- 08/2023: Paper about task as context data annotation for inter-dependent tasks accepted by HCOMP 2023.
- 07/2023: Paper about natural language querying on NoSQL database accepted by ACM BCB 2023.
- 06/2023: Received NSF CRII award on the project about
reasoning argumented searching. Thanks, NSF!
- 03/2023: Congratulations to Xinming Yang for being admitted to the PhD program at CUNY!
- 03/2023: Recognized for excellence in teaching in Fall 2022.
- 02/2023: Demo paper about an interactive tool for event detection exploration accepted by ACM IUI.
- 01/2023: Paper about learnersourced content moderation of learning materials accepted by the workshop on Partnerships for Cocreating Educational Content.
- 12/2022: Congratulations to Kangping Zeng for being admitted to the data science PhD progam at Stevens!
- 11/2022: Invited talk in CS 101 Research and Entrepreneurship in Computing at CS@Stevens.
- 09/2022: Paper about crowdsourcing inter-dependent tasks accepted by HCOMP.
- 08/2022: Welcome Chengyang and Wenlong to join the LEAF Lab!
- 06/2022: Paper about knowledge base question answering on clinical notes accepted by ACM BCB.
- 05/2022: Invited to serve as area chair for the inference and question answering track in COLING 2022.
- 04/2021: Invited talk at the CS department, The University of Massachusetts Lowell.
- 10/2021: Invited talk at the ECE department, Stevens and the CS department, The University of Hong Kong.
- 08/2021: Paper about the interpretation for document classification accepted by TKDD.